{"title":"无线自组织网络中最小能量广播树问题的迭代算法","authors":"Manki Min","doi":"10.1109/WASA.2007.71","DOIUrl":null,"url":null,"abstract":"In this paper, we present an iterated algorithm framework that can be implemented with heuristics in the literature for the minimum energy broadcasting problem in wireless ad hoc networks. We investigate three iterated algorithm implementations, IBIP, IOMEGa, ISOR, that are based on BIP, OMEGa, SOR. The algorithms run iterations to find better solutions of the problem and in each iteration, fixing the source node's transmission power, the algorithm finds the intermediate solutions. And after all the iterations, the algorithm will give the output of the best solution so far. By fixing the source node's transmission power we can get the effect of diverse solution search without hurting the original algorithm's theoretical performance bound. The experimental results confirm that the iterated algorithms significantly improve the solution quality with the help of diverse search.","PeriodicalId":316831,"journal":{"name":"International Conference on Wireless Algorithms, Systems and Applications (WASA 2007)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Iterated Algorithms for the Minimum Energy Broadcast Tree Problem in Wireless Ad Hoc Networks\",\"authors\":\"Manki Min\",\"doi\":\"10.1109/WASA.2007.71\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present an iterated algorithm framework that can be implemented with heuristics in the literature for the minimum energy broadcasting problem in wireless ad hoc networks. We investigate three iterated algorithm implementations, IBIP, IOMEGa, ISOR, that are based on BIP, OMEGa, SOR. The algorithms run iterations to find better solutions of the problem and in each iteration, fixing the source node's transmission power, the algorithm finds the intermediate solutions. And after all the iterations, the algorithm will give the output of the best solution so far. By fixing the source node's transmission power we can get the effect of diverse solution search without hurting the original algorithm's theoretical performance bound. The experimental results confirm that the iterated algorithms significantly improve the solution quality with the help of diverse search.\",\"PeriodicalId\":316831,\"journal\":{\"name\":\"International Conference on Wireless Algorithms, Systems and Applications (WASA 2007)\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Wireless Algorithms, Systems and Applications (WASA 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WASA.2007.71\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Wireless Algorithms, Systems and Applications (WASA 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WASA.2007.71","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Iterated Algorithms for the Minimum Energy Broadcast Tree Problem in Wireless Ad Hoc Networks
In this paper, we present an iterated algorithm framework that can be implemented with heuristics in the literature for the minimum energy broadcasting problem in wireless ad hoc networks. We investigate three iterated algorithm implementations, IBIP, IOMEGa, ISOR, that are based on BIP, OMEGa, SOR. The algorithms run iterations to find better solutions of the problem and in each iteration, fixing the source node's transmission power, the algorithm finds the intermediate solutions. And after all the iterations, the algorithm will give the output of the best solution so far. By fixing the source node's transmission power we can get the effect of diverse solution search without hurting the original algorithm's theoretical performance bound. The experimental results confirm that the iterated algorithms significantly improve the solution quality with the help of diverse search.