Kosuke Ozera, Shinji Sakamoto, Donald Elmazi, Kevin Bylykbashi, Makoto Ikeda, L. Barolli
{"title":"一种模糊聚类方法:不同参数下的性能评价","authors":"Kosuke Ozera, Shinji Sakamoto, Donald Elmazi, Kevin Bylykbashi, Makoto Ikeda, L. Barolli","doi":"10.1504/IJSSC.2017.10010064","DOIUrl":null,"url":null,"abstract":"A mobile ad hoc network (MANET) is a multi-hop wireless network in which the mobile nodes are dynamic in nature and has a limited bandwidth and minimum battery power. Due to this challenging environment, the mobile nodes can be grouped into clusters to achieve better stability and scalability. Grouping the mobile nodes is called clustering, in which a leader node is elected to manage the entire network. In this paper, first we introduce various approaches for clustering focused on different performance metrics. Then, we show some clustering schemes. Finally, we present and compare two Fuzzy based systems (called F2SMC1 and F2SMC2) for clustering nodes in MANETs. We consider different parameters for clustering such as: number of nodes in a cluster, node spent power, node security and distance of the node from cluster centre. We compare the performance of F2SMC1 and F2SMC2 and show that the F2SMC2 is more complex than F2SMC1, but the F2SMC2 can manage the nodes in the cluster better than F2SMC1. The evaluation results show that by selecting nodes with small distance and high security values, the nodes are closer to cluster centre and more secure, so they will remain in the cluster. In the case when NNC is 0.9, SP is 0.3, SC is 0.9 and DS is 0.1, the proposed F2SMC2 scheme outperforms the F2SMC1 scheme by 15% in terms of number of remained nodes in a cluster.","PeriodicalId":43931,"journal":{"name":"International Journal of Space-Based and Situated Computing","volume":"1 1","pages":"166-176"},"PeriodicalIF":0.0000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"A fuzzy approach for clustering in MANETs: performance evaluation for different parameters\",\"authors\":\"Kosuke Ozera, Shinji Sakamoto, Donald Elmazi, Kevin Bylykbashi, Makoto Ikeda, L. Barolli\",\"doi\":\"10.1504/IJSSC.2017.10010064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A mobile ad hoc network (MANET) is a multi-hop wireless network in which the mobile nodes are dynamic in nature and has a limited bandwidth and minimum battery power. Due to this challenging environment, the mobile nodes can be grouped into clusters to achieve better stability and scalability. Grouping the mobile nodes is called clustering, in which a leader node is elected to manage the entire network. In this paper, first we introduce various approaches for clustering focused on different performance metrics. Then, we show some clustering schemes. Finally, we present and compare two Fuzzy based systems (called F2SMC1 and F2SMC2) for clustering nodes in MANETs. We consider different parameters for clustering such as: number of nodes in a cluster, node spent power, node security and distance of the node from cluster centre. We compare the performance of F2SMC1 and F2SMC2 and show that the F2SMC2 is more complex than F2SMC1, but the F2SMC2 can manage the nodes in the cluster better than F2SMC1. The evaluation results show that by selecting nodes with small distance and high security values, the nodes are closer to cluster centre and more secure, so they will remain in the cluster. In the case when NNC is 0.9, SP is 0.3, SC is 0.9 and DS is 0.1, the proposed F2SMC2 scheme outperforms the F2SMC1 scheme by 15% in terms of number of remained nodes in a cluster.\",\"PeriodicalId\":43931,\"journal\":{\"name\":\"International Journal of Space-Based and Situated Computing\",\"volume\":\"1 1\",\"pages\":\"166-176\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Space-Based and Situated Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJSSC.2017.10010064\",\"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 Journal of Space-Based and Situated Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJSSC.2017.10010064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fuzzy approach for clustering in MANETs: performance evaluation for different parameters
A mobile ad hoc network (MANET) is a multi-hop wireless network in which the mobile nodes are dynamic in nature and has a limited bandwidth and minimum battery power. Due to this challenging environment, the mobile nodes can be grouped into clusters to achieve better stability and scalability. Grouping the mobile nodes is called clustering, in which a leader node is elected to manage the entire network. In this paper, first we introduce various approaches for clustering focused on different performance metrics. Then, we show some clustering schemes. Finally, we present and compare two Fuzzy based systems (called F2SMC1 and F2SMC2) for clustering nodes in MANETs. We consider different parameters for clustering such as: number of nodes in a cluster, node spent power, node security and distance of the node from cluster centre. We compare the performance of F2SMC1 and F2SMC2 and show that the F2SMC2 is more complex than F2SMC1, but the F2SMC2 can manage the nodes in the cluster better than F2SMC1. The evaluation results show that by selecting nodes with small distance and high security values, the nodes are closer to cluster centre and more secure, so they will remain in the cluster. In the case when NNC is 0.9, SP is 0.3, SC is 0.9 and DS is 0.1, the proposed F2SMC2 scheme outperforms the F2SMC1 scheme by 15% in terms of number of remained nodes in a cluster.