Energy efficient gravitational model for tree based routing in wireless sensor networks

Abstract

Wireless Sensor Networks (WSNs) are widely used for gathering data from heterogeneous environments. Reduction of energy consumption is a key factor for WSN to maximize the network lifetime. A mobile sink with WSN is very effective to achieve the flexibility for data gathering in order to save energy, thereby enhancing network lifetime. In this thesis, we have proposed a novel tree-clustering algorithm based on the natural gravitational model to save energy in WSN with the mobile sink. We have used the concept of natural gravity to construct the tree cluster routing structure for sensor nodes. The main goal of this strategy is to shorten data transmission distance with bottleneck-free routing path of sensor nodes by adopting gravitational tree-cluster and multihop concepts. The residual energy of sensor nodes and distance between them is used to create an efficient routing structure and also determine the optimal position for the mobile sink. The energy consumption is reduced and the lifetime is elongated for the sensor nodes by balancing the network load and utilizing most reliable routing path. We use computer simulation which shows that our proposed scheme outperforms than cognate works in the energy consumption, network lifetime, throughput, and transmission overhead. Moreover, suitable delay time, minimum distance communication and minimum number of message retransmission are achieved by utilizing the mobile sink.