The most important challenge in Wireless Sensor Networks (WSNs) is the energy constraint. Numerous solutions have been proposed to alleviate the issue, including clustering. Game theory is an effective decision-making tool that has been shown to be effective in solving complex problems. In this paper, we employ cooperative games and propose a new clustering scheme called Coalitional Game-Theoretic Clustering (CGTC) algorithm for WSNs. The idea is to partition the entire network area into two regions, namely far and vicinity, in order to address the hotspot problem in WSNs, wherein nodes close to the base station (BS) tend to deplete their energy faster due to relaying the traffic load received from farther nodes. Then, coalitional games are utilized to group nodes as coalitions. The main factor in choosing coalition heads is the energy level of nodes so that the most powerful nodes play the role of heads. The Shapley value is adopted as the solution concept to our coalitional games. The results of simulations confirm the effectiveness of CGTC in terms of energy efficiency and improved throughput.
翻译:在无线传感器网络(WSNs)中,最重要的挑战是能源限制。提出了许多缓解问题的解决方案,包括集群。游戏理论是一个有效的决策工具,在解决复杂问题时证明是有效的。在本文中,我们采用了合作游戏,并为WSNS提出了称为联合游戏-理论集群(CGTC)的新的集群方案。想法是将整个网络区域分为两个区域,即远处和邻近地区,以便解决WSNs的热点问题,因为与基地站(BS)相近的节点往往由于转发从更远的节点接收的交通负荷而更快地耗尽它们的能量。然后,联盟游戏被用来将节点分组为联盟。选择联盟头的主要因素是节点的能量水平,以便最强大的节点发挥头的作用。将沙普利值作为我们联盟游戏的解决方案概念。模拟的结果证实了CGTC在能源效率和改善吞吐量方面的有效性。