P. Satyanarayana, Sa P. Teja Venkata, P. R. Kumar, Varma S. Girish Kumar, M.D. Zulfath Aamina
{"title":"改进的基于簇的路由算法在无线传感器网络中的实现","authors":"P. Satyanarayana, Sa P. Teja Venkata, P. R. Kumar, Varma S. Girish Kumar, M.D. Zulfath Aamina","doi":"10.1109/wispnet54241.2022.9767114","DOIUrl":null,"url":null,"abstract":"A Network consisting of sensor nodes is referred to as Wireless Sensor Network. In this Network the sensor nodes are positioned in geographical locations or concerned regions for monitoring of respective physical conditions. Environmental sensing, health care surveillance, border surveillance, forest monitoring are few of the applied fields of wireless sensor networks. The key challenge will be the energy utilization. To overcome this challenge numerous algorithms have been proposed. These various algorithms proposed are cluster-based algorithms which contribute an answer for the energy utilization problem. The working of clustering algorithm is explained as follows. Initially, the algorithm divides the network into cells say clusters. Then, the genetic algorithm comes into picture so that the optimal numbers of nodes are determined in a network. Then these nodes are placed in the environment, the chromosome length is set equal to number of nodes so that it may have slow convergence. Due to this there will be reduction in the chromosome length and so that we can reach the optimal solution due to swift convergence. Conversely, K-Means algorithm is used after setting up the cluster heads in each chromosome, those are delegated as the early points for the algorithm which is used for speed clustering procedure.","PeriodicalId":432794,"journal":{"name":"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Implementation of modified Cluster Based Routing Algorithm to Enhance QoS for Wireless Sensor Networks\",\"authors\":\"P. Satyanarayana, Sa P. Teja Venkata, P. R. Kumar, Varma S. Girish Kumar, M.D. Zulfath Aamina\",\"doi\":\"10.1109/wispnet54241.2022.9767114\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Network consisting of sensor nodes is referred to as Wireless Sensor Network. In this Network the sensor nodes are positioned in geographical locations or concerned regions for monitoring of respective physical conditions. Environmental sensing, health care surveillance, border surveillance, forest monitoring are few of the applied fields of wireless sensor networks. The key challenge will be the energy utilization. To overcome this challenge numerous algorithms have been proposed. These various algorithms proposed are cluster-based algorithms which contribute an answer for the energy utilization problem. The working of clustering algorithm is explained as follows. Initially, the algorithm divides the network into cells say clusters. Then, the genetic algorithm comes into picture so that the optimal numbers of nodes are determined in a network. Then these nodes are placed in the environment, the chromosome length is set equal to number of nodes so that it may have slow convergence. Due to this there will be reduction in the chromosome length and so that we can reach the optimal solution due to swift convergence. Conversely, K-Means algorithm is used after setting up the cluster heads in each chromosome, those are delegated as the early points for the algorithm which is used for speed clustering procedure.\",\"PeriodicalId\":432794,\"journal\":{\"name\":\"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/wispnet54241.2022.9767114\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/wispnet54241.2022.9767114","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implementation of modified Cluster Based Routing Algorithm to Enhance QoS for Wireless Sensor Networks
A Network consisting of sensor nodes is referred to as Wireless Sensor Network. In this Network the sensor nodes are positioned in geographical locations or concerned regions for monitoring of respective physical conditions. Environmental sensing, health care surveillance, border surveillance, forest monitoring are few of the applied fields of wireless sensor networks. The key challenge will be the energy utilization. To overcome this challenge numerous algorithms have been proposed. These various algorithms proposed are cluster-based algorithms which contribute an answer for the energy utilization problem. The working of clustering algorithm is explained as follows. Initially, the algorithm divides the network into cells say clusters. Then, the genetic algorithm comes into picture so that the optimal numbers of nodes are determined in a network. Then these nodes are placed in the environment, the chromosome length is set equal to number of nodes so that it may have slow convergence. Due to this there will be reduction in the chromosome length and so that we can reach the optimal solution due to swift convergence. Conversely, K-Means algorithm is used after setting up the cluster heads in each chromosome, those are delegated as the early points for the algorithm which is used for speed clustering procedure.