{"title":"基于阈值能量选择簇头的聚类算法","authors":"Ying Huang, Cong Huang","doi":"10.1109/ICECE.2010.657","DOIUrl":null,"url":null,"abstract":"One of important requirements for many Wireless sensor network applications is to prolong network lifetime. The cluster head consumes more energy than other member nodes, because it gathers data from its member nodes, processes it (e.g. data fusion), and transfers data to the sink node or to the base station that maybe located remotely. Therefore, the cluster head should be elected periodically within the cluster to avoid the quick death of the head node and make all node loads distribute evenly. Based on the extensive analyzing of those algorithms such as LEACH, a cluster algorithm for electing cluster heads based on threshold energy is presented. The lifetime is suggested to be expressed as to both the maximum last node dying time and the minimum time difference between the last node dying and the first node dying. In order to obtain the effect, threshold energy was obtained and evaluated. The threshold energy is related to the initial energy of each node (Eo), number of nodes(n), energy consumption of cluster head (ECch), and energy consumption of cluster members (ECcm). The main purpose is to obtain the maximum network lifetime. What we now have done just to analyse the static threshold energy. When the optimal Dynamic threshold energy is adapted in the algorithm, the lifetime can be prolonged while the performance of network can maintain unabated. Results demonstrate that this algorithm which is more effective routing protocol prolongs the network lifetime when cluster heads are elected with the optimal threshold energy.","PeriodicalId":6419,"journal":{"name":"2010 International Conference on Electrical and Control Engineering","volume":"2 1","pages":"2692-2695"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Cluster Algorithm for Electing Cluster Heads Based on Threshold Energy\",\"authors\":\"Ying Huang, Cong Huang\",\"doi\":\"10.1109/ICECE.2010.657\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of important requirements for many Wireless sensor network applications is to prolong network lifetime. The cluster head consumes more energy than other member nodes, because it gathers data from its member nodes, processes it (e.g. data fusion), and transfers data to the sink node or to the base station that maybe located remotely. Therefore, the cluster head should be elected periodically within the cluster to avoid the quick death of the head node and make all node loads distribute evenly. Based on the extensive analyzing of those algorithms such as LEACH, a cluster algorithm for electing cluster heads based on threshold energy is presented. The lifetime is suggested to be expressed as to both the maximum last node dying time and the minimum time difference between the last node dying and the first node dying. In order to obtain the effect, threshold energy was obtained and evaluated. The threshold energy is related to the initial energy of each node (Eo), number of nodes(n), energy consumption of cluster head (ECch), and energy consumption of cluster members (ECcm). The main purpose is to obtain the maximum network lifetime. What we now have done just to analyse the static threshold energy. When the optimal Dynamic threshold energy is adapted in the algorithm, the lifetime can be prolonged while the performance of network can maintain unabated. Results demonstrate that this algorithm which is more effective routing protocol prolongs the network lifetime when cluster heads are elected with the optimal threshold energy.\",\"PeriodicalId\":6419,\"journal\":{\"name\":\"2010 International Conference on Electrical and Control Engineering\",\"volume\":\"2 1\",\"pages\":\"2692-2695\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Electrical and Control Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECE.2010.657\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Electrical and Control Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECE.2010.657","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cluster Algorithm for Electing Cluster Heads Based on Threshold Energy
One of important requirements for many Wireless sensor network applications is to prolong network lifetime. The cluster head consumes more energy than other member nodes, because it gathers data from its member nodes, processes it (e.g. data fusion), and transfers data to the sink node or to the base station that maybe located remotely. Therefore, the cluster head should be elected periodically within the cluster to avoid the quick death of the head node and make all node loads distribute evenly. Based on the extensive analyzing of those algorithms such as LEACH, a cluster algorithm for electing cluster heads based on threshold energy is presented. The lifetime is suggested to be expressed as to both the maximum last node dying time and the minimum time difference between the last node dying and the first node dying. In order to obtain the effect, threshold energy was obtained and evaluated. The threshold energy is related to the initial energy of each node (Eo), number of nodes(n), energy consumption of cluster head (ECch), and energy consumption of cluster members (ECcm). The main purpose is to obtain the maximum network lifetime. What we now have done just to analyse the static threshold energy. When the optimal Dynamic threshold energy is adapted in the algorithm, the lifetime can be prolonged while the performance of network can maintain unabated. Results demonstrate that this algorithm which is more effective routing protocol prolongs the network lifetime when cluster heads are elected with the optimal threshold energy.