Research Article
Exploration on Increasing Packet delivery rate in WSN using Cluster Approach
@ARTICLE{10.4108/eai.12-9-2018.155556, author={R. Mahaveerakannan and Dr. C. Suresh Gnana Dhas and Dr. V. Ganesan}, title={Exploration on Increasing Packet delivery rate in WSN using Cluster Approach}, journal={EAI Endorsed Transactions on Energy Web and Information Technologies}, volume={5}, number={20}, publisher={EAI}, journal_a={EW}, year={2018}, month={9}, keywords={WSN, Location Accuracy, Neighbor Node Table, Cluster Region, Location Status Navigator and Delay}, doi={10.4108/eai.12-9-2018.155556} }
- R. Mahaveerakannan
Dr. C. Suresh Gnana Dhas
Dr. V. Ganesan
Year: 2018
Exploration on Increasing Packet delivery rate in WSN using Cluster Approach
EW
EAI
DOI: 10.4108/eai.12-9-2018.155556
Abstract
Wireless Sensor Network (WSN) plays a vital role and part of real time communication applications. Location of unknown node is difficult to find in the presence of mobile sensor nodes. Navigator plays an important role in identifying network fault and unknown node location. In existing schemes, either trilateration or geographical position routing were deployed to increase the location accuracy. In this research, Neighbour based Cluster Location Aware Routing (NCLAR) is proposed to achieve more packet delivery rate with high location accuracy. It consists of three phases. In first phase, cluster region is formed with less signal delay value and more signal strength. In second phase, neighbour node routing table is constructed and updated with addition of more fields. These fields are reliability, probability of successful transmission of packets and delay. The back off timer is estimated to update the table within a periodical time. In last phase, location status navigator is calculated to increase location accuracy and to maximize the packet delivery ratio. Based on the simulation results, the proposed scheme NCLAR achieves high location accuracy, more packet delivery ratio, less overhead, less delay and high network lifetime.
Copyright © 2018 R. Mahaveerakannan et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.