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Journal articles on the topic 'Heterogenous Networks'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Kubde, Vidya Sachin, and Sudhir D. Sawarkar. "Exploring Multipath TCP Schedulers in Heterogeneous Networks." International Journal of Information Communication Technologies and Human Development 14, no. 1 (January 2022): 1–11. http://dx.doi.org/10.4018/ijicthd.295857.

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Multipath Transmission Control Protocol (MPTCP) is a transport layer protocol, which transmits TCP segments on more than one path, in multihomed devices. It was designed with the aim of Bandwidth aggregation and redundant connections. Currently, multihomed devices have wireless interfaces of heterogeneous nature. MPTCP is not able to give its optimal performance in heterogeneous networks. This paper presents an experimental performance study of four different schedulers, namely Roundrobin, Default, Blest, and Redundant. Our testbed comprises Ethernet, LTE, and Wifi networks to connect multihomed devices. We have compared the scheduler performance in terms of Throughput , Download time and path utilization rate in homogenous and heterogenous scenarios . Results showed that Round robin provides optimal throughput in homogenous networks and also performs bandwidth aggregation by utilizing both the paths but fails to perform in heterogenous networks. Blest, provides best throughput among the four schedulers but prefers fast path only.

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Naylor, T., A. Allan, and I. A. Steele. "Heterogenous telescope networks: An introduction." Astronomische Nachrichten 327, no. 8 (September 2006): 741–43. http://dx.doi.org/10.1002/asna.200610624.

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3

DURRESI, ARJAN, VAMSI PARUCHURI, and RAJ JAIN. "GEOMETRIC BROADCAST PROTOCOL FOR HETEROGENEOUS SENSOR NETWORKS." Journal of Interconnection Networks 06, no. 03 (September 2005): 193–207. http://dx.doi.org/10.1142/s0219265905001381.

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We present Geometric Broadcast for Heterogeneous Sensor Networks (GBS), a novel broadcasting protocol for heterogeneous wireless sensor and actor networks. While broadcasting is a very energy expensive protocol, it is also widely used as a building block for a variety of other network layer protocols. Therefore, reducing the energy consumption by optimizing broadcasting is a major improvement in heterogenous sensor networking. GBS is a distributed algorithm where nodes make local decisions on whether to transmit based on a geometric approach. GBS does not need any neighborhood information and imposes very low communication overhead. GBS is scalable to the change in network size, node type, node density and topology. Furthermore it accommodates seamlessly such network changes, including the presence of actors in heterogeneous sensor networks. Indeed, GBS takes advantage of actor nodes, and uses their resources when possible, thus reducing the energy consumption by sensor nodes. Through simulation evaluations, we show that GBS is very scalable and its performance is improved by the presence of actors. At the best of our knowledge, GBS is the first broadcast protocol designed specifically for heterogeneous sensor and actor networks.

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Hauge, Mariann, Lars Landmark, Piotr Łubkowski, Marek Amanowicz, and Krzysztof Maślanka. "Selected Issues of QoS Provision in Heterogenous Military Networks." International Journal of Electronics and Telecommunications 60, no. 1 (March 1, 2014): 1–7. http://dx.doi.org/10.2478/eletel-2014-0001.

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Abstract Tactical ad-hoc networks are evolving today towards complex heterogeneous networks in terms of architecture, protocols and security. Due to the difference in network resources and reliability, end-to-end quality of service provisioning becomes very challenging. If we also take into account communication issues such as unpredictable connectivity, preferential forwarding for special traffic classes, intermittency due to node or communication link failure, the problem is further aggravated. In this article, we examine the major challenges that must be solved in order to provide efficient QoS provisioning in the heterogeneous network. Finally we describe QoS-aware mechanisms for inter-domain and intra-domain heterogeneous networks, also including real-time services provision in highly mobile environments.

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Hardjawana, Wibowo, and Branka Vucetic. "Discrete Power Control in Heterogenous Networks." Makara Journal of Technology 20, no. 1 (April 26, 2016): 31. http://dx.doi.org/10.7454/mst.v20i1.3053.

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Hardjawana, Wibowo, and Branka Vucetic. "Discrete Power Control in Heterogenous Networks." Makara Journal of Technology 20, no. 1 (April 26, 2016): 31. http://dx.doi.org/10.7454/mst.v20i1.3121.

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7

Ben-Zion, Yossi, Yahel Cohen, and Nadav M. Shnerb. "Modeling epidemics dynamics on heterogenous networks." Journal of Theoretical Biology 264, no. 2 (May 2010): 197–204. http://dx.doi.org/10.1016/j.jtbi.2010.01.029.

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8

WANG, JIAN-WEI. "ROBUSTNESS OF HETEROGENOUS NETWORKS WITH MITIGATION STRATEGY AGAINST CASCADING FAILURES." Modern Physics Letters B 26, no. 14 (May 14, 2012): 1250087. http://dx.doi.org/10.1142/s021798491250087x.

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The network disaster induced by cascading failures has traumatized modern societies. How to protect these networks and improve their robustness against cascading failures has become the key issue. To this end, we construct a cascading model and propose an efficient mitigation strategy against cascading failures. In many real-world networks, there exist some heterogeneous nodes, for example the hosts and the routers in the Internet, and the users and the supply-grid stations in the power grid. In previous studies, however, less cascading models were constructed to describe such fact. Including two types of nodes in a network, we present a new cascading model. We introduce a new mitigation strategy with dynamically adjusting the load and demonstrate its efficiency on the Barabási–Albert (BA) network and the power grid as well as the Internet. We show that with small changes in dynamically adjusting the load the robustness of these networks can be improved dramatically. Our results are useful not only for protecting networks from the local perspective, but also for significantly improving the robustness of the existing infrastructure networks.

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Khan, Shafiullah, Muhammad Muneer Umar, Chunhua Jin, Shaozhang Xiao, Zeeshan Iqbal, and Noha Alnazzawi. "Game-Theory-Based Multimode Routing Protocol for Internet of Things." Electronics 11, no. 24 (December 12, 2022): 4134. http://dx.doi.org/10.3390/electronics11244134.

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Various routing protocols have been proposed for ad hoc networks such as the Internet of Things (IoT). Most of the routing protocols introduced for IoT are specific to applications and networks. In the current literature, it is essential to configure all the network nodes with a single proposed protocol. Moreover, it is also possible for a single IoT network to consist of different kinds of nodes. Two or more IoT networks can also be connected to create a bigger heterogeneous network. Such networks may need various routing protocols with some gateway nodes installed. The role of gateway nodes should not be limited to the interconnection of different nodes. In this paper, a multi-mode hybrid routing mechanism is proposed that can be installed on all or a limited number of nodes in a heterogenous IoT network. The nodes configured with the proposed protocols are termed smart nodes. These nodes can be used to connect multiple IoT networks into one. Furthermore, a game-theory-based model is proposed that is used for intercommunication among the smart nodes to gain optimal efficiency. Various performance matrices are assessed under different network scenarios. The simulation results show that the proposed mechanism outperforms in broader heterogeneous IoT networks with diverse nodes.

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Li, Shudong, Zhongtian Jia, Aiping Li, Lixiang Li, Xinran Liu, and Yixian Yang. "Cascading Dynamics of Heterogenous Scale-Free Networks with Recovery Mechanism." Abstract and Applied Analysis 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/453689.

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In network security, how to use efficient response methods against cascading failures of complex networks is very important. In this paper, concerned with the highest-load attack (HL) and random attack (RA) on one edge, we define five kinds of weighting strategies to assign the external resources for recovering the edges from cascading failures in heterogeneous scale-free (SF) networks. The influence of external resources, the tolerance parameter, and the different weighting strategies on SF networks against cascading failures is investigated carefully. We find that, under HL attack, the fourth kind of weighting method can more effectively improve the integral robustness of SF networks, simultaneously control the spreading velocity, and control the outburst of cascading failures in SF networks than other methods. Moreover, the third method is optimal if we only knew the local structure of SF networks and the uniform assignment is the worst. The simulations of the real-world autonomous system in, Internet have also supported our findings. The results are useful for using efficient response strategy against the emergent accidents and controlling the cascading failures in the real-world networks.

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Alawi, Mahmoud, Raed Alsaqour, Maha Abdelhaq, Reem Alkanhel, Baraa Sharef, Elankovan Sundararajan, and Mahamod Ismail. "Adaptive QoS-Aware Multi-Metrics Gateway Selection Scheme for Heterogenous Vehicular Network." Systems 10, no. 5 (September 7, 2022): 142. http://dx.doi.org/10.3390/systems10050142.

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A heterogeneous vehicular network (HetVNET) is a promising network architecture that combines multiple network technologies such as IEEE 802.11p, dedicated short-range communication (DSRC), and third/fourth generation cellular networks (3G/4G). In this network area, vehicle users can use wireless fidelity access points (Wi-Fi APs) to offload 4G long-term evolution (4G-LTE) networks. However, when using Wi-Fi APs, the vehicles must organize themselves and select an appropriate mobile gateway (MGW) to communicate to the cellular infrastructure. Researchers are facing the problem of selecting the best MGW vehicle to aggregate vehicle traffic and reduce LTE load in HetVNETs when the Wi-Fi APs are unavailable for offloading. The selection process utilizes extra network overhead and complexity due to the frequent formation of clusters in this highly dynamic environment. In this study, we proposed a non-cluster adaptive QoS-aware gateway selection (AQAGS) scheme that autonomously picks a limited number of vehicles to act as LTE gateways based on the LTE network’s load status and vehicular ad hoc network (VANET) application’s QoS requirements. The present AQAGS scheme focuses on highway scenarios. The proposed scheme was evaluated using simulation of Urban mobility (SUMO) and network simulator version 2 (NS2) simulators and benchmarked with the clustered and non-clustered schemes. A comparison was made based on the end-to-end delay, throughput, control packet overhead (CPO), and packet delivery ratio (PDR) performance metrics over Voice over Internet Protocol (VoIP) and File Transfer Protocol (FTP) applications. Using VoIP, the AQAGS scheme achieved a 26.7% higher PDR compared with the other schemes.

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Geerts, Robbe, Frédéric Vandermoere, and Stijn Oosterlynck. "The Functionality of Dissimilarity: Pro-Environmental Behavior through Heterogenous Networks." Social Sciences 9, no. 12 (December 1, 2020): 221. http://dx.doi.org/10.3390/socsci9120221.

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This study explores whether social interaction with dissimilar others can lead to pro-environmental behavior. Dissimilar others are people who differ from the person in question (e.g., in terms of lifestyle or culture). While most research focuses on homogenous social networks (e.g., spatial communities), we explore the potential of network heterophily. Specifically, using data (n = 1370) from the Flemish Survey on Sociocultural Shifts, we examine the relationship between network heterophily and pro-environmental behavior (i.e., shopping decisions and curtailment behavior). Building on Granovetter’s study on ‘the strength of weak ties’, we emphasize the importance of social ties that provide novel information and social expectations. Through interaction with dissimilar others, people may create a heterogeneous network in which a diversity of information and social expectations with regard to pro-environmental behavior circulates. We expect that network heterophily may foster pro-environmental behavior. Our findings indicate that pro-environmental behavior may indeed be positively related to interaction with dissimilar others, partly because people with many dissimilar ties know more about environmental problems and are more concerned about them. This study therefore shows that network heterophily promotes pro-environmental behavior. The paper concludes with a discussion of the functionality of dissimilarity and some avenues for future research.

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13

Abuhaija, Belal. "System Selection Algorithm for Heterogenous Radio Access Networks." International Journal of Computer Applications 88, no. 13 (February 14, 2014): 35–40. http://dx.doi.org/10.5120/15416-4065.

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Sun, Yaohua, and Mugen Peng. "Recent Advances of Heterogenous RadioAccess Networks: A Survey." Journal of Mobile Multimedia 14, no. 4 (2018): 345–66. http://dx.doi.org/10.13052/jmm1550-4646.1441.

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15

Al-Saqabi, Khaled, Syed Sarwar, and Kassem Saleh. "Distributed gang scheduling in networks of heterogenous workstations." Computer Communications 20, no. 5 (July 1997): 338–48. http://dx.doi.org/10.1016/s0140-3664(97)00020-0.

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Kasraoui, M., A. Cabani, and H. Chafouk. "Secure collaborative system in heterogenous wireless sensor networks." Journal of Applied Research and Technology 13, no. 2 (April 2015): 342–50. http://dx.doi.org/10.1016/j.jart.2015.06.016.

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17

Andrabi, Umer Mukhtar, and Mikhail S. Stepanov. "Collective servicing of heterogenous traffic streams over 3GPP LTE network and application of access control." T-Comm 16, no. 3 (2022): 43–49. http://dx.doi.org/10.36724/2072-8735-2022-16-3-43-49.

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Due to the progressions in the cellular technologies in recent times, communicating networks have seen vast expansion in the volumes and multiplicities of the data transmitted over the enhanced smart network especially IoT. The regulation and organization of such enormous amounts of data is posing substantial challenges across the various network industries. Because majority of data traffic transferred over such complex networks is comprised of "Big Data" That is continuously growing and evolving. 3GPP have acknowledged such scenarios and have given several recommendations and procedures to manage resources in such situations. But regrettably there are no concrete explanations and techniques on how these resources should be distributed in heterogenous networks. The mathematical modeling that considers the characteristics of traffic flows originating and accepting for servicing is deemed as one of the critical answers to such problems. To address this issue, we have designed a model of resource allocation and sharing strategy for conjoint servicing of real time video traffic referred as "Heavy traffic" of surveillance cameras and low-quality video traffic, referred as "Light traffic" which are transmitted as files over LTE cell facilities in a surveillance operator system. In the model, the access control is incorporated to create the conditions for differentiated servicing of heterogenous traffic incoming sessions. The mathematical model can be utilized to study reservation-based resource allocation scenarios over a shared heterogenous network.

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A. P, Kavya, and D. J. Ravi. "A Distributed Clustering Based Energy Management Scheme for Heterogenous Wireless Sensor Network." Journal of Communication Engineering and Its Innovations 9, no. 1 (January 23, 2023): 1–13. http://dx.doi.org/10.46610/jocei.2023.v09i01.001.

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The Internet of Things (IoT) is an emerging paradigm that offers a wide array of benefits for real-world applications. An IoT system is supported by a network of heterogeneous sensor nodes that collect information about the environment over time. The non-rechargeable batteries and energy constraints limit the network's lifespan. For this reason, controlling energy dissipation is one of the most important considerations when designing communication protocols for sensor networks. The clustering scheme is one of the most efficient ways to help networks be more energy-efficient. However, the majorities of existing protocols do not handle energy distribution among heterogeneous sensor nodes well and are inappropriate. The purpose of this paper is to emphasize cluster head selection criteria and to propose an energy management clustering mechanism that takes heterogeneity into account. A dense deployment of heterogeneous multi-level nodes is considered in the proposed scheme to improve the nodes' stability and power efficiency. The threshold probability for selecting optimal CH nodes is determined by an energy-balanced weighted parameter. The proposed scheme is implemented on a numerical computing tool MatLab. In terms of alive nodes, dead nodes, packets sent to the base station, and processing time, the simulation provides efficient results. When compared to similar existing approaches, the proposed scheme was more successful in terms of network lifetime, stability, delay, and packet delivery.

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Xiang, Linying, Jonathan J. H. Zhu, Fei Chen, and Guanrong Chen. "Controllability of Weighted and Directed Networks with Nonidentical Node Dynamics." Mathematical Problems in Engineering 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/405034.

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The concept of controllability from control theory is applied to weighted and directed networks with heterogenous linear or linearized node dynamics subject to exogenous inputs, where the nodes are grouped into leaders and followers. Under this framework, the controllability of the controlled network can be decomposed into two independent problems: the controllability of the isolated leader subsystem and the controllability of the extended follower subsystem. Some necessary and/or sufficient conditions for the controllability of the leader-follower network are derived based on matrix theory and graph theory. In particular, it is shown that a single-leader network is controllable if it is a directed path or cycle, but it is uncontrollable for a complete digraph or a star digraph in general. Furthermore, some approaches to improving the controllability of a heterogenous network are presented. Some simulation examples are given for illustration and verification.

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Ogbodo, Emmanuel Utochukwu, Adnan M. Abu-Mahfouz, and Anish M. Kurien. "Enabling LPWANs for Coexistence and Diverse IoT Applications in Smart Cities Using Lightweight Heterogenous Multihomed Network Model." Journal of Sensor and Actuator Networks 11, no. 4 (December 19, 2022): 87. http://dx.doi.org/10.3390/jsan11040087.

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Smart cities have been envisioned to provide smartness in managing internet of things (IoT) application domains, such as transport and mobility, health care, natural resources, electricity and energy, homes and buildings, commerce and retail, society and workplace, industry, agriculture, and the environment. The growth trajectory in usage of these IoT domains has led to a heterogeneous dense network in a smart city environment. The heterogeneous dense network in smart cities has led to challenges, such as difficulties in the management of LPWAN coexistence, interference, spectrum insufficiency, QoS, and scalability issues. The existing LPWAN technologies cannot support the heterogeneous dense network challenges in smart cities. Further, it cannot support diverse IoT, including medium- to high-bandwidth applications, due to the power, complexity, and resource constraints of the LPWAN devices. Hence, this paper addresses high data rate IoT applications and heterogeneous dense networks. This paper proposes a lightweight heterogenous multihomed network (LHM-N) model for diverse smart city applications that will address dense heterogeneity network challenges in a smart city. The work aims to advocate and integrate a manageable license-free LPWAN that will coexist with 5G private and public cellular networks in the LHM-N model. This will help to provide a cost-effective solution model in a heterogeneous dense smart city environment. Further, a secured lightweight energy-efficient packet-size forwarding engine (PSFE) algorithm is presented using the discrete event simulation (DES) methodological approach in MATLAB for complexity evaluation. In addition, a 5G reduced capability (RedCap) IoT device is integrated into the (LHM-N) model to support smart city. Finally, the results show that the LHM-N model outperforms the conventional quadrature amplitude modulation (QAM) protocol scheme in terms of error rate, latency, and data throughput with reduced energy costs for medium- to high-bandwidth industrial IoT applications. This validates the suitability of the LHM-N model for high data rate IoT applications.

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Wang, Wei, Mengjun Zhang, Li Zhang, and Qiong Bai. "Imbalanced Data Classification for Multi-Source Heterogenous Sensor Networks." IEEE Access 8 (2020): 27406–13. http://dx.doi.org/10.1109/access.2020.2966324.

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Zhong, Wei, Bing Fang, and Zuping Qian. "Game Theoretic Resource Allocation for D2D MIMO Heterogenous Networks." Wireless Personal Communications 84, no. 1 (May 12, 2015): 273–85. http://dx.doi.org/10.1007/s11277-015-2607-8.

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Wang, Yunjia, Jiantao Yuan, Guanding Yu, Qimei Chen, and Rui Yin. "Minority Game for Distributed User Association in Unlicensed Heterogenous Networks." IEEE Transactions on Wireless Communications 19, no. 6 (June 2020): 4220–33. http://dx.doi.org/10.1109/twc.2020.2981328.

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Lai, Shouwen, Binoy Ravindran, and Hyeonjoong Cho. "Heterogenous Quorum-Based Wake-Up Scheduling in Wireless Sensor Networks." IEEE Transactions on Computers 59, no. 11 (November 2010): 1562–75. http://dx.doi.org/10.1109/tc.2010.20.

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SATO, K., R. HASHIMOTO, M. YOSHINO, R. SHINKUMA, and T. TAKAHASHI. "Incentive Mechanism for P2P Content Sharing over Heterogenous Access Networks." IEICE Transactions on Communications E91-B, no. 12 (December 1, 2008): 3821–30. http://dx.doi.org/10.1093/ietcom/e91-b.12.3821.

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Wang, Jia-zeng, Zeng-rong Liu, and Jianhua Xu. "Epidemic spreading on uncorrelated heterogenous networks with non-uniform transmission." Physica A: Statistical Mechanics and its Applications 382, no. 2 (August 2007): 715–21. http://dx.doi.org/10.1016/j.physa.2007.04.034.

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Singh, Parvinder, and Rajeshwar Singh. "Energy-Efficient QoS-Aware Intelligent Hybrid Clustered Routing Protocol for Wireless Sensor Networks." Journal of Sensors 2019 (December 12, 2019): 1–12. http://dx.doi.org/10.1155/2019/8691878.

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A wireless sensor network consists of numerous low-power microsensor devices that can be deployed in a geographical area for remote sensing, surveillance, control, and monitoring applications. The advancements of wireless devices in terms of user-friendly interface, size, and deployment cost have given rise to many smart applications of wireless sensor networks (WSNs). However, certain issues like energy efficiency, long lifetime, and communication reliability restrict their large scale utilization. In WSNs, the cluster-based routing protocols assist nodes to collect, aggregate, and forward sensed data from event regions towards the sink node through minimum cost links. A clustering method helps to improve data transmission efficiency by dividing the sensor nodes into small groups. However, improper cluster head (CH) selection may affect the network lifetime, average network energy, and other quality of service (QoS) parameters. In this paper, a multiobjective clustering strategy is proposed to optimize the energy consumption, network lifetime, network throughput, and network delay. A fitness function has been formulated for heterogenous and homogenous wireless sensor networks. This fitness function is utilized to select an optimum CH for energy minimization and load balancing of cluster heads. A new hybrid clustered routing protocol is proposed based on fitness function. The simulation results conclude that the proposed protocol achieves better efficiency in increasing the network lifetime by 63%, 26%, and 10% compared with three well-known heterogeneous protocols: DEEC, EDDEEC, and ATEER, respectively. The proposed strategy also attains better network stability than a homogenous LEACH protocol.

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Sun, Donglai, Yang Liu, Jianhua Li, and Yue Wu. "Collaborative Opportunistic Scheduling in Heterogeneous Networks: A Distributed Approach." Mathematical Problems in Engineering 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/414689.

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We consider a collaborative opportunistic scheduling problem in a decentralized network with heterogeneous users. While most related researches focus on solutions for optimizing decentralized systems’ total performance, we proceed in another direction. Two problems are specifically investigated. (1) With heterogenous users having personal demands, is it possible to have it met by designing distributed opportunistic policies? (2) With a decentralized mechanism, how can we prevent selfish behaviors and enforce collaboration? In our research, we first introduce a multiuser network model along with a scheduling problem constrained by individual throughput requirement at each user’s side. An iterative algorithm is then proposed to characterize a solution for the scheduling problem, based on which collaborative opportunistic scheduling scheme is enabled. Properties of the algorithm, including convergence, will be discussed. Furthermore in order to keep the users staying with the collaboration state, an additional punishment strategy is designed. Therefore selfish deviation can be detected and disciplined so that collaboration is enforced. We demonstrate our main findings with both analysis and simulations.

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Cwalina, Krzysztof K., Piotr Rajchowski, Alicja Olejniczak, Olga Błaszkiewicz, and Robert Burczyk. "Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning." Sensors 21, no. 22 (November 19, 2021): 7716. http://dx.doi.org/10.3390/s21227716.

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Following the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides a significant gain (almost 40%) with 10.7% compared to the linear model with the lowest RMSE (Root Mean Squared Error) 17.01%. The solution can be adopted as a part of the data allocation algorithm implemented in the telemetry devices equipped with the 4G radio interface, or, after the adjustment, the NB-IoT (Narrowband Internet of Things), to maximize the reliability of the services in harsh indoor or urban environments. Presented results also prove the existence of the inverse proportional dependence between the number of hidden layers and the number of historical samples in terms of the obtained RMSE. The increase of the historical data memory allows using models with fewer hidden layers while maintaining a comparable RMSE value for each scenario, which reduces the total computational cost.

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Linn, Nyi Nyi, Kai Liu, and Qiang Gao. "A Contention-Free Cooperative MAC Protocol for Eliminating Heterogenous Collisions in Vehicular Ad Hoc Networks." Sensors 23, no. 2 (January 16, 2023): 1033. http://dx.doi.org/10.3390/s23021033.

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In vehicular ad hoc networks (VANETs), efficient data dissemination to a specified number of vehicles with minimum collisions and limited access delay is critical for accident prevention in road safety. However, packet collisions have a significant impact on access delay, and they may lead to unanticipated link failure when a range of diversified collisions are combined due to complex traffic conditions and rapid changes in network topology. In this paper, we propose a distributed contention-free cooperative medium access control (CFC-MAC) protocol to reduce heterogenous collisions and unintended access delay in stochastic traffic scenarios. Firstly, we develop a cooperative communication system model and cooperative forwarding mechanism to explore the optimum road path between the source and destination by identifying the potential cooperative vehicles. Secondly, we propose a vectorized trajectory estimation mechanism to suppress merging collisions by identifying the relative velocity of vehicles with different speeds in a specific time interval. Based on the case study, typical heterogeneous collisions and aggregated heterogeneous collisions at dissociated positions and associated positions are investigated. In both cases, we propose the corresponding collision-resolving mechanisms by methodically recapturing the colliding time slot or acquiring the available free time slots after identifying the access vehicles and comparing the received signal strengths. Performance analysis for collision probability and access delay is conducted. Finally, the simulation results show that the proposed protocol can achieve deterministic access delay and a minimal collision rate, substantially outperforming the existing solutions.

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Risi, Sebastian, and Kenneth O. Stanley. "Deep Innovation Protection: Confronting the Credit Assignment Problem in Training Heterogeneous Neural Architectures." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 14 (May 18, 2021): 12391–99. http://dx.doi.org/10.1609/aaai.v35i14.17470.

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Deep reinforcement learning approaches have shown impressive results in a variety of different domains, however, more complex heterogeneous architectures such as world models require the different neural components to be trained separately instead of end-to-end. While a simple genetic algorithm recently showed end-to-end training is possible, it failed to solve a more complex 3D task. This paper presents a method called Deep Innovation Protection (DIP) that addresses the credit assignment problem in training complex heterogenous neural network models end-to-end for such environments. The main idea behind the approach is to employ multiobjective optimization to temporally reduce the selection pressure on specific components in multi-component network, allowing other components to adapt. We investigate the emergent representations of these evolved networks, which learn to predict properties important for the survival of the agent, without the need for a specific forward-prediction loss.

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Boldrini, Chiara, Marco Conti, and Andrea Passarella. "Performance modelling of opportunistic forwarding under heterogenous mobility." Computer Communications 48 (July 2014): 56–70. http://dx.doi.org/10.1016/j.comcom.2014.03.028.

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Bharath, B. N., K. G. Nagananda, and H. Vincent Poor. "A Learning-Based Approach to Caching in Heterogenous Small Cell Networks." IEEE Transactions on Communications 64, no. 4 (April 2016): 1674–86. http://dx.doi.org/10.1109/tcomm.2016.2536728.

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Li, Shilin, Yunzheng Tao, Xiaoqi Qin, Long Liu, Zhi Zhang, and Ping Zhang. "Energy-Aware Mobile Edge Computation Offloading for IoT Over Heterogenous Networks." IEEE Access 7 (2019): 13092–105. http://dx.doi.org/10.1109/access.2019.2893118.

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Zhang, Xing, and David J. Sanderson. "Scale up of two-dimensional conductivity tensor for heterogenous fracture networks." Engineering Geology 53, no. 1 (May 1999): 83–99. http://dx.doi.org/10.1016/s0013-7952(98)00082-9.

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Battaglia, Filippo, and Lucia Lo Bello. "A novel JXTA-based architecture for implementing heterogenous Networks of Things." Computer Communications 116 (January 2018): 35–62. http://dx.doi.org/10.1016/j.comcom.2017.11.002.

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Wang, Yingying, Jianfeng Liu, Yufeng Li, Yu Yang, and Keshen Li. "Systematic Characterization of Heterogeneity Caused by Neuroinflammation in Alzheimer’s Disease Based on Integrative Network Analysis." Current Alzheimer Research 18, no. 13 (November 29, 2021): 1041–56. http://dx.doi.org/10.2174/1567205019666211216104449.

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Background: Alzheimer's disease (AD) is the most common cause of dementia. As a heterogenous disease, there are several clinically and pathobiological defined subtypes with different molecular signatures. Neuroinflammation contributed to AD pathogenesis, however, the roles it played in the heterogeneity of AD was unclear. Objective: We aimed to illustrate the roles neuroinflammation played in the heterogeneity of AD. Method: An integrative network analysis based on transcriptomics, miRNOmics, and proteomics was performed to illustrate the heterogeneous characters of AD. Combined-functional-networks and hypothesis-network were constructed and analyzed to explore the roles neuroinflammation played in AD heterogeneity. Results: Astrocytes, microglia, ‘M2 macrophage-Neuron’, and ‘Microglia- Neuron’ were shown to be enriched in neuroinflammation related functional terms in a cell- and spatial-specific way. The microglia and neurons could interact with each other in three different ways including indirect interactions via intermediate cells, indirect interactions via soluble factors, and direct interactions established localized and functionally distinct signaling, all of which were used to control different biological processes. The combined network analyses exhibited the key roles neuroinflammation plays in the 'AD hypothesis network’. Conclusion : The AD heterogeneity may be caused by the heterogeneous cells involved in neuroinflammation and the crosstalks between spatial-specific molecular signatures.

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Wang, Chuncheng. "AI-Based Heterogenous Large-Scale English Translation Strategy." Mobile Information Systems 2022 (February 9, 2022): 1–10. http://dx.doi.org/10.1155/2022/8344814.

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English has become one of the most widely used languages in the world. If there is no good translation mechanism for such a widely used language, it will bring trouble to both study and life. At present, the world’s major platforms are committed to the study of English translation strategies. There are translation platforms from different regions and different translation mechanisms. These translation data from different translation platforms have the characteristics of large-scale, multisource, heterogeneity, high dimensions, and poor quality. However, such inconsistent translation data will increase the translation difficulty and translation time. Therefore, it is necessary to improve the quality of translation data to achieve a better translation effect. How to provide a large-scale and efficient translation strategy needs to integrate the translation strategies of various platforms to perform heterogeneous translation data cleaning and fusion based on machine learning. At first, this paper represents the multisource, heterogeneous translation data model as tree-augmented naive Bayes networks (TANs) and naturally captures the relationship between the datasets through the learning of TANs structure and the probability distribution of input attributes and tuples, using data probability value to complete the classification of translation data cleaning. Then, a multisource, heterogeneous translation data fusion model based on recurrent neural network (RNN) is constructed, and RNN is used to control the node data of hidden layer to enhance the fault-tolerant ability in the fusion process and complete the construction of fusion model. Finally, experimental results show that TANs-based translation data cleaning method can effectively improve the cleaning rate with an average improvement of approximately 10% and cleaning time with an average reduce about 5%. In addition, RNN-based multisource translation data fusion method improves the shortcomings of the traditional fusion model and improves the practicability of the fusion model in terms of root mean square error (RMSE), mean absolute percentage error (MAPE), fusion time, and integrity.

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Niederberger, C., and M. Gross. "Hierarchical and Heterogenous Reactive Agents for Real-Time Applications." Computer Graphics Forum 22, no. 3 (September 2003): 323–31. http://dx.doi.org/10.1111/1467-8659.00679.

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Komorowski, Marlen, Ruxandra Lupu, Sara Pepper, and Justin Lewis. "Joining the Dots—Understanding the Value Generation of Creative Networks for Sustainability in Local Creative Ecosystems." Sustainability 13, no. 22 (November 9, 2021): 12352. http://dx.doi.org/10.3390/su132212352.

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In recent years, the ecological shift from an economically driven model of arts and culture to that of an ecosystem in the creative industries determined the emergence of a range of new bottom-up, place-based networks herewith referred to as “creative networks”. This article explores how these networks can generate sustainability for local creative ecosystems through a value network approach. Building on the quadruple helix model to identify the actors in these networks, this study explores the relationships and value flows between the actors of 22 identified creative networks across the UK. It then maps these relationships using data gathered through a mixed methodology that includes survey data and focus group research. Our findings show that creative networks operate as central nodes of the local creative ecosystem, functioning as a ‘glue’ inside the otherwise very heterogenous creative industries. From this position, creative networks can act as catalysts for sustainability. However, the economic, cultural, and social value created by creative networks is often overshadowed by other challenges including a lack of funding and a lack of understanding from policy makers or the public.

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Wu, Weihua, Qinghai Yang, Peng Gong, and Kyung Sup Kwak. "Energy-Efficient Resource Optimization for OFDMA-Based Multi-Homing Heterogenous Wireless Networks." IEEE Transactions on Signal Processing 64, no. 22 (November 15, 2016): 5901–13. http://dx.doi.org/10.1109/tsp.2016.2599481.

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Spence, C., and J. Hosler. "Representation of stores along drainage networks in heterogenous landscapes for runoff modelling." Journal of Hydrology 347, no. 3-4 (December 2007): 474–86. http://dx.doi.org/10.1016/j.jhydrol.2007.09.035.

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Zang, Yaohua, Gang Bao, Xiaojing Ye, Hongyuan Zha, and Haomin Zhou. "A jump stochastic differential equation approach for influence prediction on heterogenous networks." Communications in Mathematical Sciences 18, no. 8 (2020): 2341–59. http://dx.doi.org/10.4310/cms.2020.v18.n8.a11.

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Zhou, Li, Chunsheng Zhu, Rukhsana Ruby, Xiaofei Wang, Xiaoting Ji, Shan Wang, and Jibo Wei. "QoS-aware energy-efficient resource allocation in OFDM-based heterogenous cellular networks." International Journal of Communication Systems 30, no. 2 (January 25, 2015): e2931. http://dx.doi.org/10.1002/dac.2931.

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WU, QINGCHU, XINCHU FU, and GUANGHU ZHU. "GLOBAL ATTRACTIVENESS OF DISCRETE-TIME EPIDEMIC OUTBREAK IN NETWORKS." International Journal of Biomathematics 05, no. 01 (January 2012): 1250004. http://dx.doi.org/10.1142/s1793524511001441.

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Epidemic dynamics in networks have attracted a great deal of attention from researchers of many fields. In this paper, we mainly study the global behaviors of discrete-time epidemic model in heterogenous networks. By theoretical analysis, we show that the model can be characterized by the basic reproduction number R0. When R0 is smaller than unit, the disease-free equilibrium is globally stable, while R0 is larger than unit, the unique positive equilibrium is globally attractive.

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Golla, Alena-K., Christian Tönnes, Tom Russ, Dominik F. Bauer, Matthias F. Froelich, Steffen J. Diehl, Stefan O. Schoenberg, et al. "Automated Screening for Abdominal Aortic Aneurysm in CT Scans under Clinical Conditions Using Deep Learning." Diagnostics 11, no. 11 (November 17, 2021): 2131. http://dx.doi.org/10.3390/diagnostics11112131.

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Abdominal aortic aneurysms (AAA) may remain clinically silent until they enlarge and patients present with a potentially lethal rupture. This necessitates early detection and elective treatment. The goal of this study was to develop an easy-to-train algorithm which is capable of automated AAA screening in CT scans and can be applied to an intra-hospital environment. Three deep convolutional neural networks (ResNet, VGG-16 and AlexNet) were adapted for 3D classification and applied to a dataset consisting of 187 heterogenous CT scans. The 3D ResNet outperformed both other networks. Across the five folds of the first training dataset it achieved an accuracy of 0.856 and an area under the curve (AUC) of 0.926. Subsequently, the algorithms performance was verified on a second data set containing 106 scans, where it ran fully automated and resulted in an accuracy of 0.953 and an AUC of 0.971. A layer-wise relevance propagation (LRP) made the decision process interpretable and showed that the network correctly focused on the aortic lumen. In conclusion, the deep learning-based screening proved to be robust and showed high performance even on a heterogeneous multi-center data set. Integration into hospital workflow and its effect on aneurysm management would be an exciting topic of future research.

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Oliveira, Francisco, Eduardo Tavares, Erica Sousa, and Bruno Nogueira. "Video Conferencing Evaluation Considering Scalable Video Coding and SDN Network." Revista de Informática Teórica e Aplicada 25, no. 2 (July 17, 2018): 38. http://dx.doi.org/10.22456/2175-2745.79310.

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Video conferencing is very common nowadays, and it may contemplate heterogenous devices (e.g., smartphones, notebooks, game consoles) and networks in the same session. Developing video conferencing systems for this myriad of devices with different capabilities requires special attention from system designer. Scalable video coding (SVC) is a prominent option to mitigate this heterogeneity issue, but traditional Internet protocol (IP) networks may not fully benefit from such a technology. In contrast, software-defined networking (SDN) may allow better utilization of SVC and improvements on video conferencing components. This paper evaluates the performance of video conferencing systems adopting SVC, SDN and ordinary IP networks, taking into account throughput, delay and peak signal-to-noise ratio (PSNR) as the metrics of interest. The experiments are based on Mininet framework and distinct network infrastructures are also considered. Results indicate SDN with SVC may deliver better video quality with reduced delay and increased throughput.

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Jankovics, Vince, Michael Garcia Ortiz, and Eduardo Alonso. "HetSAGE: Heterogenous Graph Neural Network for Relational Learning (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 18 (May 18, 2021): 15803–4. http://dx.doi.org/10.1609/aaai.v35i18.17898.

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This paper aims to bridge this gap between neuro-symbolic learning (NSL) and graph neural networks (GNN) approaches and provide a comparative study. We argue that the natural evolution of NSL leads to GNNs, while the logic programming foundations of NSL can bring powerful tools to improve the way information is represented and pre-processed for the GNN. In order to make this comparison, we propose HetSAGE, a GNN architecture that can efficiently deal with the resulting heterogeneous graphs that represent typical NSL learning problems. We show that our approach outperforms the state-of-the-art on 3 NSL tasks: CORA, MUTA188 and MovieLens.

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RMundada, Monica, Nishanth Thimmegowda, Thippesh K S, Avinash S, T. Bhuvaneswari, and Cyril Raj. "Hybrid Energy Efficient Protocol for Stable Concentric Clustering in Heterogenous Wireless Sensor Networks." International Journal of Computer Applications 73, no. 2 (July 26, 2013): 48–52. http://dx.doi.org/10.5120/12717-9531.

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Elwahab Fawzy, Abd, Asmaa Amer, Mona Shokair, Said El-Halafawy, and Waleed Saad. "Balanced and Efficient Energy Multi-hop Routing Algorithm in Heterogenous Wireless Sensor Networks." International Journal of Sensors, Wireless Communications and Control 6, no. 2 (September 6, 2016): 129–40. http://dx.doi.org/10.2174/2210327906666160727161736.

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