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1
Abdulrahman, H., and V. A. Skorokhodov. "Biresource Networks with Magnetic Reachability." UNIVERSITY NEWS. NORTH-CAUCASIAN REGION. NATURAL SCIENCES SERIES, no. 3 (207) (October 2, 2020): 4–10. http://dx.doi.org/10.18522/1026-2237-2020-3-4-10.
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In this paper, ergodic biresource networks with magnetic reachability are studied. A special feature of the distribution of two resources in such networks is that one of the resources has priority in the distribution of resource flow values. A resource with a high priority is called first or main. Two cases of such networks are considered. In the first case, only the total throughput is specified for each arc. In the second case, two values of throughput and are specified for each arc u, and there are condition that the value of the second resource which is passing through any arc u cannot exceed the value . For each type of networks with magnetic reachability, resource allocation rules, which are based on the construction of an auxiliary network, are adapted. For the case of a semi-ergodic auxiliary network, the method for finding the limit state for an arbitrary value of the total resource is modified. Also, for networks with double throughputs, a method for finding the threshold value T', which is the maximum value of the first resource at which both resources are distributed independently of each other, is developed. The value of T' for each network depends on the total value of the second resource.
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Yang, Haizhu, Xiangyang Liu, Yiming Guo, and Peng Zhang. "Fault Location of Active Distribution Networks Based on the Golden Section Method." Mathematical Problems in Engineering 2020 (February 8, 2020): 1–9. http://dx.doi.org/10.1155/2020/6937319.
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Aiming at the problem of fault location in distribution networks with distributed energy resources (DERs), a fault location method based on the concepts of minimum fault reactance and golden section is proposed in this paper. Considering the influence of distributed energy resource supply on fault point current in distribution networks, an improved trapezoidal iteration method is proposed for load flow analysis and fault current calculation. This method only needs to measure the synchronous current of the distributed energy resource and does not need to measure the voltage information. Therefore, the investment in equipment is reduced. Validation is made using the IEEE 34-node test feeder. The simulation results show that the method is suitable for fault location of distribution networks with multiple distributed generators. This method can accurately locate the faults of the active distribution network under different conditions.
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Qi, Lu. "An Optimization Method of Sports Service Network Layout Based on Network Communication." Mathematical Problems in Engineering 2022 (April 14, 2022): 1–9. http://dx.doi.org/10.1155/2022/4980386.
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Sports culture industry (CI), as a new sunrise industry, has achieved unprecedented development in the world, and many developed countries regard it as a pillar industry. In our country, the sports CI is quickly growing and contributing significantly to national economic growth. The layout mode of the sports CI is crucial in identifying regional growth advantages and resource development, as well as maximizing industrial function allocation and creating sports CI development strategy. This paper takes Dalian’s sports CI as the research object and expounds the concept of sports culture, sports CI, and spatial layout of sports CI through analyzing and sorting out previous research results. This study analyses the evolution and spatial distribution of the Dalian sports CI, as well as the current challenges, using theories and methodologies from sports science and economic geography and proposes countermeasures for Dalian to develop its sports CI. Regional development theories, such as central place theory, growth pole theory, point axis theory, and Maslow’s hierarchy of needs theory, have important theoretical value and practical guiding significance for the rationalization of spatial distribution of Dalian sports CI. On the basis of analyzing the resources, traffic network, and economic development of Dalian sports CI, the paper constructs the spatial distribution mode of Dalian sports CI, namely, two core points, three development axes, and multiple nodes, and puts forward the measures to optimize the spatial distribution of Dalian sports CI. This paper examines the current condition, resource architecture, and major structure of supply of leisure sports service items in the Zhejiang coastline area using the literature and field inquiry methodologies. On this basis, the optimization countermeasures of combining Zhejiang coastal leisure sports service products with recreational fishery and yacht economy are put forward to perfect the system of coastal leisure sports service products and improve the supply capacity.
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Tan, Jing Jing, Ning Pan, and Ke Wang. "Study of Resource Allocation Method of Communication Network in Dense Crowded Area." Applied Mechanics and Materials 713-715 (January 2015): 1115–18. http://dx.doi.org/10.4028/www.scientific.net/amm.713-715.1115.
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In the dense crowded area, the communication resource allocation method has a very broad application space in the communication research field. Therefore, an improved communication resource distribution method in the dense crowded area is proposed based on pheromone search algorithm. In the dense crowded area, the regional communication network is constructed, and the pheromone of each resource node is taken with initialization processing. The collection of communication resource allocation task is obtained, the execution time of task is calculated, and the communication channel is selected. According to the pheromone concentration, all the pheromones are updated. The optimal channel of optimized communication resource allocation is searched, and the algorithm is improved. The simulation results show that the improved algorithm is applied in the regional allocation of communication resources in crowded area, the communication time can be effectively reduced, and the utilization of communication resources is improved, it will have a prospect application value in practice.
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Lu, Shuijin, and Yujie Mo. "Distributed dispatching method of active distribution network considering multiple regulation resources." Journal of Physics: Conference Series 2237, no. 1 (March 1, 2022): 012004. http://dx.doi.org/10.1088/1742-6596/2237/1/012004.
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Abstract In view of the low capacity of distribution network to accept renewable energy such as wind power and photovoltaic, which leads to the failure of active distribution network to achieve the expected economic benefits, a distributed scheduling method of active distribution network considering multiple regulation resources is proposed in this paper. In the case of multiple coupled energy access, the resource collaborative scheduling principle is designed, the business process of adjustable resources participating in the emergency coordination control of auxiliary distribution network is proposed, and the supply side resources and demand side resources are planned. The installation location and initial capacity of distributed generation are determined by network sensitivity factor method. After optimizing the capacity, the location and scale of distributed generation are obtained. Considering the load response and distribution of distributed generation, the distributed dispatching model of active distribution network is established with the goal of minimizing output cost and dispatching cost. The net annual value method is used to calculate the operation benefit increment of distribution network, so as to evaluate the effect of control. Taking the pilot project in Zhejiang as an example, the maximum operating benefit increment of this method is 367600 yuan, which is 32800 yuan and 45300 yuan higher than the scheduling method based on power load temporal and spatial correlation and risk distribution respectively, which can improve the operating benefit for the power grid company.
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Mundher, Zaid. "A Method for Investigating Coverage Area Issue in Dynamic Networks." Technium: Romanian Journal of Applied Sciences and Technology 4, no. 3 (April 16, 2022): 19–27. http://dx.doi.org/10.47577/technium.v4i3.6342.
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Coverage area in dynamic networks is considered an important issue that affects their general performance. It also affects the delay time when exchanging data and the consumption of resources in the network. Moreover, the coverage area issue in dynamic networks is directly affected by the distributions of nodes within the environment. Movement patterns may also affect the performance when it comes to coverage area. Therefore, this work develops a method that simulates different scenarios. These scenarios include a variety of settings and parameters that are believed to affect the coverage area issue of dynamic networks. These experiments enable network developers to be aware of the optimal conditions that maximize the coverage area of dynamic network nodes and eventually improve the overall performance of the network. Three distributions are used in the experiments namely, Cauchy distribution, Power-Law distribution, and Normal distribution. Also, the simulations incorporate the correlation mobility model for nodes dynamics. The findings show that Cauchy distribution is not appropriate for simulating dynamic networks due to the large uncovered areas by nodes communications. Also, the stability of an approach is considered an important factor when measuring the performance of a dynamic network. The results of this research are important to avoid wasting network resources.
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Yang, Zhidong, Guangjiu Chen, Jianwu Ding, Xiaojing Kang, and Meng Sheng. "Multi-Stage Distribution Network Space Load Forecasting Method Considering Demand Side Resources." Journal of Nanoelectronics and Optoelectronics 15, no. 12 (December 1, 2020): 1474–81. http://dx.doi.org/10.1166/jno.2020.2881.
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Under the background of the further development of electric power, this paper forecasts the spatial load of distribution network, and proposes a multi-stage spatial load forecasting method considering the demand side resources. Firstly, the load of distribution network is pretreated to improve the prediction function of the processing system, and the working efficiency of the whole system is enhanced to solve the maximum load value. Then, the different conditions of demand side resources are considered step by step to realize the fine analysis, confirm the saturation density value of load, understand the specific information of spatial load, master the predicted data status, and finally carry out the comprehensive prediction method research of spatial load to realize the prediction research of spatial load of distribution network. The experimental results show that the multi-stage spatial load forecasting method considering demand side resources has high accuracy and reliability, and its forecasting effect can improve the system forecasting performance to a certain extent, reduce unnecessary operation time, reduce energy and resource consumption, and promote the development of load forecasting research.
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Hung Tran, Cong, Dien Tam Le, and Thanh Hieu Huynh. "Game Theory Application Resources Management and Distribution in Blockchain Network." International Journal of Network Security & Its Applications 13, no. 1 (January 31, 2021): 65–78. http://dx.doi.org/10.5121/ijnsa.2021.13105.
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The paper illustrated a basic blockchain system, applying game theory to simulate resource management in blockchain transactions. By the method of illustration, simulation, our team has demonstrated the effect of game theory transactions, transactions with specific value can demonstrate the benefits of game theory in co-life. time can be used to manage resources in blockchain. Based on the proposed algorithm model, we have built a test system with the maximum number of virtual machines to demonstrate the effectiveness in applying game theory in managing and distributing resources for transactions in the blockchain network.
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Han, Bing, and Yonggang Li. "Optimization method for reducing network loss of dc distribution system with distributed resource." Photonic Network Communications 37, no. 2 (November 15, 2018): 233–42. http://dx.doi.org/10.1007/s11107-018-0805-5.
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Li, Da, Ningli Qin, Bo Li, Xiaosong Jing, Changyu Du, and Chunyi Wan. "Resource allocation method based on massive MIMO NOMA MEC on distribution communication network." IOP Conference Series: Earth and Environmental Science 634 (February 5, 2021): 012069. http://dx.doi.org/10.1088/1755-1315/634/1/012069.
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Kamal, Muhammad Ayoub, Hafiz Wahab Raza, Muhammad Mansoor Alam, Mazliham Mohd Su’ud, and Aznida binti Abu Bakar Sajak. "Resource Allocation Schemes for 5G Network: A Systematic Review." Sensors 21, no. 19 (October 2, 2021): 6588. http://dx.doi.org/10.3390/s21196588.
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Fifth-generation (5G) communication technology is intended to offer higher data rates, outstanding user exposure, lower power consumption, and extremely short latency. Such cellular networks will implement a diverse multi-layer model comprising device-to-device networks, macro-cells, and different categories of small cells to assist customers with desired quality-of-service (QoS). This multi-layer model affects several studies that confront utilizing interference management and resource allocation in 5G networks. With the growing need for cellular service and the limited resources to provide it, capably handling network traffic and operation has become a problem of resource distribution. One of the utmost serious problems is to alleviate the jamming in the network in support of having a better QoS. However, although a limited number of review papers have been written on resource distribution, no review papers have been written specifically on 5G resource allocation. Hence, this article analyzes the issue of resource allocation by classifying the various resource allocation schemes in 5G that have been reported in the literature and assessing their ability to enhance service quality. This survey bases its discussion on the metrics that are used to evaluate network performance. After consideration of the current evidence on resource allocation methods in 5G, the review hopes to empower scholars by suggesting future research areas on which to focus.
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Liu, Haike, Huajian Zhang, Kai Yang, and Jiali Li. "Virtualized High Throughput Satellite Gateway with a Global Bandwidth Management Method." Mobile Information Systems 2022 (January 11, 2022): 1–11. http://dx.doi.org/10.1155/2022/6257885.
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With the development of new satellite payload technology, in order to improve the utilization of system resources, research is based on software-defined network (SDN) and network function virtualization (NFV) gateway architecture. Based on this architecture, the system realizes global resource management and overall data distribution, which can solve the problem of resource allocation and maximum/minimum rate guarantee between different VNO terminals under different beams, different gateways, and different satellites. For this, a global bandwidth management method can be used which is mainly a process of management to control the traffic on a communication link. The proposed global resource management and control method can be based on the rate guarantee value of the VNO/terminal configured in the system as the basic limiting condition and reallocate the rate guarantee value limiting parameter according to the resource application status of the online terminal. The method can maximize the resource utilization of the entire satellite communication system and satisfy the resource request of the user terminal as much as possible.
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Li, Fenglei, Chunxia Dou, and Shiyun Xu. "Optimal Scheduling Strategy of Distribution Network Based on Electric Vehicle Forecasting." Electronics 8, no. 7 (July 22, 2019): 816. http://dx.doi.org/10.3390/electronics8070816.
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Based on the Monte Carlo method, this paper simulates, predicts the load, and considers the travel chain of electric vehicles and different charging methods to establish a predictive model. Based on the results of electric vehicle simulation prediction, an optimal scheduling model of the distribution network considering the demand response side load is established. The firefly optimization algorithm is used to solve the optimal scheduling problem. The results show that the prediction model proposed in this paper has a certain reference value for the prediction of an electric vehicle load. The electric vehicle is placed in the optimal scheduling resource of the distribution network, which increases the dimension of the scheduling resources of the network and improves the economics of the distribution network operation.
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Khakimov, A., A. Suminov, and A. Muthanna. "DEVELOPMENT OF EDGE COMPUTING DISTRIBUTION METHOD IN VANET." Telecom IT 7, no. 2 (December 2019): 46–54. http://dx.doi.org/10.31854/2307-1303-2019-7-2-46-54.
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Research subject. Devoted the VANET network architecture, based on SDN / MEC (software-defined networks / mobile edge computing) systems that can reduce network load and traffic density. Method. The developed algorithm is considered. A testbed experiment based on a model network was done. Core results. The article examined the possibility of temporarily placing an application in RSU to reduce the load on the transit network. The condition for temporary placement of an application is based on data on congestion of road sections from Google Map & Yandex monitoring systems and current statistics on Internet traffic. Practical relevance. The proposed architecture allows to optimal use of RSU/MEC resources and significantly reduces the delay and load on data transmission.
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Zhao, Guotao, and Jie Ding. "Image Network Teaching Resource Retrieval Algorithm Based on Deep Hash Algorithm." Scientific Programming 2021 (October 11, 2021): 1–7. http://dx.doi.org/10.1155/2021/9683908.
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In order to improve the retrieval ability of multiview attribute coded image network teaching resources, a retrieval algorithm of image network teaching resources based on depth hash algorithm is proposed. The pixel big data detection model of the multiview attribute coding image network teaching resources is constructed, the pixel information collected by the multiview attribute coding image network teaching resources is reconstructed, the fuzzy information feature components of the multiview attribute coding image are extracted, and the edge contour distribution image is combined. The distributed fusion result of the edge contour of the view image of the network teaching resources realizes the construction of the view feature parameter set. The gray moment invariant feature analysis method is used to realize information coding, the depth hash algorithm is used to realize the retrieval of multiview attribute coded image network teaching resources, and the information recombination is realized according to the hash coding result of multiview attribute coded image network teaching resources, thus improving the fusion. The simulation results show that this method has higher precision, better retrieval precision, and higher level of resource fusion for multiview coded image network teaching resource retrieval.
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Shen, Ling, Guangming Wang, and Haiwei Gao. "Regional Information Management of Higher Education Based on Network Security and Grey Relational Analysis." Security and Communication Networks 2022 (March 31, 2022): 1–7. http://dx.doi.org/10.1155/2022/6638408.
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The optimal allocation of higher education resources is related to the growth of the regional economy and the development of innovation ability. Therefore, it is essential to deal with the relationship between quality, scale, efficiency, and fairness in the process of regional educational resource allocation. This study uses a method that combines empirical and normative analysis to classify and integrate regional educational data using the grey relational method and to improve the status quo of regional educational resource distribution. The infrastructure and resource-sharing mode of a regional university information resource grid database is designed in combination with the network security method. Various performance indicators are used to evaluate the quality of resource sharing. The assessment of resources sharing using performance indicators can enhance the initiative and enthusiasm of resource sharing among colleges and universities in the region. The feasibility of the scheme is verified through the educational information integration test, which can effectively promote the regional development of higher education and improve the quality of educational services.
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Li, Xiaohui, Xin Su, Nansi He, and Anil Sharma. "Optimization Distribution Method of Computer Sensor Network Communication Based on the Linear Planning Model." Journal of Sensors 2022 (March 26, 2022): 1–7. http://dx.doi.org/10.1155/2022/7520749.
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In order to explore the optimal allocation method of computer network communication, a linear programming model is proposed. Based on the overall structure of service chain deployment, the integer linear programming model is introduced to make mathematical modeling, so that network resources and load balancing can be effectively utilized under resource and delay constraints. Simulation results showed that in the experiment, 10 to 100 SFC request intensities were generated, respectively, calculating the request acceptance rates of the three deployment algorithms. Under the same conditions, the average request acceptance rate based on the G-kSP algorithm is about 95.4% and about 92.3%, and the greedy deployment algorithm is about 81.7%. We show that the optimized distribution method of computer sensor network communication based on a linear programming model reduces the load balance and time complexity while reducing the request acceptance rate.
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Skorokhodov, V. A., and D. O. Sviridkin. "Flows in strongly regular periodic dynamic resource networks." Vestnik Udmurtskogo Universiteta. Matematika. Mekhanika. Komp'yuternye Nauki 31, no. 3 (September 2021): 458–70. http://dx.doi.org/10.35634/vm210308.
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This paper is devoted to studying the processes of resource allocation in dynamic resource networks. In such networks, the capacities of the arcs depend on time. Resource allocation in the network occurs in discrete time. The resource of each vertex is distributed only between adjacent vertices according to some rules. The study of the processes of resource redistribution in such networks is carried out. The main goal is to develop methods for finding the limit state (distribution) of a resource in a dynamic resource network. It is shown that the approach based on the construction of an auxiliary network is also applicable to reduce the problem of resource allocation in a dynamic network to a similar problem in an auxiliary network. Theorems on the existence of a limit state on an auxiliary graph are proved for strongly regular periodic dynamical networks. To find the limit states, one can use the approaches which are developed for the shortest path problem in dynamic networks.
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Cui, Yaping, Xinyun Huang, Dapeng Wu, and Hao Zheng. "Machine Learning-Based Resource Allocation Strategy for Network Slicing in Vehicular Networks." Wireless Communications and Mobile Computing 2020 (November 17, 2020): 1–10. http://dx.doi.org/10.1155/2020/8836315.
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The diversified service requirements in vehicular networks have stimulated the investigation to develop suitable technologies to satisfy the demands of vehicles. In this context, network slicing has been considered as one of the most promising architectural techniques to cater to the various strict service requirements. However, the unpredictability of the service traffic of each slice caused by the complex communication environments leads to a weak utilization of the allocated slicing resources. Thus, in this paper, we use Long Short-Term Memory- (LSTM-) based resource allocation to reduce the total system delay. Specially, we first formulated the radio resource allocation problem as a convex optimization problem to minimize system delay. Secondly, to further reduce delay, we design a Convolutional LSTM- (ConvLSTM-) based traffic prediction to predict traffic of complex slice services in vehicular networks, which is used in the resource allocation processing. And three types of traffic are considered, that is, SMS, phone, and web traffic. Finally, based on the predicted results, i.e., the traffic of each slice and user load distribution, we exploit the primal-dual interior-point method to explore the optimal slice weight of resources. Numerical results show that the average error rates of predicted SMS, phone, and web traffic are 25.0%, 12.4%, and 12.2%, respectively, and the total delay is significantly reduced, which verifies the accuracy of the traffic prediction and the effectiveness of the proposed strategy.
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Kimambo, Josephina, Kwame S. Ibwe, Ellen Kalinga, and Abdi T. Abdalla. "Resource Efficient Advanced Metering Infrastructure Model." Tanzania Journal of Science 48, no. 1 (March 31, 2022): 57–72. http://dx.doi.org/10.4314/tjs.v48i1.6.
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Advanced Metering Infrastructure (AMI) enables two-way communication between smart devices and utility control centers. This involves remote monitoring and control of energy consumption as well as other parameters in the electrical power network in real time. However, increasing technologies in AMI due to huge deployment of smart meters, integration of devices and application of sensors, demand a strong architectural model with the best network topology to guarantee efficient usage of network resources with minimal latency. In this work, a resource efficient multi-hop network architecture is proposed using hybrid media access protocols. The architecture combines queuing and random-access protocol to achieve optimal network performance. Numerical results show that the probability of delay incurred by an arbitrary smart meter depends on the mean and distribution of the queue switch over a period. It is also observed that for a single queued system, the throughput performance is equal to the existing hybrid method. As the number of smart meters increases to 500, the throughput of the proposed method improves by 10% compared to the existing method. Likewise, as the number of smart meters increases to 500, the delay reduced by 15% compared to the existing method.
Keywords: Advanced Metering Infrastructure; hybrid media access protocols; Smart Meter; Smart Grid; Power Network.
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Ren, Jin Xia, and Hao Yang Guo. "Research on the Network Congestion Control Based on GA-PSO Path Optimization." Applied Mechanics and Materials 513-517 (February 2014): 675–78. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.675.
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Based on the integration of the genetic algorithm and particle swarm algorithm, a network congestion control method is proposed for path optimization, which takes the load balanced distribution function and the resource consumption function as optimization target and optimizes path under the condition of meeting a number of QoS metrics such as bandwidth, delay, expense. Aiming at avoidance of network congestion, the approach attempt to minimize the network resource consumption and balance the distribution of network load. Simulation results show that the method is effective and reliable.
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Bushelenkov, S., and A. Paramonov. "ANALYSIS AND METHODS OF ORGANIZING NODE PART OF THE ACCESS NETWORK." Telecom IT 8, no. 1 (April 2020): 34–41. http://dx.doi.org/10.31854/2307-1303-2020-8-1-34-41.
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This paper presents results of developing a models and methods for organizing a node part of an optical access network. The object of research is optical cross of the GPON, and the subject of research is models and methods for reducing its resource consumption and increasing other parameters characterizing its functioning. Models and methods are proposed for choosing the type of equipment for optical cable distribution system, as well as a model and method for choosing the structure of switching connections that solve the problem of minimizing the amount of resources.
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Kim, Yeonggwang, Jaehyung Park, Jinyoung Kim, Junchurl Yoon, Sangjoon Lee, and Jinsul Kim. "A Modified Quad Q Network Algorithm for Predicting Resource Management." Applied Sciences 11, no. 11 (June 1, 2021): 5154. http://dx.doi.org/10.3390/app11115154.
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As the resource management systems continues to grow, the resource distribution system is expected to expand steadily. The demand response system enables producers to reduce the consumption costs of an enterprise during fluctuating periods in order balance the supply grid and resell the remaining resources of the product to generate revenue. Q-learning, a reinforcement learning algorithm based on a resource distribution compensation mechanism, is used to make optimal decisions to schedule the operation of smart factory appliances. In this paper, we proposed an effective resource management system for enterprise demand response using a Quad Q Network algorithm. The proposed algorithm is based on a Deep Q Network algorithm that directly integrates supply-demand inputs into control logic and employs fuzzy inference as a reward mechanism. In addition to using uses the Compare Optimizer method to reduce the loss value of the proposed Q Network Algorithm, Quad Q Network also maintains a high accuracy with fewer epochs. The proposed algorithm was applied to market capitalization data obtained from Google and Apple. Also, we verified that the Compare Optimizer used in Quad Q Network derives the minimum loss value through the double operation of Double Q value.
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Wan, Bingtong, Xueying Bao, and Jianchang Zhao. "Evaluation Method and Application of Ecological Sensitivity of Intercity Railway Network Planning." Sustainability 14, no. 2 (January 12, 2022): 804. http://dx.doi.org/10.3390/su14020804.
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In the planning stage of the intercity railway network, the ecological sensitivity evaluation of the planning scheme is not only the key content to explore the ecological environmental rationality of the planning scheme but also a scientific means to promote the sustainable development of intercity railway networks. The purpose of this study is to establish an evaluation method that can quantitatively evaluate the ecological sensitivity of intercity railway network planning to put forwards targeted optimization and adjustment suggestions for the planning scheme. Taking the intercity railway network planning of Guizhou Province as an example, its ecological sensitivity is predicted and evaluated. Six types of ecologically sensitive areas were selected as ecological sensitivity evaluation factors, including protected areas, drinking water sources, geological disaster-prone areas, soil erosion areas, cultivated land resource distribution areas and coal resource distribution areas. Based on the GIS overlay method, the quantitative measurement methods of each evaluation factor are established in turn, and the single factor sensitivity evaluation index is obtained. In addition, the weighted superposition model is used to quantitatively calculate the ecological sensitivity of the planned lines of the intercity railway network in Guizhou Province. Finally, the short board factor of each planned line is obtained, and targeted optimization and adjustment suggestions are put forwards. The research content of this paper can provide a theoretical reference for the practical evaluation of the ecological sensitivity of intercity railway network planning.
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Wang, Fu. "Water Resources Information Management System Based on Agent Model." Journal of Physics: Conference Series 2066, no. 1 (November 1, 2021): 012036. http://dx.doi.org/10.1088/1742-6596/2066/1/012036.
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Abstract With the rapid development and wide application of computer technology and network technology, the Internet has become an important information infrastructure in modern society. However, the resource capacity used by the Internet is much smaller than the actual resource capacity. How to choose the right resources to serve the people has become a crucial issue. Huge data resources, heterogeneous distribution and unreasonable resource organization are important reasons for this phenomenon. When solving the problems of batch data, heterogeneous distribution, complex processing, and cumbersome use in a distributed heterogeneous network environment, the traditional methods of resource processing and resource aggregation services become more and more difficult. In recent years, how to redistribute and organize scattered resources in a dynamic and open environment, how to effectively gather different resources, realize resource sharing and full utilization, and provide users with reasonable and convenient resource collection services have become one of the main research points. This paper mainly uses the questionnaire survey method to study the water resources information management system based on the Agent model. First, it summarizes the characteristics of the Agent model and the problems existing in the water resource information management system based on the Agent model through the literature research method, and then uses the questionnaire survey method, investigate some evaluations and suggestions about the need to use the water resources system. The results of the survey show that in the evaluation of the use of the water resources information management system based on the Agent model, about 50% of people encounter the waiting time for the system. For long-term phenomena, about 30% of them are stuck. The recommendations for the use of water resources information management systems based on the Agent model are more concerned about the simple operation of the system, with about 54% of the choices, and about 36% of the people choosing when there is no lag.
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Naumov, Valeriy A., Yuliya V. Gaidamaka, and Konstantin E. Samouylov. "Computing the Stationary Distribution of Queueing Systems with Random Resource Requirements via Fast Fourier Transform." Mathematics 8, no. 5 (May 12, 2020): 772. http://dx.doi.org/10.3390/math8050772.
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Queueing systems with random resource requirements, in which an arriving customer, in addition to a server, demands a random amount of resources from a shared resource pool, have proved useful to analyze wireless communication networks. The stationary distributions of such queuing systems are expressed in terms of truncated convolution powers of the cumulative distribution function of the resource requirements. Discretization of the cumulative distribution function and the application of the fast Fourier transform are a traditional way of calculating convolutions. We suggest finding truncated convolution powers of the cumulative distribution functions by calculating the convolution powers of the truncated cumulative distribution functions via fast Fourier transform. This radically decreases computational complexity. We introduce the concept of resource load and investigate the accuracy of the proposed method at low and high resource loads. It is shown that the proposed method makes it possible to quickly and accurately calculate truncated convolution powers required for the analysis of queuing systems with random resource requirements.
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Fu, Liping, Kaibo Xu, Feng Liu, Lu Liang, and Zhengmin Wang. "Regional Disparity and Patients Mobility: Benefits and Spillover Effects of the Spatial Network Structure of the Health Services in China." International Journal of Environmental Research and Public Health 18, no. 3 (January 26, 2021): 1096. http://dx.doi.org/10.3390/ijerph18031096.
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Background: The distribution of medical resources in China is seriously imbalanced due to imbalanced economic development in the country; unbalanced distribution of medical resources makes patients try to seek better health services. Against this backdrop, this study aims to analyze the spatial network characteristics and spatial effects of China’s health economy, and then find evidence that affects patient mobility. Methods: Data for this study were drawn from the China Health Statistical Yearbooks and China Statistical Books. The gravitational value of China’s health spatial network was calculated to establish a network of gravitational relationships. The social network analysis method was used for centrality analysis and spillover effect analysis. Results: A gravity correlation matrix was constructed among provinces by calculating the gravitational value, indicating the spatial relationships of different provinces in the health economic network. Economically developed provinces, such as Shanghai and Jiangsu, are at the center of the health economic network (centrality degree = 93.333). These provinces also play a strong intermediary role in the network and have connections with other provinces. In the CONCOR analysis, 31 provinces are divided into four blocks. The spillover effect of the blocks indicates provinces with medical resource centers have beneficial effects, while provinces with insufficient resources have obvious spillover effects. Conclusion: There is a significant gap in the geographical distribution of medical resources, and the health economic spatial network structure needs to be improved. Most medical resources are concentrated in economically developed provinces, and these provinces’ positions in the health economic spatial network are becoming more centralized. By contrast, economically underdeveloped regions are at the edge of the network, causing patients to move to provinces with medical resource centers. There are health risks of the increasing pressure to seek medical treatment in developed provinces with abundant medical resources.
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Wang, Feng, Wei Chai, Xiaotian Shi, Mingru Dong, and Bin Yan. "Does Regional Financial Resource Contribute to Economic Growth? From the Perspective of Spatial Correlation Network." SAGE Open 11, no. 1 (January 2021): 215824402199938. http://dx.doi.org/10.1177/2158244021999381.
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Using the method of social network analysis, this article explores the characteristics of financial resources distribution at the provincial level in China from 2000 to 2017, and analyzes the influencing factors and network effects of the spatial correlation network characteristics on distribution of financial resources, the results are as follows: The overall network characteristics of the financial resources distribution among provinces and cities in China are of low density, of high dependence and poor stability. The level of economic development, marketization, and integration are related to the spatial correlation network of the distribution of financial resources, and the level of integration and marketization have a significant positive impact on it. Due to the imbalance of economic development among regions in China, the overall network characteristics have a negative network effect on the speed of economic development. Individual network characteristics have a positive network effect on the speed of economic development. Improving network density, network correlation, and reducing network level can narrow the gap in economic development between provinces.
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Xu, Xiao Feng, Jin Lou Zhao, and Jie Kun Song. "Optimal Model of Resource Planning for Collaborative Logistics Network Considering Robust Constraints." Advanced Materials Research 403-408 (November 2011): 3642–46. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.3642.
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Uncertainty factors which influence the resource plan for collaborative logistics network, is the completely uncertain problem that parameter status and probability distribution are unknown, but traditional plan methods can’t ensure the robustness of plan implementation. Based on robust optimal control, the paper carries on simulation about uncertain parameters with Monte Carlo method, and proposes a expected model of robust restraint, the robustness constrains realizes to contract the feasible region and improve robustness of model. Finally, The simulation results illustrate the validity of the improved model.
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Zhuk, A. A., and V. M. Buloichyk. "Neural network method of the decision Of the nonlinear problem of optimum distribution of the non-uniform resource." «System analysis and applied information science», no. 1 (April 26, 2021): 45–52. http://dx.doi.org/10.21122/2309-4923-2021-1-45-52.
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Given article is devoted features of the decision of a problem of integer nonlinear programming, by means of developed neural network method and algorithm of nonlinear optimization of means «decision Search» tabular processor Microsoft Excel. In offered neural network method the task in view decision is made by means of a recurrent neural network (RNN) matrix architecture with m neurons in each line and n neurons in each column. All neurons such network are connected with each other by communications, and the signal from an exit neuron can move on its input. Neural network method is characterized by that on inputs mentioned RNN the entrance vector of values of parameters of optimized nonlinear criterion function of a problem of distribution of a non-uniform resource moves, calculation of values of weight factors connected among themselves neurons is carried out and signal RNN is formed. This signal by means of nonlinear function will be transformed to the discrete target signal characterizing values quasi-optimal of the decision of the mentioned problem which size changes from 0 to 1. The estimation of efficiency of the decision of a considered problem was carried out at its various values of an indicator of efficiency on the basis of developed imitating model RNN. As indicators of efficiency of application offered neural network method were used – an average relative error and time of the decision of a problem. The value received by means of algorithm of nonlinear optimization of means was accepted to the exact decision «decision Search» tabular processor Microsoft Excel. The analysis of the received results of the experimental researches, offered neural network method, has allowed to make the conclusion that in comparison with an existing method of nonlinear optimization of tabular processor Microsoft Excel use offered neural network method allows essentially (in 9,4 times) to lower time of the decision of a problem dimension 10 × 8 (m × n) and thus to provide accuracy of its decision not less than 99,8 %.
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Chen, Uei-Ren, and Yun-Ching Tang. "Realistic Modeling of Resources for a Large-Scale Computational Grid System." International Journal of Grid and High Performance Computing 4, no. 3 (July 2012): 1–29. http://dx.doi.org/10.4018/jghpc.2012070101.
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To build a large-scale computational grid resource model with realistic characteristics, this paper proposes a statistical remedy to approximate the distributions of computational and communicational abilities of resources. After fetching the source data of resources including computing devices and networks from the real world, the gamma and normal distributions are employed to approximate probabilities for the ability distribution of grid resources. With this method, researchers can supply the computational grid simulators with required parameters relating to computational and communicational abilities. The experiment result shows that proposed methodology can lead to a better precision according to the error measurement of the simulated data and its source. The proposed method can support existing modern grid simulators with a high-precision resource model which can consider the characteristics of distribution for its computational and communicational abilities in the grid computing environment.
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He, Xuan, Kai Niu, Zhiqiang He, Jiaru Lin, Hui Zhang, and Zhong-Yuan Jiang. "Efficient packet navigation method on scale-free networks with finite and diversiform node delivery capacity." International Journal of Modern Physics C 27, no. 09 (August 2016): 1650098. http://dx.doi.org/10.1142/s0129183116500984.
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Routing strategy is essential for high transport efficiency on realistic networked complex systems. Beginning from the consideration of finite and diversiform node delivery capacity distributions, a general node capacity allocation mechanism with a tunable parameter [Formula: see text] is presented. A node capacity, based routing strategy is proposed to improve the network traffic capacity. Compared with the traditional shortest path routing (SPR) and the efficient routing (ER) methods, it suggests that routing strategy should be chosen heuristically according to the limited capacity resource distribution, instead of using one certain method for all cases. With proper range of parameter [Formula: see text], the new routing strategy achieves the highest traffic capacity and other preferable measure metrics including network diameter, average path length, efficient betweenness, average packet travel time and average traffic load. The theoretical analysis for traffic capacity has a good correspondence to the simulation results. This work studies routing mechanisms from a very practical perspective, and helps network researchers to understand the traffic dynamics on complex networks comprehensively.
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Andrabi, Umer Mukhtar, Sergey N. Stepanov, Juvent Ndayikunda, and Margarita G. Kanishcheva. "CELLULAR NETWORK RESOURCE DISTRIBUTION METHODS FOR THE JOINT SERVICING OF REAL-TIME MULTISERVICE TRAFFIC AND GROUPED IOT TRAFFIC." T-Comm 14, no. 10 (2020): 61–69. http://dx.doi.org/10.36724/2072-8735-2020-14-10-61-69.
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Immense growth in the volumes and multiplicity of data to be collected in future Internet of Things (IoT) applications is one of the crucial challenges for the networking organizations as they develop from 4G+ to true 5G systems. Particularly bulk of this traffic includes complex, unstructured and varied data (Big Data) evolve from smart networking ecosystems (LTE-devices, NB-IoT devices). Although 5G offers many low power wide area technologies (Lora WAN, GSM and NB-IoT etc.), principally NB-IoT seems very promising addressing the problem because of its certain characteristics like high fault tolerance, delay tolerance, higher coverage area etc. However, due to the limited bandwidth (180 kHz) availability one of the challenges is how to efficiently use these resources to support and handle massive number of growing IoT devices, also resource management and allocation methodology between LTE and NB-IoT traffic flows. In this context, several key issues for IoT communications in 5G networks should be addressed to satisfy quality of service (QoS) provisioning. In this paper, we proposed a mathematical model for Operator Surveillance systems for sharing radio resources between LTE and NB-IoT. The model utilizes the technique of network slicing for resource management. The proposed techniques provide scenarios that aims to offer a trade-off between the two types of traffics by guaranteeing the network performance and avoiding unproductive utilization of available resources.
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Belousov, Vadim, Irina Fateeva, and Antonina Deniskina. "Parametrical network models of distribution of limited resources in difficult systems." MATEC Web of Conferences 265 (2019): 07025. http://dx.doi.org/10.1051/matecconf/201926507025.
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In article effective methods of the temporary analysis and calculation of the generalized network models are offered. On their basis the class of parametrical network models is under construction and applications of such models to problems of distribution of limited resources of difficult systems in the conditions of an intensification of works are considered. A number of terms of scheduling is specified. Conditions of consistency and criteria of resource resolvability of some classes of tasks on such models are investigated.
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Liang, Jianxiong, Xiaoguang Chen, and Tianyi Wang. "Percolation Distribution in Small-World Quantum Networks." Applied Sciences 12, no. 2 (January 11, 2022): 701. http://dx.doi.org/10.3390/app12020701.
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Quantum networks have good prospects for applications in the future. Compared with classical networks, small-world quantum networks have some interesting properties. The topology of the network can be changed through entanglement exchange operations, and different network topologies will result in different percolation thresholds when performing entanglement percolation. A lower percolation threshold means that quantum networks require fewer minimum resources for communication. Since a shared singlet between two nodes can still be a limitation, concurrency percolation theory (ConPT) can be used to relax the condition. In this paper, we investigate how entanglement distribution is performed in small-world quantum networks to ensure that nodes in the network can communicate with each other by establishing communication links through entanglement swapping. Any node can perform entanglement swapping on only part of the connected edges, which can reduce the influence of each node in the network during entanglement swapping. In addition, the ConPT method is used to reduce the percolation threshold even further, thus obtaining a better network structure and reducing the resources required.
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An, Yingbo, Meiling Xu, and Chen Shen. "Classification Method of Teaching Resources Based on Improved KNN Algorithm." International Journal of Emerging Technologies in Learning (iJET) 14, no. 04 (February 27, 2019): 73. http://dx.doi.org/10.3991/ijet.v14i04.10131.
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In order to effectively utilize the network teaching resources, a teaching resource classification method based on the improved KNN (K-Nearest Neighbor) algorithm was proposed. Taking the text class primary and secondary school teaching resources as the research object, combined with the domain characteristics, the KNN algorithm was improved. By measuring the sample space density, the text of the high-density area was found. Different clipping methods were proposed for both intra-class and inter-class regions. The problem of cropping in the space of multiple class boundaries was considered. Results showed that the method ensured uniform distribution of samples and reduced the time of classification. Therefore, under the Weka platform, the improved KNN algorithm is effective.
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Ren, Hongjia, Xianchang Wang, Hongbo Ren, and Qiulin Guo. "Spatial Distribution Prediction of Oil and Gas Based on Bayesian Network with Case Study." Mathematical Problems in Engineering 2020 (August 27, 2020): 1–9. http://dx.doi.org/10.1155/2020/4986563.
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Effectively predicting the spatial distribution of oil and gas contributes to delineating promising target areas for further exploration. Determining the location of hydrocarbon is a complex and uncertain decision problem. This paper proposes a method for predicting the spatial distribution of oil and gas resource based on Bayesian network. In this method, qualitative dependency relationship between the hydrocarbon occurrence and key geologic factors is obtained using Bayesian network structure learning by integrating the available geoscience information and the current exploration results and then using Bayesian network topology structure to predict the probability of hydrocarbon occurrence in the undiscovered area; finally, the probability map of hydrocarbon-bearing is formed by interpolation method. The proposed method and workflow are further illustrated using an example from the Carboniferous Huanglong Formation (C2hl) in the eastern part of the Sichuan Basin in China. The prediction results show that the coincidence rate between the results of 248 known exploration wells and the predicted results reaches 89.5%, and it has been found that the gas fields are basically located in the high value area of the hydrocarbon-bearing probability map. The application results show that the Bayesian network method can effectively predict the spatial distribution of oil and gas resources, thereby reducing exploration risks, optimizing exploration targets, and improving exploration benefits.
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Popov, Anatoly, Michael Dorrer, Alexandra Dorrer, Elizaveta Trishkina, and Nikita Romanov. "An approach to building a predictive model of the life cycle of information resources based on stochastic gert-networks and process mining technology." Informatization and communication 4 (November 2020): 107–12. http://dx.doi.org/10.34219/2078-8320-2020-11-4-107-112.
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The article proposes an approach to predicting the numerical parameters of the life cycle of information resources. The main task of this work is to develop a tool for numerical forecasting of the life cycle of information resources based on actual life cycle data in the form of resource history event logs. The forecast is carried out using the apparatus of stochastic GERT networks. The construction of the GERT model is performed using the Process Mining algorithmic apparatus and the ProM software framework. The object of the analysis was the data of the Scientific Electronic Library Online. The data is publicly available on the Kaggle.com website. To build a GERT network describing the life cycle model of an information resource, we used the methods of intellectual analysis of Process Mining processes implemented using the ProM Framework. In the course of the work, an analysis of the life cycle of information resources of the Scientific Electronic Online Library was carried out. The paper presents the process of extracting data used to model a GERT network using the ProM framework. The data obtained made it possible to restore the topology of the stochastic network and identify the laws of probability density distribution of the duration of the life cycle stages. On the basis of the constructed GERT-network, the law of distribution of the probability density of the duration of the life cycle of an information resource was described. The obtained result confirms the applicability of Process Mining technology to probabilistic analysis and forecasting of the life cycle of information resources.
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Anand, V., and K. Anuradha. "A Prolific Scheme for Load Balancing Relying on Task Completion Time." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 3 (June 1, 2018): 1741. http://dx.doi.org/10.11591/ijece.v8i3.pp1741-1746.
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In networks with lot of computation, load balancing gains increasing significance. To offer various resources, services and applications, the ultimate aim is to facilitate the sharing of services and resources on the network over the Internet. A key issue to be focused and addressed in networks with large amount of computation is load balancing. Load is the number of tasks‘t’ performed by a computation system. The load can be categorized as network load and CPU load. For an efficient load balancing strategy, the process of assigning the load between the nodes should enhance the resource utilization and minimize the computation time. This can be accomplished by a uniform distribution of load of to all the nodes. A Load balancing method should guarantee that, each node in a network performs almost equal amount of work pertinent to their capacity and availability of resources. Relying on task subtraction, this work has presented a pioneering algorithm termed as E-TS (Efficient-Task Subtraction). This algorithm has selected appropriate nodes for each task. The proposed algorithm has improved the utilization of computing resources and has preserved the neutrality in assigning the load to the nodes in the network.
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Yin, Fengjing, Xiang Zhao, Xin Zhang, Bin Ge, and Weidong Xiao. "Improving Accuracy and Scalability of Personal Recommendation Based on Bipartite Network Projection." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/823749.
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Bipartite network projection method has been recently employed for personal recommendation. It constructs a bipartite network between users and items. Treating user taste for items as resource in the network, we allocate the resource via links between user nodes and item nodes. However, the taste model employed by existing algorithms cannot differentiate “dislike” and “unrated” cases implied by user ratings. Moreover, the distribution of resource is solely based on node degrees, ignoring the different transfer rates of the links. To enhance the performance, this paper devises a negative-aware and rating-integrated algorithm on top of the baseline algorithm. It enriches the current user taste model to encompass “like,” “dislike,” and “unrated” information from users. Furthermore, in the resource distribution stage, we propose to initialize the resource allocation according to user ratings, which also determines the resource transfer rates on links afterward. Additionally, we also present a scalable implementation in the MapReduce framework by parallelizing the algorithm. Extensive experiments conducted on real data validate the effectiveness and efficiency of the proposed algorithms.
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Sallum, Eduardo, Nuno Pereira, Mário Alves, and Max Santos. "Improving Quality-Of-Service in LoRa Low-Power Wide-Area Networks through Optimized Radio Resource Management." Journal of Sensor and Actuator Networks 9, no. 1 (February 8, 2020): 10. http://dx.doi.org/10.3390/jsan9010010.
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Low Power Wide Area Networks (LPWAN) enable a growing number of Internet-of-Things (IoT) applications with large geographical coverage, low bit-rate, and long lifetime requirements. LoRa (Long Range) is a well-known LPWAN technology that uses a proprietary Chirp Spread Spectrum (CSS) physical layer, while the upper layers are defined by an open standard—LoRaWAN. In this paper, we propose a simple yet effective method to improve the Quality-of-Service (QoS) of LoRaWAN networks by fine-tuning specific radio parameters. Through a Mixed Integer Linear Programming (MILP) problem formulation, we find optimal settings for the Spreading Factor (SF) and Carrier Frequency (CF) radio parameters, considering the network traffic specifications as a whole, to improve the Data Extraction Rate (DER) and to reduce the packet collision rate and the energy consumption in LoRa networks. The effectiveness of the optimization procedure is demonstrated by simulations, using LoRaSim for different network scales. In relation to the traditional LoRa radio parameter assignment policies, our solution leads to an average increase of 6% in DER, and a number of collisions 13 times smaller. In comparison to networks with dynamic radio parameter assignment policies, there is an increase of 5%, 2.8%, and 2% of DER, and a number of collisions 11, 7.8 and 2.5 times smaller than equal-distribution, Tiurlikova’s (SOTA), and random distribution, respectively. Regarding the network energy consumption metric, the proposed optimization obtained an average consumption similar to Tiurlikova’s, and 2.8 times lower than the equal-distribution and random dynamic allocation policies. Furthermore, we approach the practical aspects of how to implement and integrate the optimization mechanism proposed in LoRa, guaranteeing backward compatibility with the standard protocol.
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Zhao, Hua, Xin Zhang, Caixia Wang, and Weiyu Yuan. "Classification Method of Aerobics Course Online Teaching Resources Based on Artificial Intelligence Technology." Wireless Communications and Mobile Computing 2022 (February 9, 2022): 1–10. http://dx.doi.org/10.1155/2022/8915705.
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In light of the current uneven distribution of aerobics course online resources, this paper presents research on the classification method of aerobics course online teaching resources based on artificial intelligence technology, constructs the display education resource management system based on artificial intelligence technology, realizes the classification of teaching information characteristics, and constructs the classification and evaluation algorithm of aerobiology course online resources. The online teaching resource classification of aerobics course achieves its design goal. Finally, the experiment shows that the artificial intelligence-based online teaching resource classification method for aerobics course is highly practicable and fully meets the research requirements.
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Bujnowski, Sławomir, Beata Marciniak, Tomasz Marciniak, and Zbigniew Lutowski. "The Method of Determining the Optimal Transmission Resources Distribution of ICT Networks Modelled by Graphs." Transport and Telecommunication Journal 22, no. 3 (June 1, 2021): 353–66. http://dx.doi.org/10.2478/ttj-2021-0028.
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Abstract The paper discusses the method of improvement of transmission properties of ICT networks by setting the correct distribution of transmission resources in order that it is possible to increase the resulting global probability of supporting the calls generated in the nodes included in the network. The method uses some parts of the graph theory. A minimum length path searching algorithm was used which made it possible to calculate the volume of movement transferred by individual edges of the graph describing the network. The coefficient of the distribution of transmission resources was determined and used to calculate the value of the resources in reference to a particular link, both in the case of equal and diverse movement generated in individual network nodes. A piece of software was developed which uses the results of applying the above-mentioned algorithm to prepare the files describing the analyzed structures in order to carry out simulation tests. The views and analyses are illustrated by examples, and the resulting effects of the influence of the introduction of the method of dividing network resources into transmission properties of a network modelled by graphs are shown in the charts included.
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Alakbarov, Rashid G. "Method for Effective Use of Cloudlet Network Resources." International Journal of Computer Network and Information Security 12, no. 5 (October 8, 2020): 46–55. http://dx.doi.org/10.5815/ijcnis.2020.05.04.
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The article addresses the issue of balanced placement of mobile software applications of mobile users in cloudlets deployed near base stations of Wireless Metropolitan Area Networks (WMAN), taking into account their technical capabilities. It is noted that the proposed model is more efficient in meeting the demand for computing and memory resources of mobile devices, eliminating network delays and using a reliable communication channel. At the same time, a minimum of cloudlet-based communication channels with a mobile user was suggested, reducing the network load and reliability of the communication channel when using multimedia software on mobile devices. The article reviews the balanced distribution of the tasks in the cloudlet network. If a user offloads the task to the nearest cloud and resolves it there, then the delays and energy consumption will be less. When the cloudlet is far from the mobile device, as the number of communication channels increases the delays are observed. Moreover, the article discusses the issue of selecting the cloudlets that meet some of the user requirements. Using the possible values that determine the importance of cloudlets (vacant resources in cloudlets, closeness of cloudlets to the user, high reliability, etc.), the conditions, according to which the user's application is offloaded to the certain cloudlet, are studied and a method is proposed.
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Hosseini, Seyed Amir, Mohsen Karami, Seyed Siavash Karimi Madahi, Farzad Razavi, and Ali Asghar Ghadimi. "Determining the Optimal Capacity and Place of DGs in Distribution Systems." Applied Mechanics and Materials 110-116 (October 2011): 5195–99. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.5195.
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Increasing application of distributed generation on distribution networks is the direct impact of development of technology and the energy disasters that the world is encountering. Using these resources in distribution network is one of the most influential solutions to reduce losses, improve voltage profile and improve power quality. To obtain these goals the resources capacity and the installation place are of a crucial importance. In this paper a new method is proposed to find the optimal and simultaneous place and capacity of these resources to reduce losses, improve voltage profile and reduce network harmonics. The proposed method is also capable of identifying the appropriate number of resources. The method is tested on actual power network of Zanjan Province, Iran and the simulation results are presented and discussed. Genetic algorithm is used to obtain the best answers.
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Shuang, Qing, Yongbo Yuan, Mingyuan Zhang, and Yisheng Liu. "A Cascade-Based Emergency Model for Water Distribution Network." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/827816.
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Water distribution network is important in the critical physical infrastructure systems. The paper studies the emergency resource strategies on water distribution network with the approach of complex network and cascading failures. The model of cascade-based emergency for water distribution network is built. The cascade-based model considers the network topology analysis and hydraulic analysis to provide a more realistic result. A load redistribution function with emergency recovery mechanisms is established. From the aspects of uniform distribution, node betweenness, and node pressure, six recovery strategies are given to reflect the network topology and the failure information, respectively. The recovery strategies are evaluated with the complex network indicators to describe the failure scale and failure velocity. The proposed method is applied by an illustrative example. The results showed that the recovery strategy considering the node pressure can enhance the network robustness effectively. Besides, this strategy can reduce the failure nodes and generate the least failure nodes per time.
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Ale, Laha, Ning Zhang, Scott A. King, and Jose Guardiola. "Spatio-temporal Bayesian Learning for Mobile Edge Computing Resource Planning in Smart Cities." ACM Transactions on Internet Technology 21, no. 3 (June 9, 2021): 1–21. http://dx.doi.org/10.1145/3448613.
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A smart city improves operational efficiency and comfort of living by harnessing techniques such as the Internet of Things (IoT) to collect and process data for decision-making. To better support smart cities, data collected by IoT should be stored and processed appropriately. However, IoT devices are often task-specialized and resource-constrained, and thus, they heavily rely on online resources in terms of computing and storage to accomplish various tasks. Moreover, these cloud-based solutions often centralize the resources and are far away from the end IoTs and cannot respond to users in time due to network congestion when massive numbers of tasks offload through the core network. Therefore, by decentralizing resources spatially close to IoT devices, mobile edge computing (MEC) can reduce latency and improve service quality for a smart city, where service requests can be fulfilled in proximity. As the service demands exhibit spatial-temporal features, deploying MEC servers at optimal locations and allocating MEC resources play an essential role in efficiently meeting service requirements in a smart city. In this regard, it is essential to learn the distribution of resource demands in time and space. In this work, we first propose a spatio-temporal Bayesian hierarchical learning approach to learn and predict the distribution of MEC resource demand over space and time to facilitate MEC deployment and resource management. Second, the proposed model is trained and tested on real-world data, and the results demonstrate that the proposed method can achieve very high accuracy. Third, we demonstrate an application of the proposed method by simulating task offloading. Finally, the simulated results show that resources allocated based upon our models’ predictions are exploited more efficiently than the resources are equally divided into all servers in unobserved areas.
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Alsaffar, Aymen Abdullah, Hung Phuoc Pham, Choong-Seon Hong, Eui-Nam Huh, and Mohammad Aazam. "An Architecture of IoT Service Delegation and Resource Allocation Based on Collaboration between Fog and Cloud Computing." Mobile Information Systems 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/6123234.
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Despite the wide utilization of cloud computing (e.g., services, applications, and resources), some of the services, applications, and smart devices are not able to fully benefit from this attractive cloud computing paradigm due to the following issues: (1) smart devices might be lacking in their capacity (e.g., processing, memory, storage, battery, and resource allocation), (2) they might be lacking in their network resources, and (3) the high network latency to centralized server in cloud might not be efficient for delay-sensitive application, services, and resource allocations requests. Fog computing is promising paradigm that can extend cloud resources to edge of network, solving the abovementioned issue. As a result, in this work, we propose an architecture of IoT service delegation and resource allocation based on collaboration between fog and cloud computing. We provide new algorithm that is decision rules of linearized decision tree based on three conditions (services size, completion time, and VMs capacity) for managing and delegating user request in order to balance workload. Moreover, we propose algorithm to allocate resources to meet service level agreement (SLA) and quality of services (QoS) as well as optimizing big data distribution in fog and cloud computing. Our simulation result shows that our proposed approach can efficiently balance workload, improve resource allocation efficiently, optimize big data distribution, and show better performance than other existing methods.
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Hong, Sothea, Pierre-Olivier Malaterre, Gilles Belaud, and Cyril Dejean. "Optimization of water distribution for open-channel irrigation networks." Journal of Hydroinformatics 16, no. 2 (August 5, 2013): 341–53. http://dx.doi.org/10.2166/hydro.2013.194.
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Water distribution for open-channel irrigation networks is more and more complex due to increasing constraints on water resources and changing demand patterns, whereas the performance of such systems is expected to increase. In this regard, an optimization approach is developed in order to schedule a fair scenario of water distribution among different users, where water demand is formulated in term of start time, duration and flow rate. This study investigates how to optimize the water distribution over a finite scheduling horizon while respecting the constraints linked to the system. The optimization approach forces the scheduled start time and the volume to be closer to the demanded ones, to minimize water losses and to reduce manpower. The constraints take into account the flow routing processes, the physical infrastructure, the available water resource, and the gate keeper timetable. The numerical resolution is done by using an optimization software IBM-Ilog Cplex. The method is then illustrated with the scheduling of off-take withdrawals for a typical traditional open-channel network: a lateral canal of the Gignac canal, in southern France.
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Ye, Siyu, Yi Zhang, Wen Yao, Quan Chen, and Xiaoqian Chen. "An Effective Surrogate Ensemble Modeling Method for Satellite Coverage Traffic Volume Prediction." Applied Sciences 9, no. 18 (September 5, 2019): 3689. http://dx.doi.org/10.3390/app9183689.
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The satellite constellation network is a powerful tool to provide ground traffic business services for continuous global coverage. For the resource-limited satellite network, it is necessary to predict satellite coverage traffic volume (SCTV) in advance to properly allocate onboard resources for better task fulfillment. Traditionally, a global SCTV distribution data table is first statistically constructed on the ground according to historical data and uploaded to the satellite. Then SCTV is predicted onboard by a data table lookup. However, the cost of the large data transmission and storage is expensive and prohibitive for satellites. To solve these problems, this paper proposes to distill the data into a surrogate model to be uploaded to the satellite, which can both save the valuable communication link resource and improve the SCTV prediction accuracy compared to the table lookup. An effective surrogate ensemble modeling method is proposed in this paper for better prediction. First, according to prior geographical knowledge of the SCTV distribution, the global earth surface domain is split into multiple sub-domains. Second, on each sub-domain, multiple candidate surrogates are built. To fully exploit these surrogates and combine them into a more accurate ensemble, a partial weighted aggregation method (PWTA) is developed. For each sub-domain, PWTA adaptively selects the candidate surrogates with higher accuracy as the contributing models, based on which the ultimate ensemble is constructed for each sub-domain SCTV prediction. The proposed method is demonstrated and testified with an air traffic SCTV engineering problem. The results demonstrate the effectiveness of PWTA regarding good local and global prediction accuracy and modeling robustness.