Open Access

ARTICLE

Metaheuristic Clustering Protocol for Healthcare Data Collection in Mobile Wireless Multimedia Sensor Networks

G. Kadiravan¹, P. Sujatha¹, T. Asvany¹, R. Punithavathi², Mohamed Elhoseny³, Irina V. Pustokhina⁴, Denis A. Pustokhin⁵, K. Shankar^6,*
1 Department of Computer Science, Pondicherry University, Puducherry, 605014, India
2 Department of Information Technology, M.Kumarasamy College of Engineering, Karur, 639113, India
3 Faculty of Computers and Information, Mansoura University, Egypt
4 Department of Entrepreneurship and Logistics, Plekhanov Russian University of Economics, Moscow, 117997, Russia
5 Department of Logistics, State University of Management, Moscow, 109542, Russia
6 Department of Computer Applications, Alagappa University, Karaikudi, India
* Corresponding Author: K. Shankar. Email:
(This article belongs to this Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)

Computers, Materials & Continua 2021, 66(3), 3215-3231. https://doi.org/10.32604/cmc.2021.013034

Received 22 July 2020; Accepted 23 October 2020; Issue published 28 December 2020

Abstract

Nowadays, healthcare applications necessitate maximum volume of medical data to be fed to help the physicians, academicians, pathologists, doctors and other healthcare professionals. Advancements in the domain of Wireless Sensor Networks (WSN) and Multimedia Wireless Sensor Networks (MWSN) are tremendous. M-WMSN is an advanced form of conventional Wireless Sensor Networks (WSN) to networks that use multimedia devices. When compared with traditional WSN, the quantity of data transmission in M-WMSN is significantly high due to the presence of multimedia content. Hence, clustering techniques are deployed to achieve low amount of energy utilization. The current research work aims at introducing a new Density Based Clustering (DBC) technique to achieve energy efficiency in WMSN. The DBC technique is mainly employed for data collection in healthcare environment which primarily depends on three input parameters namely remaining energy level, distance, and node centrality. In addition, two static data collector points called Super Cluster Head (SCH) are placed, which collects the data from normal CHs and forwards it to the Base Station (BS) directly. SCH supports multi-hop data transmission that assists in effectively balancing the available energy. A detailed simulation analysis was conducted to showcase the superior performance of DBC technique and the results were examined under diverse aspects. The simulation outcomes concluded that the proposed DBC technique improved the network lifetime to a maximum of 16,500 rounds, which is significantly higher compared to existing methods.

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Keywords

Smart sensor environment; healthcare data; multimedia; big data processing; clustering; mobility; energy efficiency

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Citations