Quantum Particle Swarm Optimization and Compressive Sensing-Based Clustering Protocol for Wireless Sensor Networks
Prabhdeep Singh1, Anuj Kumar Gupta2, Ravinder Singh3
1Er. Prabhdeep Singh, Assistant Professor Chandigarh University, Gharuan, Mohali, Punjab, India.
2Dr. Anuj Kumar Gupta, Professor and Head Chandigarh Group of Colleges.
3Dr. Ravinder Singh, lecturer Beant College of Engineering and Technology, Gurdaspur, Punjab, India.

Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 5842-5847 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8737118419/2019©BEIESP | DOI: 10.35940/ijrte.D8737.118419

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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: 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.
Keywords: Data Aggregation, Particle Swarm Optimization, Network Lifetime.
Scope of the Article: Aggregation, Integration, and Transformation.