{"title":"A New Energy-Efficient Routing Algorithm Based on Ant Colony System for Wireless Sensor Networks","authors":"Songzhu Xia, Su Wu, Jun Ni","doi":"10.1109/ICICSE.2009.27","DOIUrl":null,"url":null,"abstract":"Due to the limited availability of energy within network nodes, energy-efficient routing mechanism is one of the most critical issues in wireless sensor networks. In this paper, we propose a multi-path routing algorithm with energy-aware based on ant colony system. The algorithm introduces three improved rules: Ant Marginalization Rule, State Transition Rule and Global Pheromone Update Rule to solve the problems of local convergence, local optimization and multi-path for transferring data respectively. It can avoid using up the energy of nodes on the optimal path while preserving network connectivity. Compared with traditional routing methods, simulation results demonstrate that the algorithm can help save energy and prolong the lifetime of the network.","PeriodicalId":193621,"journal":{"name":"2009 Fourth International Conference on Internet Computing for Science and Engineering","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Fourth International Conference on Internet Computing for Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICSE.2009.27","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Due to the limited availability of energy within network nodes, energy-efficient routing mechanism is one of the most critical issues in wireless sensor networks. In this paper, we propose a multi-path routing algorithm with energy-aware based on ant colony system. The algorithm introduces three improved rules: Ant Marginalization Rule, State Transition Rule and Global Pheromone Update Rule to solve the problems of local convergence, local optimization and multi-path for transferring data respectively. It can avoid using up the energy of nodes on the optimal path while preserving network connectivity. Compared with traditional routing methods, simulation results demonstrate that the algorithm can help save energy and prolong the lifetime of the network.
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