Authors : V. Manikandan, M. Sivaram, Amin Salih Mohammed and V. Porkodi
Abstract: In Wireless Sensor Networks (WSN), sensor nodes makes use of battery energy, routing and energy consumption along with certain limitations of sensor nodes are considered as a preliminary challenges and problems associated with WSN. In recent times, in WSNs, identification of successive nodes based on the localization and the energy minimization can be achieved by partitioning the nodes into clusters at the central region. In this manner, this research attempts to maintain energy consumption using optimal cuckoo search model in the network nodes. While comparing this with conventional models, the proposed model for energy estimation attains finest efficiency in relation to improvement in network lifetime. In this investigation, cuckoo optimization algorithm with Markov Chain model for successive identification of transition state is performed in WSN environment for identifying the optimal nodes for multi-hop routing and estimating energy. The anticipated strategy is measured in three specific criteria, nodes successive life time, energy utilization, end to end delay with targeted CMMRR algorithm, the residual energy, distance amongst the nodes and cluster head distance is also observed. The outcomes of simulating the anticipated CMMRR method are done in MATLAB environment. The outcomes of the proposed method is compared with the existing techniques like EAR Model, the proposed method shows better trade off 10.4-29% over prevailing EAR protocol in terms of packet delivery ratio, nodes life time and so on.
V. Manikandan, M. Sivaram, Amin Salih Mohammed and V. Porkodi, 2019. An Intelligent Optimization Algorithm for Optimal Route Selection for Wireless Sensor Networks. Journal of Engineering and Applied Sciences, 14: 6510-6518.