Energy Efficient Receiver Signal Strength Indicator Based Clustered Routing Algorithm for Wireless Sensor Network
R. Anandha Lakshmi1, T. Sureshz2, R. Maruti3

1Ms. R.Anandha Lakshmi, Assistant Professor, Department of BCA, Anna Adarsh College for Women, Chennai.
2Dr. T. Suresh, Associate Professor, Department of Computer Science and Engineering, Annamalai University, Chidambaram, Tamil Nadu.
3Dr. R. Maruti, Professor, PonnaiyahRamajayam Institute of Science and Technology, Chennai.
Manuscript received on January 26, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 2590-2593 | Volume-9 Issue-3, February 2020. | Retrieval Number: C5596029320/2020©BEIESP | DOI: 10.35940/ijeat.C5596.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Robust and efficient algorithms for routing and other process for a wireless sensor network are under active development due to technological advancements on wireless transmission systems. Each of the sensor nodes in a wireless sensor network either transmits or forwards the data packets to the base station. The main objective of the majority of the work in the literature is to save the energy consumption efficiently. The cluster based routing mechanism helps to achieve low energy consumption within the network. The network organizes its nodes as a cluster and selects a particular node as cluster head to manage the transmission within and between clusters. The majority of the clustering approach selects the cluster head using a thresholding based approach. Nodes having energy level higher than the threshold are the candidates for the cluster head selection. In the proposed approach the nodes remaining energy and the sum of distance between individual nodes to the cluster head node is considered. Optimal cluster head selection will help to increase the overall life time of the network. The distance between the sensor nodes is estimated using RSSI (Received Signal Strength Indicator) and other parameters measured from the physical layer. Experiments are conducted with simulation environment created with the NS-2 simulator and efficiency of the approach is analyzed in detail.
Keywords: Cluster based routing, RSSI (Received Signal Strength Indicator), NS-2 simulator, cluster head selection, thresholding