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An Energy-Efficient Mobile Agent-Based Data Aggregation Scheme for Wireless Body Area Networks

by Gulzar Mehmood1, Muhammad Zahid Khan1, Muhammad Fayaz2, Mohammad Faisal1, Haseeb Ur Rahman1, Jeonghwan Gwak3,4,5,6,*

1 Department of Computer Science & Information Technology, University of Malakand, Chakdara Dir Lower, 23021, Pakistan
2 Department of Computer Science, University of Central Asia, Naryn, Kyrgyzstan
3 Department of Software, Korea National University of Transportation, Chungju, 27469, Korea
4 Department of Biomedical Engineering, Korea National University of Transportation, Chungju, 27469, Korea
5 Department of AI Robotics Engineering, Korea National University of Transportation, Chungju, 27469, Korea
6 Department of IT and Energy Convergence (BK21 FOUR), Korea National University of Transportation, Chungju, 27469, Korea

* Corresponding Author: Jeonghwan Gwak. Email: email

(This article belongs to the Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)

Computers, Materials & Continua 2022, 70(3), 5929-5948. https://doi.org/10.32604/cmc.2022.020546

Abstract

Due to the advancement in wireless technology and miniaturization, Wireless Body Area Networks (WBANs) have gained enormous popularity, having various applications, especially in the healthcare sector. WBANs are intrinsically resource-constrained; therefore, they have specific design and development requirements. One such highly desirable requirement is an energy-efficient and reliable Data Aggregation (DA) mechanism for WBANs. The efficient and reliable DA may ultimately push the network to operate without much human intervention and further extend the network lifetime. The conventional client-server DA paradigm becomes unsuitable and inefficient for WBANs when a large amount of data is generated in the network. Similarly, in most of the healthcare applications (patient's critical conditions), it is highly important and required to send data as soon as possible; therefore, reliable data aggregation in WBANs is of great concern. To tackle the shortcomings of the client-server DA paradigm, the Mobile Agent-Based mechanism proved to be a more workable solution. In a Mobile Agent-Based mechanism, a task-specific mobile agent (code) traverses to the intended sources to gather data. These mobile agents travel on a predefined path called itinerary; however, planning a suitable and reliable itinerary for a mobile agent is also a challenging issue in WBANs. This paper presents a new Mobile Agent-Based DA scheme for WBANs, which is energy-efficient and reliable. Firstly, in the proposed scheme, the network is divided into clusters, and cluster-heads are selected. Secondly, a mobile agent is generated from the base station to collect the required data from cluster heads. In the case, if any fault occurs in the existing itinerary, an alternate itinerary is planned in real-time without compromising the network performance. In our simulation-based validation, we have found that the proposed system delivers significantly improved fault-tolerance and reliability with energy-efficiency and extended network lifetime in WBANs.

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APA Style
Mehmood, G., Khan, M.Z., Fayaz, M., Faisal, M., Rahman, H.U. et al. (2022). An energy-efficient mobile agent-based data aggregation scheme for wireless body area networks. Computers, Materials & Continua, 70(3), 5929-5948. https://doi.org/10.32604/cmc.2022.020546
Vancouver Style
Mehmood G, Khan MZ, Fayaz M, Faisal M, Rahman HU, Gwak J. An energy-efficient mobile agent-based data aggregation scheme for wireless body area networks. Comput Mater Contin. 2022;70(3):5929-5948 https://doi.org/10.32604/cmc.2022.020546
IEEE Style
G. Mehmood, M. Z. Khan, M. Fayaz, M. Faisal, H. U. Rahman, and J. Gwak, “An Energy-Efficient Mobile Agent-Based Data Aggregation Scheme for Wireless Body Area Networks,” Comput. Mater. Contin., vol. 70, no. 3, pp. 5929-5948, 2022. https://doi.org/10.32604/cmc.2022.020546

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cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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