Quantum Particle Swarm Optimization and Compressive Sensing-Based Clustering Protocol for Wireless Sensor Networks
Author(s) -
Er. Prabhdeep Singh,
Anuj Gupta,
Ravinder Singh
Publication year - 2019
Publication title -
international journal of recent technology and engineering (ijrte)
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d8737.118419
Subject(s) - wireless sensor network , computer science , protocol (science) , cluster analysis , key distribution in wireless sensor networks , particle swarm optimization , computer network , swarm behaviour , energy consumption , mobile wireless sensor network , compressed sensing , battery (electricity) , distributed computing , wireless , wireless network , engineering , telecommunications , electrical engineering , artificial intelligence , machine learning , physics , medicine , power (physics) , alternative medicine , pathology , quantum mechanics
Wireless sensor networks play important role to build various smart systems such as health, medical, military, etc. A wireless sensor network contains tiny sensor nodes to sense information of given environment. But these sensor networks are battery constrained. Therefore, become dead after certain period. Also, the batteries of these sensor nodes are not rechargeable and even not replaceable. Therefore, conserving the energy of these sensor nodes become more challenging. Many researchers have developed various protocols to reduce the energy consumption. But it is still defined as an open area of research. Therefore, in this paper, we have designed a novel quantum particle swarm optimization and compressive sensing-based clustering protocol. Extensive experiments show that the proposed protocol indicates better energy conservation as compared to the competitive protocols.
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