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1
Mathonsi, Topside E., Tshimangadzo Mavin Tshilongamulenzhe, and Bongisizwe Erasmus Buthelezi. "Enhanced Resource Allocation Algorithm for Heterogeneous Wireless Networks." Journal of Advanced Computational Intelligence and Intelligent Informatics 24, no. 6 (November 20, 2020): 763–73. http://dx.doi.org/10.20965/jaciii.2020.p0763.
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In heterogeneous wireless networks, service providers typically employ multiple radio access technologies to satisfy the requirements of quality of service (QoS) and improve the system performance. However, many challenges remain when using modern cellular mobile communications radio access technologies (e.g., wireless local area network, long-term evolution, and fifth generation), such as inefficient allocation and management of wireless network resources in heterogeneous wireless networks (HWNs). This problem is caused by the sharing of available resources by several users, random distribution of wireless channels, scarcity of wireless spectral resources, and dynamic behavior of generated traffic. Previously, resource allocation schemes have been proposed for HWNs. However, these schemes focus on resource allocation and management, whereas traffic class is not considered. Hence, these existing schemes significantly increase the end-to-end delay and packet loss, resulting in poor user QoS and network throughput in HWNs. Therefore, this study attempts to solve the identified problem by designing an enhanced resource allocation (ERA) algorithm to address the inefficient allocation of available resources vs. QoS challenges. Computer simulation was performed to evaluate the performance of the proposed ERA algorithm by comparing it with a joint power bandwidth allocation algorithm and a dynamic bandwidth allocation algorithm. On average, the proposed ERA algorithm demonstrates a 98.2% bandwidth allocation, 0.75 s end-to-end delay, 1.1% packet loss, and 98.9% improved throughput performance at a time interval of 100 s.
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Liu, Huiying, Bo Xi, Ying Wang, Yuling Guo, and Botao Hou. "Dynamic Channel Allocation Algorithm for Heterogeneous Cellular Networks in Power Communication." Journal of Nanoelectronics and Optoelectronics 17, no. 6 (June 1, 2022): 983–90. http://dx.doi.org/10.1166/jno.2022.3264.
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In order to solve the problems of low efficiency and high noise in the application of modern channel resource allocation methods, an anti-interference dynamic channel allocation algorithm for heterogeneous cellular networks in power communication is proposed. First, the heterogeneous cellular network model of power communication and the architecture of power multi-channel transmission platform are constructed. Then, according to the receiving and noise characteristics of communication resources, the anti-interference algorithm of power communication resources under multi-channel transmission is designed to obtain the communication index of power communication heterogeneous cellular network, and the anti-interference dynamic allocation algorithm of power communication heterogeneous cellular network resources is realized, Finally, the comparison method is used to prove the practicability of the method in this paper. The experimental results show that the average value of communication resources after interference suppression is 950 Mb, the average signal to noise ratio is 10.5 dB, and the resource allocation time is less than 3 min after 5000 iterations, which is superior to the comparison method. The method has good channel anti-interference ability and channel resource allocation efficiency, and has certain application value.
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Du, R. F., Y. J. Zhang, Y. G. Liu, S. H. Liu, F. Wang, X. Zhang, and J. C. Xie. "Application of water resource multi-objective allocation service based on digital water network." Water Supply 22, no. 3 (December 23, 2021): 2683–94. http://dx.doi.org/10.2166/ws.2021.448.
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Abstract The rational allocation of water resources plays an important role in alleviating disparities between supply and demand in areas with water shortages. With the continuous development of modern information technology, the pace of digitization is accelerating. Digital water networks provide a means of technical support, and their application is becoming more extensive. Based on the traditional study of water resource allocation combined with the development of modern information technology, this paper proposes a new operational application model of multi-objective water resource allocation based on a digital water network and applies this model to allocate water resources in the Heihe River basin in Xi'an, Shaanxi Province. First, a topological digital water network is constructed based on the connectivity criterion of water systems, and a cooperative configuration model with social, economic and ecological objectives is established. Second, the model and its solution method are componentized, and the water resource allocation business system is constructed based on the comprehensive integration platform to integrate the digital water network and the water resource multi-objective allocation business. Finally, to verify the scientificity and feasibility of the new model, the new model was applied to allocate water resources in the Heihe River basin of Xi'an city, Shaanxi Province.
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Sun, Xiao. "Resource Allocation and Scheduling in Modern Cloud Computing." ACM SIGMETRICS Performance Evaluation Review 50, no. 3 (December 30, 2022): 32–35. http://dx.doi.org/10.1145/3579342.3579351.
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With various types of resources, infrastructures and users participating in the current big data ecosystem at an astonishing speed, resource allocation and scheduling has been identified as one of the key areas needing substantial research for the advancement of system performance.
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Gayathri, S., and R. Sabitha. "Resource Allocation in Downlink of LTE using Bandwidth Prediction Through Statistical Information." Indonesian Journal of Electrical Engineering and Computer Science 10, no. 2 (May 1, 2018): 680. http://dx.doi.org/10.11591/ijeecs.v10.i2.pp680-686.
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<span lang="EN-US">Long Term Evolution (LTE) is the technology used in modern third and fourth generation mobile wireless cellular networks. Due to the presence of large number of users, mobility and varying channel conditions, proper resource allocation is essential to provide a good user experience and improve the system throughput. In this paper, a resource allocation algorithm is implemented that will use the probabilistic models to predict the channel condition and allocate resources accordingly. Also, the algorithm will support QoS requirements. During the resource allocation, the channel quality information is collected and analyzed to predict the future channel conditions and resource allocation vectors are configured accordingly. The performance of the algorithm is analyzed based upon the data collected. The algorithm is able to provide a reasonable success rate for channel prediction. By using the resource allocation vectors and channel prediction, the algorithm performance also is improved considerably due to the lesser space and time complexity required.</span>
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Gao, Ying, Cong Liu, Qingtian Zeng, and Hua Duan. "Two Effective Strategies to Support Cross-Organization Emergency Resource Allocation Optimization." Mobile Information Systems 2021 (January 4, 2021): 1–15. http://dx.doi.org/10.1155/2021/7965935.
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Cross-organization emergency resource allocation optimization problem is essential to guarantee a successful emergency disposal, and it has become a research focus of modern emergency management. Generally speaking, there are two possible types of resource allocation scenarios: (1) if the emergency resources are overallocated, on the one hand, parallel execution of independent emergency activities can be supported and the emergency disposal time is reduced; on the other hand, too many idle resources may cause low resource utilization rate, high scheduling overhead, and high cost; and (2) if emergency resources are underallocated, this may lead to resource conflicts and the need for some emergency activities to wait for others to complete, and finally the emergency disposal time may increase. Therefore, reasonable emergency resource allocation strategies are highly desired. To the best of our knowledge, there is no formal approach to support the cross-organization emergency resource allocation issue. To handle this problem, we propose a two-layered framework to facilitate the allocation of limited emergency resources to meet its time constraints with high efficiency. More specifically, a kind of Petri net extended with time, resource, and message information, denoted as CE-net, is presented to model cross-organization emergency response processes. Based on the obtained CE-net, the minimum resource requirements are obtained with corresponding algorithms. Then, Minimum Execution Time (MET) strategy and Minimum Resource Consumption (MRC) strategy with their corresponding estimated execution intervals are introduced to facilitate the stakeholder to determine which strategy is suitable according to the timing requirements. A cross-organization fire emergency case is applied to validate the proposed approaches throughout the whole paper.
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Olafsson, Sverrir. "Resource Allocation as an Evolving Strategy." Evolutionary Computation 4, no. 1 (March 1996): 33–55. http://dx.doi.org/10.1162/evco.1996.4.1.33.
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The efficient utilization of resources is an issue of essential importance in modern network management. The emergence of increasingly complicated and continuously changing network services requires softer and fuzzier methods in network management. In this paper we demonstrate how evolutionary game theory can be used for an efficient allocation of service requirements onto an ensemble of heterogeneous network components. By incorporating differentiated pricing structures into a system utility function, network agents are encouraged to increase their usage of those components that are presently badly utilized. It is demonstrated how this approach can enhance network utilization significantly. Some new results regarding evolutionarily stable strategies in nonlinear evolutionary games are also reported.
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El-ghorab, Mahmoud Ahmed, Mohamed Rihan El-meligy, Mohamed Mostafa Ibrahim, and Fatma Newagy. "Energy-Efficient User Pairing for Downlink NOMA in Massive MIMO Networks." Applied Sciences 12, no. 11 (May 27, 2022): 5421. http://dx.doi.org/10.3390/app12115421.
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The motivations for deploying energy and spectral-efficient network architectures are the high energy consumption and the need for more spectral resources in modern cellular networks. The key method to solve the energy efficiency EE maximization problem of the downlink non-orthogonal multiple access (NOMA)-based massive MIMO system is to decouple it into user pairing and efficient power allocation problems. This work studies the performance of three main pairing methods in NOMA-based networks: Hungarian, Gale–Shapley, and correlation-based approaches. Firstly, we provide a mathematical analysis for EE of downlink NOMA in a massive MIMO system for the non-line of sight (NLoS) channel model with perfect successive interference cancellation (SIC). Finally, the sequential convex programming (SCP) approach is used to tackle the power allocation problem. Simulation results show that the Hungarian algorithm for pairing plus SCP for power allocation (Hungarian algorithm-SCP) achieves the highest energy efficiency among all the three pairing algorithms with an identical performance to joint user and resource block association with power allocation (joint user-RB PA) algorithm but with much lower computational complexity and outperforms the NOMA SCP greedy algorithm (NOMA-SCP-GA).
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Dechouniotis, Dimitrios, Nikolaos Athanasopoulos, Aris Leivadeas, Nathalie Mitton, Raphael Jungers, and Symeon Papavassiliou. "Edge Computing Resource Allocation for Dynamic Networks: The DRUID-NET Vision and Perspective." Sensors 20, no. 8 (April 13, 2020): 2191. http://dx.doi.org/10.3390/s20082191.
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The potential offered by the abundance of sensors, actuators, and communications in the Internet of Things (IoT) era is hindered by the limited computational capacity of local nodes. Several key challenges should be addressed to optimally and jointly exploit the network, computing, and storage resources, guaranteeing at the same time feasibility for time-critical and mission-critical tasks. We propose the DRUID-NET framework to take upon these challenges by dynamically distributing resources when the demand is rapidly varying. It includes analytic dynamical modeling of the resources, offered workload, and networking environment, incorporating phenomena typically met in wireless communications and mobile edge computing, together with new estimators of time-varying profiles. Building on this framework, we aim to develop novel resource allocation mechanisms that explicitly include service differentiation and context-awareness, being capable of guaranteeing well-defined Quality of Service (QoS) metrics. DRUID-NET goes beyond the state of the art in the design of control algorithms by incorporating resource allocation mechanisms to the decision strategy itself. To achieve these breakthroughs, we combine tools from Automata and Graph theory, Machine Learning, Modern Control Theory, and Network Theory. DRUID-NET constitutes the first truly holistic, multidisciplinary approach that extends recent, albeit fragmented results from all aforementioned fields, thus bridging the gap between efforts of different communities.
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Skondras, Emmanouil, Emmanouel T. Michailidis, Angelos Michalas, Dimitrios J. Vergados, Nikolaos I. Miridakis, and Dimitrios D. Vergados. "A Network Slicing Framework for UAV-Aided Vehicular Networks." Drones 5, no. 3 (July 30, 2021): 70. http://dx.doi.org/10.3390/drones5030070.
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In a fifth generation (5G) vehicular network architecture, several point of access (PoA) types, including both road side units (RSUs) and aerial relay nodes (ARNs), can be leveraged to undertake the service of an increasing number of vehicular users. In such an architecture, the application of efficient resource allocation schemes is indispensable. In this direction, this paper describes a network slicing scheme for 5G vehicular networks that aims to optimize the performance of modern network services. The proposed architecture consists of ground RSUs and unmanned aerial vehicles (UAVs) acting as ARNs enabling the communication between ground vehicular nodes and providing additional communication resources. Both RSUs and ARNs implement the LTE vehicle-to-everything (LTE-V2X) technology, while the position of each ARN is optimized by applying a fuzzy multi-attribute decision-making (fuzzy MADM) technique. With regard to the proposed network architecture, each RSU maintains a local virtual resource pool (LVRP) which contains local RBs (LRBs) and shared RBs (SRBs), while an SDN controller maintains a virtual resource pool (VRP), where the SRBs of the RSUs are stored. In addition, each ARN maintains its own resource blocks (RBs). For users connected to the RSUs, if the remaining RBs of the current RSU can satisfy the predefined threshold value, the LRBs of the RSU are allocated to user services. On the contrary, if the remaining RBs of the current RSU cannot satisfy the threshold, extra RBs from the VRP are allocated to user services. Similarly, for users connected to ARNs, the satisfaction grade of each user service is monitored considering both the QoS and the signal-to-noise plus interference (SINR) factors. If the satisfaction grade is higher than the predefined threshold value, the service requirements can be satisfied by the remaining RBs of the ARN. On the contrary, if the estimated satisfaction grade is lower than the predefined threshold value, the ARN borrows extra RBs from the LVRP of the corresponding RSU to achieve the required satisfaction grade. Performance evaluation shows that the suggested method optimizes the resource allocation and improves the performance of the offered services in terms of throughput, packet transfer delay, jitter and packet loss ratio, since the use of ARNs that obtain optimal positions improves the channel conditions observed from each vehicular user.
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Abbasi, Aaqif Afzaal, Mohammed A. A. Al-qaness, Mohamed Abd Elaziz, Ammar Hawbani, Ahmed A. Ewees, Sameen Javed, and Sunghwan Kim. "Phantom: Towards Vendor-Agnostic Resource Consolidation in Cloud Environments." Electronics 8, no. 10 (October 18, 2019): 1183. http://dx.doi.org/10.3390/electronics8101183.
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Mobile-oriented internet technologies such as mobile cloud computing are gaining wider popularity in the IT industry. These technologies are aimed at improving the user internet usage experience by employing state-of-the-art technologies or their combination. One of the most important parts of modern mobile-oriented future internet is cloud computing. Modern mobile devices use cloud computing technology to host, share and store data on the network. This helps mobile users to avail different internet services in a simple, cost-effective and easy way. In this paper, we shall discuss the issues in mobile cloud resource management followed by a vendor-agnostic resource consolidation approach named Phantom, to improve the resource allocation challenges in mobile cloud environments. The proposed scheme exploits software-defined networks (SDNs) to introduce vendor-agnostic concept and utilizes a graph-theoretic approach to achieve its objectives. Simulation results demonstrate the efficiency of our proposed approach in improving application service response time.
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Alhashimi, Hayder Faeq, MHD Nour Hindia, Kaharudin Dimyati, Effariza Binti Hanafi, Nurhizam Safie, Faizan Qamar, Khairul Azrin, and Quang Ngoc Nguyen. "A Survey on Resource Management for 6G Heterogeneous Networks: Current Research, Future Trends, and Challenges." Electronics 12, no. 3 (January 28, 2023): 647. http://dx.doi.org/10.3390/electronics12030647.
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The sixth generation (6G) mobile communication system is expected to meet the different service needs of modern communication scenarios. Heterogeneous networks (HetNets) have received a lot of attention in recent years due to their potential as a novel structure for evolutionary networks. When compared to homogeneous networks, HetNets provide more potential for spatial spectrum reuse and higher quality of service (QoS). However, effective resource management (RM) solutions are essential to prevent interference and accomplish spectrum sharing due to mutual interference. This paper presents a comprehensive review of resource management in 6G HetNets. The study aims to give crucial background on HetNets to aid in the creation of more effective methods in this field of study. First, a detailed examination of recent work is presented in resource management aspects such as power allocation, user association, mode selection, and spectrum allocation. Second, we identify the most severe challenges associated with the current resource management methods and propose suitable solutions. Finally, several open issues and emerging areas of research are highlighted.
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Li, Yao Lei, Cong Xian Wang, and Zhen Jia Li. "Optimization Algorithm of Resource Allocation Based on Fuzzy Assessment Method." Applied Mechanics and Materials 556-562 (May 2014): 3896–900. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.3896.
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The technology teaching of university basketball general course is a focus which all sectors of the community should pay more attention. How will the technology teaching of university basketball general course carry out optimization of integration, to play the biggest role, is also the key point of this paper. This paper from the main content of post-modern education and university basketball general course technology teaching, to understand the current situation of university basketball education, and construct basketball general course technology evaluation system. At the same time, using fuzzy evaluation method to do statistical analysis on the situation of basketball general course technology education, and in a targeted manner to set up teaching mode of basketball general course technology under Post-modern educational perspective, use the society, network, universities' and other resources effectively, to sharing the resources, realize technology education and the optimization configuration of resource.
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Mohammed, Munatel, and Abdelkrim Haqiq. "Dynamic resource allocation for service in mobile cloud computing with Markov modulated arrivals." International Journal of Modeling, Simulation, and Scientific Computing 12, no. 05 (June 21, 2021): 2150038. http://dx.doi.org/10.1142/s1793962321500380.
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Mobile Cloud Computing (MCC) is a modern architecture that brings together cloud computing, mobile computing and wireless networks to assist mobile devices in storage, computing and communication. A cloud environment is developed to support a wide range of users that request the cloud resources in a dynamic environment with possible constraints. Burstiness in users service requests causes drastic and unpredictable increases in the resource requests that have a crucial impact on policies of resource allocation. How can the cloud system efficiently handle such burstiness when the cloud resources are limited? This problem becomes a hot issue in the MCC research area. In this paper, we develop a system model for the resource allocation based on the Semi-Markovian Decision Process (SMDP), able of dynamically assigning the mobile service requests to a set of cloud resources, to optimize the usage of cloud resources and maximize the total long-term expected system reward when the arrival process is a finite-state Markov-Modulated Poisson Process (MMPP). Numerical results show that our proposed model performs much better than the Greedy algorithm in terms of achieving higher system rewards and lower service requests blocking probabilities, especially when the burstiness degree is high, and the cloud resources are limited.
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Wang, Zhe, Guangjin Pan, Yanzan Sun, and Shunqing Zhang. "An Interference-Aware Resource-Allocation Scheme for Non-Cooperative Multi-Cell Environment." Electronics 12, no. 4 (February 8, 2023): 868. http://dx.doi.org/10.3390/electronics12040868.
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Inter-cell interference cancellation has been investigated for several decades and has become an elementary technique for modern wireless networks. However, the existing interference cancellation mechanism rarely considers the historical channel variations and interference characteristics. In this paper, we propose an interference-aware prediction-based resource-allocation strategy to deal with multi-cell interference, where the historical noisy channel state and the acknowledgment feedback are fully utilized. Together with the predicted interference patterns, our proposed joint sub-channel allocation and rate selection mechanism can achieve better average throughput performance. Through the numerical as well as the prototyping results, we show that our proposed scheme is able to provide more than 9.7% and 8% average throughput improvement compared with many existing baselines.
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Lyu, Guo-Dong, Chang-Jun Fan, Lian-Fei Yu, Bao-Xin Xiu, and Wei-Ming Zhang. "Predicting missing links via structural similarity." International Journal of Modern Physics B 29, no. 15 (May 25, 2015): 1550095. http://dx.doi.org/10.1142/s0217979215500952.
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Predicting missing links in networks plays a significant role in modern science. On the basis of structural similarity, our paper proposes a new node-similarity-based measure called biased resource allocation (BRA), which is motivated by the resource allocation (RA) measure. Comparisons between BRA and nine well-known node-similarity-based measures on five real networks indicate that BRA performs no worse than RA, which was the best node-similarity-based index in previous researches. Afterwards, based on localPath (LP) and Katz measure, we propose another two improved measures, named Im-LocalPath and Im-Katz respectively. Numerical results show that the prediction accuracy of both Im-LP and Im-Katz measure improve compared with the original LP and Katz measure. Finally, a new path-similarity-based measure and its improved measure, called LYU and Im-LYU measure, are proposed and especially, Im-LYU measure is shown to perform more remarkably than other mentioned measures.
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Ning, Han. "Design of the Physical Education Teaching System by Using Edge Calculation and the Fuzzy Clustering Algorithm." Mobile Information Systems 2022 (September 27, 2022): 1–10. http://dx.doi.org/10.1155/2022/7473614.
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With the increasing number and types of terminal access, real-time processing of increasingly complex Internet of things applications has become increasingly difficult. On the one hand, cloud computing environment in virtual reality, ultrahigh definition live video, intelligent manufacturing, and other application fields put forward complex, diverse, real-time, and other new business requirements. On the other hand, modern IOT terminals have shortcomings such as insufficient computing power and limited battery capacity, which make it difficult to provide real-time processing for Internet applications. The emergence of edge computing services provides effective solutions for these applications, which can improve the local data processing capacity, shorten the data transmission delay, and reduce the hardware cost to a certain extent. Since computing offload, resource allocation, cache content placement, and edge server deployment are the basis of localized data processing and resource allocation, their performance is closely related to the efficiency and accuracy of data processing in the whole system. In the application of the current system, online learning resources and cutting-edge software and hardware teaching environment continue to emerge, shaping a unique smart classroom. The system proposed in this paper not only has the traditional physical education knowledge but also the advanced visualization principle. The combination of them can promote the practice of the new concept of physical education. Through research on edge computing and resource allocation, this paper applies it to the development of cloud computing environment and sports teaching visualization system so that the cloud computing environment and sports teaching visualization system can flourish.
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Xevgenis, Michael, Dimitrios G. Kogias, Ioannis Christidis, Charalampos Patrikakis, and Helen C. Leligou. "Evaluation of a Blockchain-Enabled Resource Management Mechanism for NGNs." International Journal of Network Security & Its Applications 13, no. 5 (September 30, 2021): 1–16. http://dx.doi.org/10.5121/ijnsa.2021.13501.
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A new era in ICT has begun with the evolution of Next Generation Networks (NGNs) and the development of human-centric applications. Ultra-low latency, high throughput, and high availability are a few of the main characteristics of modern networks. Network Providers (NPs) are responsible for the development and maintenance of network infrastructures ready to support the most demanding applications that should be available not only in urban areas but in every corner of the earth. The NP’s must collaborate to offer high- quality services and keep their overall cost low. The collaboration among competitive entities can in principle be regulated by a trusted 3rd party or by a distributed approach/technology which can guarantee integrity, security, and trust. This paper examines the use of blockchain technology for resource management and negotiation among NPs and presents the results of experiments conducted in a dedicated real testbed. The implementation of the resource management mechanism is described in a Smart Contract (SC) and the testbeds use the Raft and the IBFT consensus mechanisms respectively. The goal of this paper is two-fold: to assess its performance in terms of transaction throughput and latency so that we can assess the granularity at which this solution can operate (e.g. support resource re-allocation among NPs on micro-service level or not) and define implementation-specific parameters like the consensus mechanism that is the most suitable for this use case based on performance metrics.
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Obrosova, N., A. Shananin, and A. Spiridonov. "On the comparison of two approaches to intersectoral balance analysis." Journal of Physics: Conference Series 2131, no. 2 (December 1, 2021): 022112. http://dx.doi.org/10.1088/1742-6596/2131/2/022112.
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Abstract The diversification of the inter-industry connections of modern economies seriously hindered the analysis of production networks evolution and input-output balances projection, that traditionally was made by the Leontief Input-Output balance model. That is why the new approaches have begun to develop, that take into account the substitutability of products and services in modern supply networks. In this work we discuss the quality of the new approach to the intersectoral linkages analysis, that is based on the nonlinear model of resource allocation with Cobb-Douglas production technologies. We compare this approach with the traditional Leontief’s scheme of intersectoral connection studying. We make evaluations using the both of methods for large economies, that are on different stages of economic development.
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Lamb, Zachary, and Dharma Agrawal. "Analysis of Mobile Edge Computing for Vehicular Networks." Sensors 19, no. 6 (March 15, 2019): 1303. http://dx.doi.org/10.3390/s19061303.
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Vehicular ad-hoc Networks (VANETs) are an integral part of intelligent transportation systems (ITS) that facilitate communications between vehicles and the internet. More recently, VANET communications research has strayed from the antiquated DSRC standard and favored more modern cellular technologies, such as fifth generation (5G). The ability of cellular networks to serve highly mobile devices combined with the drastically increased capacity of 5G, would enable VANETs to accommodate large numbers of vehicles and support range of applications. The addition of thousands of new connected devices not only stresses the cellular networks, but also the computational and storage requirements supporting the applications and software of these devices. Autonomous vehicles, with numerous on-board sensors, are expected to generate large amounts of data that must be transmitted and processed. Realistically, on-board computing and storage resources of the vehicle cannot be expected to handle all data that will be generated over the vehicles lifetime. Cloud computing will be an essential technology in VANETs and will support the majority of computation and long-term data storage. However, the networking overhead and latency associated with remote cloud resources could prove detrimental to overall network performance. Edge computing seeks to reduce the overhead by placing computational resources nearer to the end users of the network. The geographical diversity and varied hardware configurations of resource in a edge-enabled network would require careful management to ensure efficient resource utilization. In this paper, we introduce an architecture which evaluates available resources in real-time and makes allocations to the most logical and feasible resource. We evaluate our approach mathematically with the use of a multi-criteria decision analysis algorithm and validate our results with experiments using a test-bed of cloud resources. Results demonstrate that an algorithmic ranking of physical resources matches very closely with experimental results and provides a means of delegating tasks to the best available resource.
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Haider Ali, Ayesha, and Muhammad Mohsin Nazir. "QoS Oriented Multiobjective Optimizer for Radio Resource Management of LTE-A Femtocells." Mobile Information Systems 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/7964359.
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The future wireless networks support multimedia applications and require ensuring quality of the services they provide. With increasing number of users, the radio resource is becoming scarce. Therefore, how should the demands for higher data rates with limited resources be met for Long Term Evolution-Advanced (LTE-A) is turning out to be a vital issue. In this research paper we have proposed an innovative approach for Radio Resource Management (RRM) that makes use of the evolutionary multiobjective optimization (MOO) technique for Quality of Service (QoS) facilitation and embeds it with the modern techniques for RRM. We have proposed a novel Multiobjective Optimizer (MOZ) that selects an optimal solution out of a Pareto optimal (PO) set in accordance with the users QoS requirements. We then elaborate the scheduling process and prove through performance evaluation that use of MOO can provide potential solutions for solving the problems for resource allocation in the advancement of LTE-A networks. Simulations are carried out using LTE-Sim simulator, and the results reveal that MOZ outperforms the reference algorithm in terms of throughput guarantees, delay bounds, and reduced packet loss. Additionally, it is capable of achieving higher throughput and lower delay by giving equal transmission opportunity to all users and achieves 100% accuracy in terms of selecting optimal solution.
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Kumari, Neha, and Dr Uday Narayan Singh. "A Study of Virtualization Techniques Applied in Cloud Computing Environment." International Journal for Research in Applied Science and Engineering Technology 11, no. 2 (February 28, 2023): 1459–64. http://dx.doi.org/10.22214/ijraset.2023.48994.
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Abstract: The fastest-growing internet technology today is cloud computing. On-demand network access to a shared pool of reconfigurable resources is possible. A fundamental component of cloud computing is virtualization, which enables real resources to be divided into virtual resources so they can be shared among other virtual machines. Utilizing this virtualized resource can help you use less real equipment, servers, and storage space. Modern technologies like cloud computing expand the functional possibilities, elastic resource management, and collaborative execution style of applications. Virtualization, which enables business or academic IT resources through ondemand allocation dynamically, is the core component of cloud computing. The resources come in a variety of shapes, including client, server, storage, network, and application. This essay focuses on how virtualization increases the resources' elasticity in a cloud computing context. This study also provides a thorough analysis of open source virtualization approaches, problems, and future research directions.
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She, Yuanjun, and Zhi Li. "Radio Resource Allocation Algorithm of the M2M Communication System in 5G Era." Wireless Communications and Mobile Computing 2022 (May 24, 2022): 1–12. http://dx.doi.org/10.1155/2022/3665513.
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M2M is a concept and a general term for all technologies that enhance the communication and network capabilities of machines and equipment. It is a combination of different types of communication technologies. M2M enables all devices and users to share information, saving operation time and improving work efficiency. M2M is not a simple data transmission, but it is an intelligent and interactive communication between machines. Even if no real-time signal is sent, the machine will actively communicate according to the established program and select intelligently according to the obtained data. The communication system refers to the general term of the technology that completes the information transmission function. The modern communication system is mainly realized by the propagation of electromagnetic waves in free space or the transmission mechanism in the guiding medium. When the wavelength of the electromagnetic wave reaches the light wave range, such a telecommunication system is called an optical communication system, and the communication system in the other electromagnetic wave range is called an electromagnetic communication system, abbreviated as a telecommunication system. The purpose of this paper is to explore the study of wireless data sharing method for M2M mobile telecommunication systems in the 5G era. It is expected that the new algorithm will make the wireless resource allocation more reasonable and improve the resource utilization rate. The performance of the deterministic measurement matrix proposed in this paper is close to or even better than that of the random measurement matrix. The M-SP algorithm greatly improves the performance of the SP algorithm. The experimental results of this paper show that when the number of microbase stations is 10, the energy consumption of the direct algorithm is 175000 W, the energy consumption of the indirect algorithm is 350000 W, and the energy consumption of the direct algorithm is much smaller than that of the indirect algorithm.
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Qasim, N. H., Y. I. Khlaponin, and M. M. Vlasenko. "FORMALIZATION OF THE PROCESS OF MANAGING THE TRANSMISSION OF TRAFFIC FLOWS ON A FRAGMENT OF THE LTE NETWORK." Collection of scientific works of the Military Institute of Kyiv National Taras Shevchenko University, no. 75 (2022): 88–93. http://dx.doi.org/10.17721/2519-481x/2022/75-09.
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With the rapid growth of mobile data traffic, the popularity of the Internet of Things (IoT) and machine-to-machine (M2M), mobile operators are constantly working to improve the quality of service, developing 4G networks in the direction of future software-configured heterogeneous 5G networks. The fourth generation of communication began to be developed in 2000. At this time, the 3G standard has already appeared. Research in the field of communications has shown that of all the variety of 4G technologies and standards, only two can be acceptable for deployment: LTE and the mobile version of WiMAX, LTE was originally developed as an adjunct to 3G cellular networks. Today, there is a rapid increase in traffic in 4th generation mobile networks, and to ensure the necessary speed for all their subscribers, operators have to look for different methods to increase data rates or to increase the efficiency of frequency resource use. Unlike 4G, the latest 5G networks have wider applications. Therefore, the main task of modern wireless networks is to optimize the distribution of a limited amount of frequency and time resources between users and devices of the Internet of Things on the basis of quality of service. The purpose of creating a conceptual model of the next generation of 5G can be called increasing the capabilities of high-speed mobile communication systems, reducing the cost of data transmission, expanding the range of services provided. The planning of the 5G network can be influenced by a number of factors due to the fundamental feature of this technology. In addition to bandwidth, an important characteristic of the system is the probability of bit error, which affects the modulation and coding algorithms used. Therefore, it is necessary to constantly maintain a balance between these two important characteristics for the user. This can be achieved by improving resource allocation methods and models, as well as effective network planning.
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Vijayalakshmi, R., V. Vasudevan, Seifedine Kadry, and R. Lakshmana Kumar. "Optimization of makespan and resource utilization in the fog computing environment through task scheduling algorithm." International Journal of Wavelets, Multiresolution and Information Processing 18, no. 01 (January 2020): 1941025. http://dx.doi.org/10.1142/s021969131941025x.
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The Fog computing is rising as a dominant and modern computing model to deliver Internet of Things (IoT) computations, which is an addition to the cloud computing standard to get it probable to perform the IoT requests in the network of edge. In those above independent and dispersed environment, resource allocation is vital. Therefore, scheduling will be a test to enhance potency and allot resources properly to the tasks. This paper offers a distinct task scheduling algorithm in the fog computing environment that tries to depreciate the makespan and maximize resource utilization. This algorithm catalogues the task based on the mean Suffrage value. The suggested algorithm gives much resource utilization and diminishes makespan. Our offered algorithm is compared with different alive scheduling for performance investigation, and test results confirm that our algorithm has a more significant resource utilization rate and low makespan than other familiar algorithms.
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Ali, Azhar, Amna Baig, Ghulam Mujtaba Awan, Wali Ullah Khan, Zain Ali, and Guftaar Ahmad Sardar Sidhu. "Efficient Resource Management for Sum Capacity Maximization in 5G NOMA Systems." Applied System Innovation 2, no. 3 (August 7, 2019): 27. http://dx.doi.org/10.3390/asi2030027.
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The modern cellular technologies are expected to provide high data rates and massive connectivity in fifth generation (5G) systems; however, this may be impossible through traditional radio access techniques. Recently, non-orthogonal multiple access (NOMA) has emerged as one of the promising cellular techniques for modern cellular communications with its ability to provide access for multiple users to the network over the same system resources. This paper studies resource management problem for downlink transmission of multiuser NOMA system. Our objective is to optimize both frequency and power resources for sum capacity maximization while taking into account each user minimum capacity requirement. Firstly, the problem of resource management decouples into two subproblems, that is, efficient sub-channel assignment and optimal power allocation, respectively. Secondly, for given power at base station, we design two sub-optimal algorithms for sub-channel assignment based on user channel condition and user minimum capacity requirement, respectively. Lastly, for any given sub-channel assignment, the problem first transforms into standard convex optimization problem and then we employ duality theory. To evaluate our proposed NOMA scheme, the enhanced version of existing NOMA optimization scheme is also presented as a benchmark. Results demonstrate that the proposed NOMA resource management scheme outperforms the benchmark NOMA optimization scheme in terms of sum capacity.
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Ogunrinola, Olawale Oluwasegun, Isaiah Opeyemi Olaniyi, Segun A. Afolabi, Gbemiga Abraham Olaniyi, and Olushola Emmanuel Ajeigbe. "Modelling and Development of a Radio Resource Control and Scheduling Algorithm for Long-Term Evolution (LTE) Uplink." Review of Computer Engineering Studies 8, no. 2 (June 30, 2021): 23–34. http://dx.doi.org/10.18280/rces.080201.
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Modern radio communication services transmit signals from an earth station to a high-altitude station, space station or a space radio system via a feeder link while in Global Systems for Mobile Communication (GSM) and computer networks, the radio uplink transmit from cell phones to base station linking the network core to the communication interphase via an upstream facility. Hitherto, the Single-Carrier Frequency Division Multiple Access (SC-FDMA) has been adopted for uplink access in the Long-Term Evolution (LTE) scheme by the 3GPP. In this journal, the LTE uplink radio resource allocation is addressed as an optimization problem, where the desired solution is the mapping of the schedulable UE to schedulable Resource Blocks (RBs) that maximizes the proportional fairness metric. The particle swarm optimization (PSO) has been employed for this research. PSO is an algorithm that is very easy to implement to solve real time optimization problems and has fewer parameters to adjust when compared to other evolutionary algorithms. The proposed scheme was found to outperform the First Maximum Expansion (FME) and Recursive Maximum Expansion (RME) in terms of simulation time and fairness while maintaining the throughput.
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Rao T, Srinivasa, Harsha G, Kiran V, and Hemanth Kumar K. "Dos flooding attack control in information-centric networks." International Journal of Engineering & Technology 7, no. 1.1 (December 21, 2017): 303. http://dx.doi.org/10.14419/ijet.v7i1.1.9708.
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ICN (Information-centric networking) is a modern networking standard that mainly works only on the content extraction from a network without taking into case about the storage location or how the content is represented. In ICN providing security for the content is more important. Here we don’t concentrate on protecting path. In order to fulfil the security goals in the new standard, it is very decisive to have a clear complete comprehension about ICN attacks and their brief allocation and the solutions. In this paper we in brief explain the attacks which effect the ICN network and other related attacks which have an impact on ICN. Attacks in ICN are divided to four categories, routing attacks, Naming attacks, Caching attacks, and other various related attacks. There are lot of solutions which are accessible. The main moto in ICN is to protect data which is very hard to achieve. So we develop a dynamic host based IP address scheme including certain snort rules which detect attacker and distinguish them in the clients and secure server from resource exhaustion. Our main center we deal with is on availability, and privacy.
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Skondras, Emmanouil, Angelos Michalas, Dimitrios J. Vergados, Emmanouel T. Michailidis, Nikolaos I. Miridakis, and Dimitrios D. Vergados. "Network Slicing on 5G Vehicular Cloud Computing Systems." Electronics 10, no. 12 (June 19, 2021): 1474. http://dx.doi.org/10.3390/electronics10121474.
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Fifth generation Vehicular Cloud Computing (5G-VCC) systems support various services with strict Quality of Service (QoS) constraints. Network access technologies such as Long-Term Evolution Advanced Pro with Full Dimensional Multiple-Input Multiple-Output (LTE-A Pro FD-MIMO) and LTE Vehicle to Everything (LTE-V2X) undertake the service of an increasing number of vehicular users, since each vehicle could serve multiple passenger with multiple services. Therefore, the design of efficient resource allocation schemes for 5G-VCC infrastructures is needed. This paper describes a network slicing scheme for 5G-VCC systems that aims to improve the performance of modern vehicular services. The QoS that each user perceives for his services as well as the energy consumption that each access network causes to user equipment are considered. Subsequently, the satisfactory grade of the user services is estimated by taking into consideration both the perceived QoS and the energy consumption. If the estimated satisfactory grade is above a predefined service threshold, then the necessary Resource Blocks (RBs) from the current Point of Access (PoA) are allocated to support the user’s services. On the contrary, if the estimated satisfactory grade is lower than the aforementioned threshold, additional RBs from a Virtual Resource Pool (VRP) located at the Software Defined Network (SDN) controller are committed by the PoA in order to satisfy the required services. The proposed scheme uses a Management and Orchestration (MANO) entity implemented by a SDN controller, orchestrating the entire procedure avoiding situations of interference from RBs of neighboring PoAs. Performance evaluation shows that the suggested method improves the resource allocation and enhances the performance of the offered services in terms of packet transfer delay, jitter, throughput and packet loss ratio.
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Gorbachuk, Vasyl, Gennadii Golotsukov, Maksym Dunaievskyi, Andrii Syrku, and Seit-Bekir Suleimanov. "GAME THEORY AND OPTIMIZATION MODELS AND METHODS TO INCREASE SECURITY OF CYBERINFRASTRUCTURES." International Scientific Technical Journal "Problems of Control and Informatics" 2, no. 6 (March 1, 2022): 92–105. http://dx.doi.org/10.34229/2786-6505-2022-2-6.
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Critical infrastructure of interdependent modern sectors is increasingly relying on cyber systems and cyber infrastructures, which are characterized by growing risks of their cyber components, including cyberphysical subsystems. Therefore, cybersecurity is important for the protection of critical infrastructure. The search for cost-effective ways to increase or improve the security of cyber infrastructure is based on optimization models and methods of cyber infrastructure stability, safety, and reliability. These models and methods have different fields of application and different directions, not necessarily focused on the cyber infrastructure resilience. The growing role of information and communication technologies has influenced the concept of security and the nature of war. Many critical infrastructures (airports, hospitals, oil pipelines) have become potentially vulnerable to organized cyber attacks. Today, the implementation of the major state function of defense and security largely depends on the successful use of information and communication technologies as modern competitive (final and intermediate) dual-use products used by different people for different purposes. Game theory is increasingly used to assess strategic interactions between attackers and defenders in cyberspace. Game research and modeling combinations are combined to study the security of cyberspace. In cyberspace, the arsenal of weapons is built by finding more vulnerabilities in the defense of the target. Vulnerability is a weakness in the security procedures of the system, the design of the system or its implementation, as well as in the organization of internal control, which may be used by the source of the threat. The dynamic nature of vulnerabilities means that they are constantly changing over time. Detecting a vulnerability by a defender reduces the effectiveness of the attacker’s cyber weapon, which exploits the vulnerability, and increases the target protection. Game theory has been applied to many issues, including resource allocation, network security, and human cooperation. In cyberspace, there is often a placement game where the attacker and the defender decide where to allocate their respective resources. Defender’s resources can be security infrastructure (firewalls), finance, training. For example, a network administrator might look for a resource allocation that minimizes the risk of (cyber) attacks and at the same time protects against cyberattacks. The attacker has limited resources and is at risk of being tracked down and punished. The problem of resource allocation in cyberspace can be formulated as a game-theoretic problem, taking into account the concept of common knowledge and the problem of uncertain observability.
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Schumacher, H. J. (Jerry), Tony Lee, and Sumit Ghosh. "A Novel, User-Level, Security-On-Demand Paradigm for ATM Networks: Modeling, Simulation, and Performance Analysis." Journal of Interconnection Networks 04, no. 04 (December 2003): 429–61. http://dx.doi.org/10.1142/s0219265903000969.
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With networks increasingly moving into virtually every aspect of our daily life, security is gaining importance, not only from the traditional perspective of communication but the network's growing role in modern automation and control. The traditional, certification based approach attempts to guarantee the security of a network through certification. Certified networks are generally confined to a limited domain and, as a result, they are isolated, costly, and under-utilized. In contrast, this paper presents a new principle – user-level, security-on-demand system, wherein the network allocates, where possible, the security resources commensurate with the user's request for transporting message(s) through the network securely. This principle is successfully demonstrated for the current Asynchronous Transfer Mode (ATM) networks, and is the result of an integration of the fundamental framework for network security, recently proposed by the authors in the literature, with the unique characteristics of ATM networks. The framework encapsulates the fundamental knowledge and set of relationships in network security and permits scientific and systematic reasoning about network security. It also enables all user groups – military, government, industry, and academia, to define their security requirements in a uniform manner. The security-on-demand approach promises the development of a "mixed use" class of networks in the future that may be simultaneously shared by different groups of users, with the system sustaining the diverse security requirements of each user. A unique characteristic in ATM network design is the dynamic call setup process. Under it, a network first establishes a virtual path or route for a user's call, guided by the user's requirements, and then transports the messages when a route has been successfully determined. This unique ATM characteristic is integrated with the framework to yield a successful demonstration of the proposed, user-level, security-on-demand approach. Utilizing the security framework as the foundation, every element of the network – node and link, is characterized by a security matrix that reflects its security resources. Every user is permitted to specify the security requirement for the call through a matrix, which expresses the limits of the security resources that the traffic cells must encounter during their transport through the network. Thus, during the dynamic establishment of the virtual path, every node and link is examined to ensure that the user-specified security is met, in addition to bandwidth and other Quality of Service (QoS) requirements. Traffic is launched when the call setup succeeds, otherwise, the call fails. Like all networks, the ATM network inherently consists of geographically dispersed entities and, as a result, the resource allocation strategy is necessarily distributed. Furthermore, as the network operation progresses, the resource availability scene changes dynamically. This paper proposes a unique function that reduces the key network resource parameters at a node to a single value, termed Node Status Indicator (NSI). The NSI value is computed dynamically at every node and disseminated across the network to be utilized by a node to refine its determination of a virtual path for a user call. The aim of the NSI is to improve the resource utilization in the network. The proposed approach is modeled for a large-scale, representative, 40-node ATM network. Utilizing stochastic input traffic that is synthesized to reflect realistic operating conditions, the model is simulated extensively on a testbed of 35+ Pentium workstations, under Linux, configured as a loosely-coupled parallel processor, utilizing an accurate, asynchronous, distributed simulator. The simulator implements the key characteristics of the ATM Forum proposed P-NNI 1.0 and UNI 3.0 standards. While the simulation results reflect a successful realization of the proposed approach, analysis reveals minimal impact of incorporating security on ATM network performance, as measured through call success rates and call setup times. In contrast, the tradition has been to incorporate security into large-scale systems and networks as an afterthought, i.e. adding hardware and software devices after the design has been completed, resulting in performance degradation. Also, while the use of NSI is observed to yield slightly lower average call setup rates and slightly higher average call setup times, a careful analysis of the trace of the calls as they progress through the system, reveals that, in general, calls are dispersed throughout the network, seeking to utilize all available resources of the network more evenly.
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Grabowska, Sandra. "Changes in the social architecture of business model in the perspective of the Industry 4.0 concept." Management 24, no. 1 (June 1, 2020): 130–42. http://dx.doi.org/10.2478/manment-2019-0039.
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SummaryAfter three industrial revolutions, the fourth comes, which transfers production to sophisticated networks of companies equipped with intelligent devices, machines, means of transport, communicating with each other using modern technologies. It creates new challenges for industrial enterprises, it requires redefining existing business models. The development of the concept of Industry 4.0 forces modern enterprises to quickly and flexibly adapt to the changing conditions of the technological environment. This is reflected in the changes taking place in the area of social and technical architecture of business models.Industry 4.0 contributes to creating a new kind of interaction between people and machines. These interactions significantly affect the way work is done and the resource allocation in the social and technical architecture of business models.The aim of the article is to identyfy the changes taking place in the area of social architecture of the business model in the era of Industry 4.0.
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BOSSARD, ANTOINE. "ON THE DECYCLING PROBLEM IN HIERARCHICAL HYPERCUBES." Journal of Interconnection Networks 14, no. 02 (June 2013): 1350006. http://dx.doi.org/10.1142/s0219265913500060.
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Due to the huge number of CPU nodes involved in modern supercomputers, efficient CPU connection is challenging, and legacy simple network topologies such as hypercubes are no more suitable for physical reasons. The hierarchical hypercube (HHC) has been designed as a topology for interconnection network of massively parallel systems. An HHC is effectively able to link many nodes while retaining a low degree and a small diameter compared to a hypercube of the same size. In this paper, we address a fundamental problem inside an HHC, the decycling problem, which consists of finding a set of nodes as small as possible such that excluding these nodes from the network ensures a cycle-free topology. This problem has many important applications such as lock-free resource allocation and concurrent access. So, we propose in this paper an efficient algorithm finding in an HHC a decycling set of competitively small size.
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Zheng, Zhichao, Shengming Jiang, Ruoyu Feng, Lige Ge, and Chongchong Gu. "Survey of Reinforcement-Learning-Based MAC Protocols for Wireless Ad Hoc Networks with a MAC Reference Model." Entropy 25, no. 1 (January 3, 2023): 101. http://dx.doi.org/10.3390/e25010101.
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In this paper, we conduct a survey of the literature about reinforcement learning (RL)-based medium access control (MAC) protocols. As the scale of the wireless ad hoc network (WANET) increases, traditional MAC solutions are becoming obsolete. Dynamic topology, resource allocation, interference management, limited bandwidth and energy constraint are crucial problems needing resolution for designing modern WANET architectures. In order for future MAC protocols to overcome the current limitations in frequently changing WANETs, more intelligence need to be deployed to maintain efficient communications. After introducing some classic RL schemes, we investigate the existing state-of-the-art MAC protocols and related solutions for WANETs according to the MAC reference model and discuss how each proposed protocol works and the challenging issues on the related MAC model components. Finally, this paper discusses future research directions on how RL can be used to enable MAC protocols for high performance.
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Li, Yiren, Tieke Li, Pei Shen, Liang Hao, Jin Yang, Zhengtong Zhang, Junhao Chen, and Liang Bao. "PAS: Performance-Aware Job Scheduling for Big Data Processing Systems." Security and Communication Networks 2022 (April 12, 2022): 1–14. http://dx.doi.org/10.1155/2022/8598305.
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Big data analytics has become increasingly vital in many modern enterprise applications such as user profiling and business process optimization. Today’s big data processing systems, such as Hadoop MapReduce, Spark, and Hive, treat big data applications as a batch of jobs for scheduling. Existing schedulers in production systems often maintain fair allocation without considering application performance and resource utilization simultaneously. It is challenging to perform job scheduling in big data systems to achieve both low turnaround time and high resource utilization due to the high complexity in data processing logics and the dynamic variation in workloads. In this article, we propose a performance-aware scheduler, referred to as PAS, which dynamically schedules big data jobs in Hadoop YARN and Spark and autonomously adjusts scheduling policies to improve application performance and resource utilization. Specifically, PAS schedules multiple concurrent jobs using different policies based on the predicted job completion time and employs a greedy approach and a one-step lookahead strategy to opportunistically maximize the average job performance while still maintaining a satisfactory level of resource utilization. We implement PAS in Hadoop YARN and evaluate its performance with HiBench, a well-known big data processing benchmark. Experimental results show that PAS reduces the average turnaround time by 25% and the makespan by 15% in comparison with four state-of-the-art schedulers.
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Chen, Rui. "The Design and Application of College English-Aided Teaching System Based on Web." Mobile Information Systems 2022 (February 25, 2022): 1–10. http://dx.doi.org/10.1155/2022/3200695.
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With the rapid advancement of information technology, the Internet and the web have become the central technology tools for information sharing in education and teaching. Modern education combines teaching with information technology and gives full play to the role of information technology in education and teaching. To improve the resource sharing and scheduling level a web-based college English-assisted teaching system is presented in this study. Using the JavaScript object notation syntax (JSON) as the data communication format between the intelligent terminal and the server, the system is implemented using a web server and mobile Android terminal, and a web-based data integration module is designed. Statistical data mining and fuzzy feature detection are employed to implement the decision-making scheduling and self-adaptive optimization of English teaching resources in a web aided English teaching system. The fusion particle swarm optimization algorithm is used to integrate English teaching resources and implement adaptive scheduling. To verify the application performance of the designed system, a simulation experiment is designed. The experimental results show that the proposed English-assisted instruction system has good convergence and high accuracy of learning information, optimal allocation, and scheduling.
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Chu, Xin, Fei Cao, Long Jiao, Jinxue Wang, and Yumei Jiao. "Optimal Allocation of Higher Education Resources Based on Data Mining and Cloud Computing." Wireless Communications and Mobile Computing 2022 (March 9, 2022): 1–9. http://dx.doi.org/10.1155/2022/7067676.
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With the explosion of information and ever-increasing information resources, humanity has entered a brand-new cloud computing era. We are confronted with a brand-new problem: how to quickly and accurately extract the required information from vast information resources. It is even possible to argue that university educational administration is inextricably linked to university teaching accomplishments. The teaching data mining (DM) technology was created in order to extract the required information from vast information resources. People’s ability to find data using cloud computing technology (IT) has improved. This paper analyzes the division and optimal allocation of talent types in universities, in combination with the development strategy and HR characteristics of universities, and provides strategies for the rational allocation of talents in universities, as well as support for the information relationship of HR in universities, using DM technology research. The emergence of DM technology alleviates the problem of data accumulation-induced information explosion. In today’s universities, there are an increasing number of talents. In terms of talent allocation, the information-based talent allocation scheme offers new approaches to talent acquisition and university education development in the modern era.
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Pedarsani, Ramtin, Jean Walrand, and Yuan Zhong. "Robust scheduling for flexible processing networks." Advances in Applied Probability 49, no. 2 (June 2017): 603–28. http://dx.doi.org/10.1017/apr.2017.14.
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Abstract Modern processing networks often consist of heterogeneous servers with widely varying capabilities, and process job flows with complex structure and requirements. A major challenge in designing efficient scheduling policies in these networks is the lack of reliable estimates of system parameters, and an attractive approach for addressing this challenge is to design robust policies, i.e. policies that do not use system parameters such as arrival and/or service rates for making scheduling decisions. In this paper we propose a general framework for the design of robust policies. The main technical novelty is the use of a stochastic gradient projection method that reacts to queue-length changes in order to find a balanced allocation of service resources to incoming tasks. We illustrate our approach on two broad classes of processing systems, namely the flexible fork-join networks and the flexible queueing networks, and prove the rate stability of our proposed policies for these networks under nonrestrictive assumptions.
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Yuan, Xinlei. "Network Education Resource Information Sharing System Based on Data Mining." Mathematical Problems in Engineering 2022 (April 7, 2022): 1–8. http://dx.doi.org/10.1155/2022/4080049.
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To enter a new stage of development of education informatization, network education has become a global trend of education training, the development of lifelong education, and resource sharing platform for higher vocational colleges to some extent, with network technology and multimedia technology as the core of the rapid development of modern information technology. The sharing of network education resource sharing system and the application in the whole advancement provide the conditions, it promotes the construction and development of higher vocational education resource system. This study examines the problems that exist in the construction of higher vocational college education resources, such as unreasonable management of education resources, unclear goals of higher vocational colleges, and unclear school-enterprise cooperation, based on the research status and achievements of higher vocational college education resources at home and abroad. On the basis of combing and analyzing the related concepts, theoretical basis, and construction principles of higher vocational education resources, the paper designs the network sharing system of higher vocational education resources in detail from its design objectives, design ideas, user needs, overall framework system, hierarchical structure, and functional modules. The core part is the realization of system function modules, including the resource management function module, system management function module, and user management function module. At present, domestic scholars have carried out a lot of research on the construction of basic education network resources. Although the research focuses on resource allocation, coconstruction and sharing mechanisms, and the current state of building and development methods, it also serves as a guide for the development of basic education network resources. However, most of these research results analyze problems from the qualitative perspective, and most of the research results are speculative research at the macro level, lacking practicality. With the rapid development of network education, the construction of network resource libraries is developing in the direction of intelligence and individuation to meet the different learning needs of learners. Based on the analysis of the problems encountered by learners in using the resource library for learning, this paper puts forward the application of data mining technology (DM) to guide the construction of the resource library and discusses how to improve the organizational structure of the resource library, improve the utilization rate of the resource library, and adapt to personalized learning. At present, the system is still in the system testing and experience stage, through the continuous testing of relevant functional modules, further improves the function of the sharing system, and constantly increases the scalability of the system function, in order to establish a perfect, comprehensive, and nationwide higher vocational education resource network sharing system.
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Zhou, Lan, and Yang Lu. "Evaluation Model for Spatial Allocation Efficiency of Modern Educational Campus Building Using Big Data." Mobile Information Systems 2022 (May 31, 2022): 1–10. http://dx.doi.org/10.1155/2022/9705618.
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With the continuous development and improvement of university education, providing students with refined and comprehensive learning environment has come to be a problem of great importance and significance to the people. The state carries out quality-oriented education through a series of measures of education reform. These measures and standards not only help to improve the overall quality of students, but also put forward higher requirements for planning and architectural design of university campuses. In fact, the development of university campuses has been severely restricted by serious contradictions between the shortage of urban construction land and the expansion of middle school campuses. Therefore, in the case of limited construction land resources, how to integrate and optimize the building space and function of campus, improve the utilization rate of building space, make full use of the limited construction land, and create a rich and diverse space environment are difficult problems that are faced in the design of today’s universities. In this paper, we discuss the integration strategy of main entrance space of university campus city through empirical research and put forward 4 value evaluation dimensions and 24 value evaluation factors. Moreover, we construct a numerical and geometric evaluation model, i.e., “CPCC,” to complete the evaluation and optimization of the integration strategy. The purpose is to provide reference for the research object and same type of space on the interface of university campus city. We observed that the proposed CPCC model can effectively promote the historical process of the integration and symbiosis between the university campus and city.
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El-Zahab, Samer, Abobakr Al-Sakkaf, Eslam Mohammed Abdelkader, and Tarek Zayed. "A Novel Lazy Serpent Algorithm for the Prioritization of Leak Repairs in Water Networks." Water 12, no. 8 (August 8, 2020): 2235. http://dx.doi.org/10.3390/w12082235.
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Maximizing benefit from budget allocation is a major challenge for municipalities in the modern era. This is especially significant when it comes to infrastructure network management such as water distribution networks. The main challenges of water distribution networks are leakage and leak repairs. Municipalities commonly use first-in-first-out approaches to determine which leaks to allocate budget for first. Yet, the deterioration of leaks is not linear through time and requires a more in-depth assessment of the condition of the leak. Therefore, this article presents two prioritization approaches for the scheduling of leaks while incorporating deterioration over time. This paper proposes and compares two optimization techniques: (1) a well-known genetic algorithm and (2) a novel approach named the Lazy Serpent Algorithm. The Lazy Serpent Algorithm has proved capable of surpassing the genetic algorithm in determining a more optimal order by using much less computation time. The Lazy Serpent Algorithm helps municipalities better distribute their resources to maximize their desired benefits.
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Rao, Juan, and Xiaofen Cao. "Construction of Resource Ecological Compensation Mechanism Model under Rural Leisure Sports Environment." Journal of Environmental and Public Health 2022 (September 29, 2022): 1–13. http://dx.doi.org/10.1155/2022/2987270.
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In order to solve the problem of resource ecological compensation, this paper proposed a model of resource ecological compensation mechanism based on a rural leisure sports environment. The model is carried out in many places in China. The survey data involves 31 provinces, 10 years, and 43 indicators, with a total of 43 × 10 × 31 = 13,330 data. The preliminary basis of mechanism construction is summarized from four aspects. Finally, make full use of modern information technology to improve the network platform of the compensation mechanism, promote the efficient allocation and comprehensive utilization of ecotourism resources, and lay a solid foundation for establishing a reasonable and perfect resource ecological compensation mechanism and ensuring the long-term and stable operation of the mechanism. Through the experiment, it is found that the timely and effective publication of information can eliminate the inner estrangement between the two sides, so as to make the behavior of both sides more rational. A special information feedback department is established to deal with the opinions put forward by all compensation parties in tourism development, extract effective information, summarize and publish reasonable guidance information, and guide the compensation of both sides to an ideal balance through the feedback of this information. The effectiveness of the experiment is verified.
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El-Ela, Adel A. Abou, Ragab A. El-Sehiemy, Abdullah M. Shaheen, and Aya R. Ellien. "Review on Active Distribution Networks with Fault Current Limiters and Renewable Energy Resources." Energies 15, no. 20 (October 17, 2022): 7648. http://dx.doi.org/10.3390/en15207648.
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To cope with the increasing energy demand, power systems, especially distribution networks, face many challenges. Recently, these networks have become complex and large, and their stability and reliability are not easy to be handled. The integration of renewable energy resources and at the same time limiting their accompanied high fault currents is one of the approvable suggestions. Many solutions have appeared to restrict the fault currents, but fault current limiters (FCLs) arise as an efficient and promising solution to whether to interrupt or limit the fault currents to allowable limits. This paper presents a literature review of the integration of renewable energy resources as distributed generation units (DGs) and FCLs in distribution networks. The DGs can be categorized based on their size and ability to deliver active or reactive power in addition to their fuel. All of solar, wind, water, biomass, geothermal, and fuel cell are utilized as the main engine for these units. Additionally, a survey about FCLs is provided, including their diverse types and applications in either medium- or low-voltage networks. FCLs are divided into reactor, pyrotechnic, non-superconducting (solid state), and the last-developed ones, superconducting FCLs. In addition, the implemented optimization techniques are summarized to correctly employ both FCLs and DGs. These techniques vary between classical and modern, whereas more methods are developed to suit the renewable energy intermittence and uncertainty and the power system operators’ aspirations. Moreover, in this paper, the optimal allocation of diverse types of DGs correlated with FCLs is presented and applied to the real Egyptian distribution network of the East Delta Network (EDN). The results show the avails obtained where the power losses are significantly reduced, with respect to the total load, from 3.59% in the initial case to 0.296%. In addition, the fault current returns to its initial value, removing the percentage of increase of 20.93%.
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Sridharan, R., and S. Domnic. "Placement Strategy for Intercommunicating Tasks of an Elastic Request in Fog-Cloud Environment." Scalable Computing: Practice and Experience 20, no. 2 (May 2, 2019): 335–48. http://dx.doi.org/10.12694/scpe.v20i2.1526.
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Cloud computing hosts large number of modern day applications using the virtualization concept. However, end-to-end network latencies are detrimental to the performance of IoT (Internet of Things) applications like video surveillance and health monitoring. Although edge/fog computing alleviates the latency concerns to some extent, it is still not suitable for applications having intercommunicating tasks. Further, these applications can be elastic in nature and demand more tasks during their life-time. To address this gap, in this paper a network aware co-allocation strategy for the tasks of an individual applications is proposed. After modelling the problem using bin packing approach with additional constraints, the authors propose a novel heuristic IcAPER,(Inter-communication Aware Placement for Elastic Requests) algorithm. The proposed algorithm uses the network neighborhood machine for placement, once current resource is fully utilized by the application. Using CloudsimPlus simulator the performance IcAPER algorithm is compared with First Come First Serve (FCFS), Random and First Fit Decreasing (FFD) algorithms for the parameters (a) resource utilization (b) resource fragmentation and (c) Number of requests having intercommunicating tasks placed on to same PM. Extensive simulation results shows IcAPER maps 34% more tasks on to the same PM and also increase the resource utilization by 13% while decreasing the resource fragmentation by 37.8% when compared to other algorithms in our consideration.
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Chai, Duo, Dong Zhang, Yonghao Sun, and Shan Yang. "Research on the City Network Structure in the Yellow River Basin in China Based on Two-Way Time Distance Gravity Model and Social Network Analysis Method." Complexity 2020 (December 22, 2020): 1–19. http://dx.doi.org/10.1155/2020/6680954.
Full textAbstract:
Modern cities form city networks through complex social ties. City network research is widely applied to guide regional planning, infrastructure construction, and resource allocation. China put forward the Yellow River Basin Development Strategy in 2019, but no research has been conducted on regional social connections among cities. Based on the gravity model modified by two-way “time distance” between cities, this is the first study to empirically examine the intensity and structure of the entire city network in the Yellow River basin using the social network analysis method and ArcGIS software. The connection rules of the cross-city transfer of city officials in the basin are also investigated to illustrate the official ties between cities. The results suggest that the intensity of two-way connections between cities is generally low in the Yellow River basin and there is a positive correlation between city network development level and regional economic development level. The development gap between cities on the north and south banks is larger than that between the east and west regions, and some cities in the middle and upper reaches of the river are marginalized in the network. The status of the central cities in the Yellow River basin is distinct, but their connecting and leading abilities are not strong, showing an inverted T-shaped spatial distribution. The subgroups of city networks have strong internal connections, while the connection among subgroups is weak and the development shows a partitioned and fragmented pattern, making it difficult to form linkages among the upper, middle, and lower reaches. The “beaded chain” spatial development strategy can be adopted in the river basin planning, giving priority to strengthening the links within subgroups of cities and among adjacent subgroups, building central city chains, and reinforcing the overall basin management.
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Koboević, Žarko, Zvonimir Šoša, and Nikša Koboević. "Belt and Road Initiative with Global Energy Interconnection." Časopis Pomorskog fakulteta Kotor - Journal of Maritime Sciences 23, no. 2 (November 19, 2022): 52–64. http://dx.doi.org/10.56080/jms221105.
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Belt and road initiative delivers an idea for Global Energy Interconnection (GEI) as globally interconnected strong and smart grid based on Ultra-High Voltage (UHV). Global Energy Interconnection is an infrastructure platform that can be used for clean energy production, transition and consumption worldwide. GEI facilitate efforts to meet global power demand with clean and green alternatives as low carbon energy. GEI is promoting integration of energy, information and transportation networks, enlarging global power trade, ensuring universal electricity service. GEI optimizes resource allocation and utilization by converting various energy sources including coal, oil, hydro, wind and solar into electricity and transmitting over long distance. It can achieve mutual support and free trade of clean energy from different regions, and maximize energy efficiency and economy by taking advantages of time-zone, seasonal and price difference. Actually, Global Energy Interconnection is a system that consist of “Smart Grid”, “UHV Grid” and “Clean Energy”. Smart Grid integrates modern smart technologies with respect to advanced power transmission, smart control, new energy integration and new energy storage. UHV Grid is mainly composed of 1000 kV (and above) AC and +-800 kV (and above) DC transmission lines, featuring long transmission distance, large capacity, high efficiency, low line loss, less land use and high security. The shaping up of GEI can be divided into three phase: domestic, intra-continental and intercontinental interconnection. UHV Grid result is visible in already tested in practice transmission lines of DC and AC voltage. Over 20 UHV networks have been built in China. There is one network longer than 2000 km in Brazil, and two networks of UHV in India.
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Zafar, Hammad, Ziaul Haq Abbas, Ghulam Abbas, Fazal Muhammad, Muhammad Tufail, and Sunghwan Kim. "An Effective Fairness Scheme for Named Data Networking." Electronics 9, no. 5 (May 2, 2020): 749. http://dx.doi.org/10.3390/electronics9050749.
Full textAbstract:
Named data networking (NDN) is a revolutionary approach to cater for modern and future Internet usage trends. The advancements in web services, social networks and cloud computing have shifted Internet utilization towards information delivery. Information-centric networking (ICN) enables content-awareness in the network layer and adopts name-based routing through the NDN architecture. Data delivery in NDN is receiver-driven pull-based and governed by requests (interests) sent out by the receiver. The ever-increasing share of high-volume media streams traversing the Internet due to the popularity and availability of video-streaming services can put a strain on network resources and lead to congestion. Since most congestion control techniques proposed for NDN are receiver-based and rely on the users to adjust their interest rates, a fairness scheme needs to be implemented at the intermediate network nodes to ensure that “rogue” users do not monopolize the available network resources. This paper proposes a fairness-based active queue management at network routers which performs per-flow interest rate shaping in order to ensure fair allocation of resources. Different congestion scenarios for both single path and multipath network topologies have been simulated to test the effectiveness of the proposed fairness scheme. Performance of the scheme is evaluated using Jain’s fairness index as a fairness metric.
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Saboor, Abdul, Mohd Fadzil Hassan, Rehan Akbar, Syed Nasir Mehmood Shah, Farrukh Hassan, Saeed Ahmed Magsi, and Muhammad Aadil Siddiqui. "Containerized Microservices Orchestration and Provisioning in Cloud Computing: A Conceptual Framework and Future Perspectives." Applied Sciences 12, no. 12 (June 7, 2022): 5793. http://dx.doi.org/10.3390/app12125793.
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Cloud computing is a rapidly growing paradigm which has evolved from having a monolithic to microservices architecture. The importance of cloud data centers has expanded dramatically in the previous decade, and they are now regarded as the backbone of the modern economy. Cloud-based microservices architecture is incorporated by firms such as Netflix, Twitter, eBay, Amazon, Hailo, Groupon, and Zalando. Such cloud computing arrangements deal with the parallel deployment of data-intensive workloads in real time. Moreover, commonly utilized cloud services such as the web and email require continuous operation without interruption. For that purpose, cloud service providers must optimize resource management, efficient energy usage, and carbon footprint reduction. This study presents a conceptual framework to manage the high amount of microservice execution while reducing response time, energy consumption, and execution costs. The proposed framework suggests four key agent services: (1) intelligent partitioning: responsible for microservice classification; (2) dynamic allocation: used for pre-execution distribution of microservices among containers and then makes decisions for dynamic allocation of microservices at runtime; (3) resource optimization: in charge of shifting workloads and ensuring optimal resource use; (4) mutation actions: these are based on procedures that will mutate the microservices based on cloud data center workloads. The suggested framework was partially evaluated using a custom-built simulation environment, which demonstrated its efficiency and potential for implementation in a cloud computing context. The findings show that the engrossment of suggested services can lead to a reduced number of network calls, lower energy consumption, and relatively reduced carbon dioxide emissions.
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Rizwan, Mian, Muhammad Waseem, Rehan Liaqat, Intisar Ali Sajjad, Udaya Dampage, Saleh H. Salmen, Sami Al Obaid, Mohamed A. Mohamed, and Andres Annuk. "SPSO Based Optimal Integration of DGs in Local Distribution Systems under Extreme Load Growth for Smart Cities." Electronics 10, no. 20 (October 18, 2021): 2542. http://dx.doi.org/10.3390/electronics10202542.
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Renewable energy-based distributed generators (DGs) are gaining more penetration in modern grids to meet the growing demand for electrical energy. The anticipated techno-economic benefits of these eco-friendly resources require their judicious and properly sized allocation in distribution networks (DNs). The preeminent objective of this research is to determine the sizing and optimal placing of DGs in the condensed DN of a smart city. The placing and sizing problem is modeled as an optimization problem to reduce the distribution loss without violating the technical constraints. The formulated model is solved for a radial distribution system with a non-uniformly distributed load utilizing the selective particle swarm optimization (SPSO) algorithm. The intended technique decreases the power loss and perfects the voltage profile at the system’s nodes. MATLAB is used for the simulation, and the obtained results are also validated by the Electrical Transient Analysis Program (ETAP). Results show that placing optimally sized DGs at optimal system nodes offers a considerable decline in power loss with an improved voltage profile at the network’s nodes. Distribution system operators can utilize the proposed technique to realize the reliable operation of overloaded urban networks.
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Wu, Ye, and Xiaowen Sun. "Optimization and Simulation of Enterprise Management Resource Scheduling Based on the Radial Basis Function (RBF) Neural Network." Computational Intelligence and Neuroscience 2021 (June 29, 2021): 1–10. http://dx.doi.org/10.1155/2021/6025492.
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In the human resource system of modern enterprises, human-post matching big data occupies an important irreplaceable position. With the deepening of the reform of state-owned enterprises, some shortcomings of human-post matching big data have become prominent. The purpose of this article is to solve the current state-owned enterprises. There are a variety of problems with big data in the enterprise, and an effective method is found that can accurately evaluate the degree of human-job matching in state-owned enterprises and provide a scientific basis for the manager of talent and resource allocation to make more rational decisions. Through the radial basis function (RBF) neural network-based big data model of human-post matching evaluation of state-owned enterprises, we scientifically and effectively evaluate the matching degree of the quality and ability of the personnel with the relevant requirements of the position and then help the company to adjust the personnel at any time changes in positions to maximize the efficiency of human resources. In this paper, considering the actual situation of the enterprise, the RBF neural network and the analytic hierarchy process (AHP) method are used comprehensively. Firstly, the AHP is used to obtain the weight of each evaluation index in the human-post matching index system. At the same time, the artificial neural network theory is self-adapting. Learning is helpful to solve the problem that the AHP method is too subjective. The two learn from each other’s strong points and combine their weaknesses organically to increase the convenience and effectiveness of evaluation.