{"title":"基于混合算法的无线传感器网络最优路由协议","authors":"Ayush Singh, A. Ojha, P. Chanak","doi":"10.1109/IATMSI56455.2022.10119277","DOIUrl":null,"url":null,"abstract":"Wireless Sensor Networks (WSNs) are widely applied in various applications such as environment monitoring, precision agriculture, healthcare, and surveillance. Sensor nodes accumulate data and transmit it to a central unit or Base Station (BS). The traditional data routing mechanisms cause high energy depletion at sensor nodes. It causes the premature death of sensor nodes. The lifetimes of sensor nodes have a direct impact on the lifetime of WSNs. To get more prolonged operation of WSNs, the lifetime of sensor nodes should be increased. This paper applies the Fuzzy C-means algorithm to create different clusters of sensor nodes. Furthermore, this paper proposes a hybrid data routing algorithm that designs an optimal route among cluster heads for data transmission. A hybrid of Ant Colony Optimization (ACO) and Bacterial Foraging Optimization (BFO) algorithm is used to identify the optimal route with in the network. The optimal data collection path minimizes the transmission distance between nodes, minimizes data collection delay and saves energy at sensor nodes. This approach has been compared with other state of the art approaches in terms of residual energy, number of alive nodes and average transmission delay. The results show that the proposed hybrid approach outperforms existing methods.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hybrid Algorithm based Optimal Routing Protocol for Wireless Sensor Networks\",\"authors\":\"Ayush Singh, A. Ojha, P. Chanak\",\"doi\":\"10.1109/IATMSI56455.2022.10119277\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wireless Sensor Networks (WSNs) are widely applied in various applications such as environment monitoring, precision agriculture, healthcare, and surveillance. Sensor nodes accumulate data and transmit it to a central unit or Base Station (BS). The traditional data routing mechanisms cause high energy depletion at sensor nodes. It causes the premature death of sensor nodes. The lifetimes of sensor nodes have a direct impact on the lifetime of WSNs. To get more prolonged operation of WSNs, the lifetime of sensor nodes should be increased. This paper applies the Fuzzy C-means algorithm to create different clusters of sensor nodes. Furthermore, this paper proposes a hybrid data routing algorithm that designs an optimal route among cluster heads for data transmission. A hybrid of Ant Colony Optimization (ACO) and Bacterial Foraging Optimization (BFO) algorithm is used to identify the optimal route with in the network. The optimal data collection path minimizes the transmission distance between nodes, minimizes data collection delay and saves energy at sensor nodes. This approach has been compared with other state of the art approaches in terms of residual energy, number of alive nodes and average transmission delay. The results show that the proposed hybrid approach outperforms existing methods.\",\"PeriodicalId\":221211,\"journal\":{\"name\":\"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IATMSI56455.2022.10119277\",\"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 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IATMSI56455.2022.10119277","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hybrid Algorithm based Optimal Routing Protocol for Wireless Sensor Networks
Wireless Sensor Networks (WSNs) are widely applied in various applications such as environment monitoring, precision agriculture, healthcare, and surveillance. Sensor nodes accumulate data and transmit it to a central unit or Base Station (BS). The traditional data routing mechanisms cause high energy depletion at sensor nodes. It causes the premature death of sensor nodes. The lifetimes of sensor nodes have a direct impact on the lifetime of WSNs. To get more prolonged operation of WSNs, the lifetime of sensor nodes should be increased. This paper applies the Fuzzy C-means algorithm to create different clusters of sensor nodes. Furthermore, this paper proposes a hybrid data routing algorithm that designs an optimal route among cluster heads for data transmission. A hybrid of Ant Colony Optimization (ACO) and Bacterial Foraging Optimization (BFO) algorithm is used to identify the optimal route with in the network. The optimal data collection path minimizes the transmission distance between nodes, minimizes data collection delay and saves energy at sensor nodes. This approach has been compared with other state of the art approaches in terms of residual energy, number of alive nodes and average transmission delay. The results show that the proposed hybrid approach outperforms existing methods.