{"title":"RWSN中基于aco的路径规划方案","authors":"Peng Huang, Zhiliang Kang, Chang Liu, F. Lin","doi":"10.1109/SKIMA.2016.7916226","DOIUrl":null,"url":null,"abstract":"Traditional wireless sensor networks (WSNs) are consist of sensor nodes with limited battery energy power. Due to rapid development of wireless power transfer technology, sensors can be recharged when they are within limited charging ranges of mobile devices and we call this kind of network rechargeable WSN(RWSN). In RWSN, mobile chargers (MC) are employed to recharge the sensor nodes. However, since charging power, moving speed and total energy of one MC are limited, finding the minimal MCs and how to schedule the MCs to complete the charging task of the sensor node become the major problems in such RWSNs. In this work, a novel path planning scheme, named ACO_PP (Ant Colony System based path planning), is proposed by modeling the path planning problem of the MC in rechargeable wireless sensor network. In ACO_PP, virtual charge nodes are introduced to create the routes for MCs, and then the Ant Colony Optimization is employed to optimize these routes. The simulation results show that the ACO_PP scheme achieves better performance than existing schemes.","PeriodicalId":417370,"journal":{"name":"2016 10th International Conference on Software, Knowledge, Information Management & Applications (SKIMA)","volume":"32 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"ACO-based path planning scheme in RWSN\",\"authors\":\"Peng Huang, Zhiliang Kang, Chang Liu, F. Lin\",\"doi\":\"10.1109/SKIMA.2016.7916226\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional wireless sensor networks (WSNs) are consist of sensor nodes with limited battery energy power. Due to rapid development of wireless power transfer technology, sensors can be recharged when they are within limited charging ranges of mobile devices and we call this kind of network rechargeable WSN(RWSN). In RWSN, mobile chargers (MC) are employed to recharge the sensor nodes. However, since charging power, moving speed and total energy of one MC are limited, finding the minimal MCs and how to schedule the MCs to complete the charging task of the sensor node become the major problems in such RWSNs. In this work, a novel path planning scheme, named ACO_PP (Ant Colony System based path planning), is proposed by modeling the path planning problem of the MC in rechargeable wireless sensor network. In ACO_PP, virtual charge nodes are introduced to create the routes for MCs, and then the Ant Colony Optimization is employed to optimize these routes. The simulation results show that the ACO_PP scheme achieves better performance than existing schemes.\",\"PeriodicalId\":417370,\"journal\":{\"name\":\"2016 10th International Conference on Software, Knowledge, Information Management & Applications (SKIMA)\",\"volume\":\"32 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 10th International Conference on Software, Knowledge, Information Management & Applications (SKIMA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SKIMA.2016.7916226\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 10th International Conference on Software, Knowledge, Information Management & Applications (SKIMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SKIMA.2016.7916226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Traditional wireless sensor networks (WSNs) are consist of sensor nodes with limited battery energy power. Due to rapid development of wireless power transfer technology, sensors can be recharged when they are within limited charging ranges of mobile devices and we call this kind of network rechargeable WSN(RWSN). In RWSN, mobile chargers (MC) are employed to recharge the sensor nodes. However, since charging power, moving speed and total energy of one MC are limited, finding the minimal MCs and how to schedule the MCs to complete the charging task of the sensor node become the major problems in such RWSNs. In this work, a novel path planning scheme, named ACO_PP (Ant Colony System based path planning), is proposed by modeling the path planning problem of the MC in rechargeable wireless sensor network. In ACO_PP, virtual charge nodes are introduced to create the routes for MCs, and then the Ant Colony Optimization is employed to optimize these routes. The simulation results show that the ACO_PP scheme achieves better performance than existing schemes.