{"title":"A cooperative communication protocol for saving energy consumption in WSNs","authors":"M. Maalej, Hichem Besbes, S. Cherif","doi":"10.1109/ComNet.2012.6217725","DOIUrl":null,"url":null,"abstract":"Cooperative communication is a promising solution for Wireless Sensor Networks (WSN). Its main idea consists in a source node (sensor) which uses, at each hop, the resources of multiple nodes (called cooperative nodes) to transmit its data. Thus, by sharing resources between nodes, the transmission quality is enhanced. In this paper, we use the technique of reinforcement learning by opponent modelling, and propose a cooperative communication protocol based on RSSI and node energy consumption in a competetive context (RSSI/Energy CC). For this algorithm, a competitive mechanism is implemented at each node using a multi-agent reinforcement learning algorithm. The reinforcement learning concept consists in considering the cooperative nodes as multiple agents learning their optimal policy through experiences and rewards. By adopting an optimal policy, agents can optimally learn using locally observed network information and limited information exchange. Simulation results show that the proposed algorithm performs well in terms of network lifetime, packet delay, and energy consumption.","PeriodicalId":296060,"journal":{"name":"Third International Conference on Communications and Networking","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third International Conference on Communications and Networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ComNet.2012.6217725","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Cooperative communication is a promising solution for Wireless Sensor Networks (WSN). Its main idea consists in a source node (sensor) which uses, at each hop, the resources of multiple nodes (called cooperative nodes) to transmit its data. Thus, by sharing resources between nodes, the transmission quality is enhanced. In this paper, we use the technique of reinforcement learning by opponent modelling, and propose a cooperative communication protocol based on RSSI and node energy consumption in a competetive context (RSSI/Energy CC). For this algorithm, a competitive mechanism is implemented at each node using a multi-agent reinforcement learning algorithm. The reinforcement learning concept consists in considering the cooperative nodes as multiple agents learning their optimal policy through experiences and rewards. By adopting an optimal policy, agents can optimally learn using locally observed network information and limited information exchange. Simulation results show that the proposed algorithm performs well in terms of network lifetime, packet delay, and energy consumption.
协作通信是无线传感器网络(WSN)中一个很有前途的解决方案。它的主要思想包括一个源节点(传感器),它在每一跳使用多个节点(称为合作节点)的资源来传输数据。因此,通过在节点之间共享资源,可以提高传输质量。在本文中,我们利用对手建模的强化学习技术,提出了一种基于RSSI和竞争环境下节点能量消耗的协作通信协议(RSSI/ energy CC)。该算法使用多智能体强化学习算法在每个节点上实现竞争机制。强化学习的概念是将合作节点视为多个智能体,通过经验和奖励学习它们的最优策略。通过采用最优策略,智能体可以利用局部观察到的网络信息和有限的信息交换进行最优学习。仿真结果表明,该算法在网络生存时间、数据包延迟和能耗方面都有较好的性能。