Shreya V. Basu, K. Ashwin, Nupur K. Neti, B. S. Premananda
{"title":"利用聚类技术提高无线传感器网络的网络寿命","authors":"Shreya V. Basu, K. Ashwin, Nupur K. Neti, B. S. Premananda","doi":"10.1109/RTEICT.2017.8256922","DOIUrl":null,"url":null,"abstract":"A wireless sensor network (WSN) is a network that consists of spatially distributed autonomous devices that use sensors to monitor the surrounding physical or environmental conditions. As WSNs are generally deployed over large areas or hostile environments, they are difficult to manage and monitor. Furthermore, the batteries cannot be easily recharged or replaced. This is a major drawback of a WSN. Clustering is an important method used for extending the lifetime of a network. It involves a cluster head (CH) which collects data from the cluster members (CMs) present in its cluster, and reports this data to the base station (BS). Thus, energy is conserved by sending data to the CH instead of the sink. An existing clustering technique for WSNs is the Low Adaptive Energy Clustering Hierarchy (LEACH). In this paper, the implementation of LEACH is discussed and an improvement of the LEACH model called Segmented LEACH is proposed. In order to further improve the network lifetime, the application of coalition game theory on a clustering algorithm is implemented. The simulation results show that the game theory model has a higher network lifetime, later first node death and lesser amount of energy consumption per node as compared to LEACH and Segmented LEACH model.","PeriodicalId":342831,"journal":{"name":"2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Improving the network lifetime of a wireless sensor network using clustering techniques\",\"authors\":\"Shreya V. Basu, K. Ashwin, Nupur K. Neti, B. S. Premananda\",\"doi\":\"10.1109/RTEICT.2017.8256922\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A wireless sensor network (WSN) is a network that consists of spatially distributed autonomous devices that use sensors to monitor the surrounding physical or environmental conditions. As WSNs are generally deployed over large areas or hostile environments, they are difficult to manage and monitor. Furthermore, the batteries cannot be easily recharged or replaced. This is a major drawback of a WSN. Clustering is an important method used for extending the lifetime of a network. It involves a cluster head (CH) which collects data from the cluster members (CMs) present in its cluster, and reports this data to the base station (BS). Thus, energy is conserved by sending data to the CH instead of the sink. An existing clustering technique for WSNs is the Low Adaptive Energy Clustering Hierarchy (LEACH). In this paper, the implementation of LEACH is discussed and an improvement of the LEACH model called Segmented LEACH is proposed. In order to further improve the network lifetime, the application of coalition game theory on a clustering algorithm is implemented. The simulation results show that the game theory model has a higher network lifetime, later first node death and lesser amount of energy consumption per node as compared to LEACH and Segmented LEACH model.\",\"PeriodicalId\":342831,\"journal\":{\"name\":\"2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RTEICT.2017.8256922\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTEICT.2017.8256922","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving the network lifetime of a wireless sensor network using clustering techniques
A wireless sensor network (WSN) is a network that consists of spatially distributed autonomous devices that use sensors to monitor the surrounding physical or environmental conditions. As WSNs are generally deployed over large areas or hostile environments, they are difficult to manage and monitor. Furthermore, the batteries cannot be easily recharged or replaced. This is a major drawback of a WSN. Clustering is an important method used for extending the lifetime of a network. It involves a cluster head (CH) which collects data from the cluster members (CMs) present in its cluster, and reports this data to the base station (BS). Thus, energy is conserved by sending data to the CH instead of the sink. An existing clustering technique for WSNs is the Low Adaptive Energy Clustering Hierarchy (LEACH). In this paper, the implementation of LEACH is discussed and an improvement of the LEACH model called Segmented LEACH is proposed. In order to further improve the network lifetime, the application of coalition game theory on a clustering algorithm is implemented. The simulation results show that the game theory model has a higher network lifetime, later first node death and lesser amount of energy consumption per node as compared to LEACH and Segmented LEACH model.