Multi-Population Ensemble Particle Swarm Optimizer based Energy Efficient Clustering Algorithms for IOT Applications
Author(s) -
Roshnee Adlak,
Pooja Meena
Publication year - 2021
Publication title -
smart moves journal ijoscience
Language(s) - English
Resource type - Journals
ISSN - 2582-4600
DOI - 10.24113/ijoscience.v7i8.409
Subject(s) - computer science , cluster analysis , particle swarm optimization , population , wireless sensor network , protocol (science) , distributed computing , routing protocol , cluster (spacecraft) , matlab , efficient energy use , internet of things , routing (electronic design automation) , algorithm , computer network , machine learning , engineering , embedded system , medicine , demography , alternative medicine , pathology , sociology , electrical engineering , operating system
With the growth of wireless sensor networks (WSN), new technologies like the Internet-of-Things (IoT) are being created. There may be challenges that come because when implementing these application areas in practice. The primary issue is energy utilization while data transmission between these resource restricted sensors. In this work, we present a cluster-based routing protocol for IoT to anticipate energy utilization. Furthermore, for cluster head selection and cluster updation, we presented a multi-population ensemble particle swarm optimizer. The simulation was carried out using the MATLAB platform and demonstrates its superiority over different approaches.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom