Open AccessMobility Aware Weighted Clustering Algorithm for Maximizing IOT Network Lifetime by Harnessing Routing Energy
Author(s) -
N. N. Srinidhi,
Sunil Kumar,
J. Shreyas
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a1885.109119
Subject(s) - computer science , cluster analysis , weighting , node (physics) , routing (electronic design automation) , network packet , computer network , energy (signal processing) , efficient energy use , mobility model , algorithm , distributed computing , engineering , mathematics , medicine , statistics , electrical engineering , structural engineering , machine learning , radiology
The Internet of Things (IoT) is considered as evolved form of Internet in the present scenario. Due to the prediction that large amount of data could be generated by billions of devices connecting to the Internet, requires data to be routed and processed rapidly by harnessing IoT devices energy. Energy constraint IoT devices consume more energy due to mobility of nodes and results in minimizing network lifetime. Motivated by this challenge, mobility aware weighted clustering algorithm (MAWCA) for maximizing IoT network lifetime by harnessing routing energy is proposed to find the optimal cluster head (CH) for mobile nodes in the IoT network. MAWCA considers degree difference of the node, sum of differences between neighbors, cumulative time, nodes mobility and delay in choosing a CH as weighting factor during CH election process. Simulation results shows that the proposed MAWCA outperforms in respect to network energy, delivery ratio, alive nodes count, packet loss ratio and network lifetime in par with similar existing algorithm. The uniqueness of the paper lies in selecting potential cluster head to maximize IoT network lifetime.