A Coalition Formation Game for Distributed Node Clustering in Mobile Ad Hoc Networks

Massin, Raphaël; Martret, Christophe J. Le; Ciblat, Philippe

doi:10.1109/twc.2017.2690419

Cited by 35 publications

(12 citation statements)

References 23 publications

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“…The algorithm developed was based on the density of the nodes and the alliance between them. The writers in [19,20] suggest a central controller that had already implemented semi-matching load balancing for WLAN. To spread the uneven network loads, the central controller acquires knowledge of the active channel time.…”

Section: Related Workmentioning

confidence: 99%

Improving the Energy Efficiency in Mobile Ad-Hoc Network Using Learning-Based Routing

Aroulanandam¹,

Latchoumi²,

Balamurugan³

et al. 2020

RIA

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Improving Mobile Ad-Hoc Network (MANET) performance is a tedious task because of the dynamic and uncertain characteristics of the nodes. MANET nodes connected to multiple applications that involve a high exchange of data. To add reliability to the application services, MANETs optimized through dedicated load balancing schemes. The Dynamic Range Clustering (DRC) algorithm associated with Learning-based Routing (LR) used in the present work to improve the energy efficiency and the nature of the network's data handling. DRC design focuses on selecting the head of the cluster and maintaining stability over the cluster. LR selects unique neighbors that assist in ensuring the efficient, non-congested communication of data exchange. An effort has made to combine the two incompatible methods to increase the performance of the network over differential network traffic. The proposed approach tested using simulations and measures output by comparative analysis.

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Section: Related Workmentioning

confidence: 99%

Improving the Energy Efficiency in Mobile Ad-Hoc Network Using Learning-Based Routing

Aroulanandam¹,

Latchoumi²,

Balamurugan³

et al. 2020

RIA

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show abstract

“…Recently, game theory has been applied to network problems because nodes in a distributed network are independent, they have to make decisions by their own interest, and game theory adapts with distributed optimization problems [26]. In [27], the authors modeled clustering problem in MANET as a coalition game framework, and proposed a distributed generic coalition formation algorithm that operated clustering process. This generic algorithm was compatible with unstructured and structured cases.…”

Section: A Related Work and Motivationsmentioning

confidence: 99%

A Game Theory Based Clustering Protocol to Support Multicast Routing in Cognitive Radio Mobile Ad Hoc Networks

et al. 2020

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The frequent movement of nodes in cognitive radio mobile ad hoc networks (CRAHNs) causes challenges in scalability, stability, channel sensing and channel access problems that can be solved by using clustering technique. Game theory is a feasible approach to solve such problems by casting clustering problems as distributed optimization problems. The main contributions of this paper are as follows. Firstly, we propose a minimum connected weighted inner edge spanning tree (MWIEST) game to find an approximate solution of a MWIEST problem in CRAHNs. In this game, a link-weight function of each link is designed based on a combination of link-stability and link-connectivity ratio functions. Secondly, we prove that the MWIEST game is an exact potential game that exists at least one Nash equilibrium (NE) point which is an approximate solution of the MWIEST problem. Besides, we also prove that best responses (BRs) of the game converge to a NE in finite iterations. Thirdly, based on the MWIEST game, we propose four algorithms including the node information exchange (NIE), the best response selection (BRS), the intermediate nodes selection (INS) and the forming cluster (FC). Specifically, the algorithms NIE, BRS and INS provide a set of intermediate nodes (SetIN) which supports the FC algorithm to form clusters. Finally, we propose the game theory based clustering (GBC) protocol which is combination of the FC algorithm and the proposed cluster maintenance algorithm to construct high stable clusters supporting multicast routing in CRAHNs. Moreover, each obtained cluster includes most members having the same receiving channel which avoids the affected regions of licensed channels. For the performance evaluation, we implement the GBC protocol in OMNET++ platform to demonstrate its performance improvement over the state-of-the-art protocols in terms of network stability and control overheads. INDEX TERMS Cognitive radio mobile ad hoc network, clustering, multicast routing, game theory, network layer, OMNET++.

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“…Moreover, the concepts of coalition and clustering are compatible. e coalitional game theory has been used in clustering for mobile ad hoc networks (MANETs) [22]. However, besides the difference of system model between MANET and VANET, there is a key difference between research in [22] and this research, that is, the formulation of the coalitional rule.…”

Section: Related Workmentioning

confidence: 99%

“…e coalitional game theory has been used in clustering for mobile ad hoc networks (MANETs) [22]. However, besides the difference of system model between MANET and VANET, there is a key difference between research in [22] and this research, that is, the formulation of the coalitional rule. Another difference is that research in [22] does not have a cluster head in cluster structure, whereas this research has.…”

Section: Related Workmentioning

confidence: 99%

Coalitional Game Theoretical Approach for VANET Clustering to Improve SNR

Sulistyo

Alam

Adrian

2019

Journal of Computer Networks and Communications

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Clustering is considered as the potential approach for network management in vehicular ad hoc network (VANET). The performance of clustering is often assessed based on the stability of the clusters. Hence, most of the clustering methods aim to establish stable clusters. However, besides the stability of cluster, good link quality must be provided, especially when reliable and high-capacity transmission is demanded. Therefore, this paper proposes a clustering method based on coalitional game theory with the purpose to improve the average of vehicle-to-vehicle (V2V) signal-to-noise ratio (SNR) and channel capacity while maintaining the stability of the cluster. In the proposed method, each vehicle attempts to form a cluster with other vehicles according to coalition value. To attain the purpose of clustering, the value of coalition is formulated based on the V2V SNR, connection lifetime, and speed difference between vehicles. In fast-changing network topology, the higher average of SNR can be achieved but the stability of cluster becomes hard to be maintained. Based on the simulation results, SNR improvement can be adjusted in order to balance with the cluster stability by setting the parameters in the proposed method accordingly. Further simulation results show that the proposed method can obtain a higher average of V2V SNR and channel capacity than other relevant methods.

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A Coalition Formation Game for Distributed Node Clustering in Mobile Ad Hoc Networks

Cited by 35 publications

References 23 publications

Improving the Energy Efficiency in Mobile Ad-Hoc Network Using Learning-Based Routing

Improving the Energy Efficiency in Mobile Ad-Hoc Network Using Learning-Based Routing

A Game Theory Based Clustering Protocol to Support Multicast Routing in Cognitive Radio Mobile Ad Hoc Networks

Coalitional Game Theoretical Approach for VANET Clustering to Improve SNR

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