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Augmentation in the Network Life Period by Threshold Sensitive Energy Efficient Sensor Network Protocol in Wireless Sensor Network
Author Name : Sheena Rawal, Sumit Dalal
ABSTRACT WSNs are used in environmental monitoring, security, medical applications, etc. The sensor nodes are usually randomly deployed in a specific region. These sensor nodes collect their data and send it to the Base Station (BS) via some routing protocol. These nodes cannot be recharged from time to time to keep them alive. They must follow a protocol which must ensure the efficient use of their power, so that those nodes may serve as long as possible without any external assistance. A routing technique plays a key role in their energy consumption. Many of the routing protocols use clustering as their routing technique. So clustering plays a very important role in prolonging the stability period and network life time. The Cluster Heads (CHs) collect the data from all the nodes in their cluster, aggregate it and then finally send it to the BS. These sensor nodes must follow a certain routing protocol to send their data efficiently to the BS. The main objective of all routing protocols is to minimize the energy consumption so that the network lifetime and particularly the stability period of the network may be enhanced. By network lifetime we mean the time duration from the start of the network till the death of the last node, whereas, stability period means the time duration from the start of the network till the death of the first node. This research has object to develop an energy efficient increased lifetime threshold sensitive clustering algorithm by dynamic selection of cluster heads using multi-hops and multi-path, that leads to load balancing on different-different clusters. This results in the enhancement of cluster heads or normal nodes network lifetime and comparison of performance of the proposed protocol with TEEN. In this work, we propose an energy efficient multipath routing algorithm in WSN. This protocol is designed to improve the latency, resiliency and efficiency through discovering multiple paths from the source to the destination.