{"title":"基于最大权值的高效簇头选举算法","authors":"P. Sivaprakasam, R. Gunavathi","doi":"10.1109/ICOAC.2011.6165195","DOIUrl":null,"url":null,"abstract":"In the last two decades, there is magnetism in the use of internet and Communication Technology in the field of Mobile Ad Hoc Network. It motivates the researchers to turn over in those areas. There were some algorithms proposed for electing the efficient Clusterheads. Clusterheads are having more responsibilities like to minimize the re-affiliation, topology changes, and the stability of the on demand networks. We proposed a new efficient clusterhead selection algorithm based on the maximum weight in which it takes consideration of five different weight parameters. In this paper we analyses the clusterhead changes, energy consumption, life time of the network and end to end delay of the nodes. The experimental result also shows that proposed algorithm is better than the existing Weighted Clustering Algorithms.","PeriodicalId":369712,"journal":{"name":"2011 Third International Conference on Advanced Computing","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"An efficient clusterhead election algorithm based on maximum weight for MANET\",\"authors\":\"P. Sivaprakasam, R. Gunavathi\",\"doi\":\"10.1109/ICOAC.2011.6165195\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the last two decades, there is magnetism in the use of internet and Communication Technology in the field of Mobile Ad Hoc Network. It motivates the researchers to turn over in those areas. There were some algorithms proposed for electing the efficient Clusterheads. Clusterheads are having more responsibilities like to minimize the re-affiliation, topology changes, and the stability of the on demand networks. We proposed a new efficient clusterhead selection algorithm based on the maximum weight in which it takes consideration of five different weight parameters. In this paper we analyses the clusterhead changes, energy consumption, life time of the network and end to end delay of the nodes. The experimental result also shows that proposed algorithm is better than the existing Weighted Clustering Algorithms.\",\"PeriodicalId\":369712,\"journal\":{\"name\":\"2011 Third International Conference on Advanced Computing\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Third International Conference on Advanced Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOAC.2011.6165195\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Third International Conference on Advanced Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOAC.2011.6165195","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An efficient clusterhead election algorithm based on maximum weight for MANET
In the last two decades, there is magnetism in the use of internet and Communication Technology in the field of Mobile Ad Hoc Network. It motivates the researchers to turn over in those areas. There were some algorithms proposed for electing the efficient Clusterheads. Clusterheads are having more responsibilities like to minimize the re-affiliation, topology changes, and the stability of the on demand networks. We proposed a new efficient clusterhead selection algorithm based on the maximum weight in which it takes consideration of five different weight parameters. In this paper we analyses the clusterhead changes, energy consumption, life time of the network and end to end delay of the nodes. The experimental result also shows that proposed algorithm is better than the existing Weighted Clustering Algorithms.