EEDLABA: Energy-Efficient Distance- and Link-Aware Body Area Routing Protocol Based on Clustering Mechanism for Wireless Body Sensor Network
Source abstract
Abstract
In medical environments, a wireless body sensor network (WBSN) is used to operate remotely, and sensor nodes are employed. It consists of sensor nodes installed on a human body to monitor a patient’s condition, such as heartbeat, temperature, and blood sugar level, and are functionalized and controlled by remote devices. A WBSN consists of nodes that are actually sensors in nature and are operated with a short range of communication. These sensor nodes are fixed with limited computation power and the main concern is energy consumption and path loss. In this paper, we propose a new protocol named energy-efficient distance- and link-aware body area (EEDLABA) with a clustering mechanism and compare it with the current link-aware and energy-efficient body area (LAEEBA) and distance-aware relaying energy-efficient (DARE) routing protocols in a WBSN. The proposed protocol is an extended type of LAEEBA and DARE in which the positive features have been deployed. The clustering mechanism has been presented and deployed in EEDLABA for better performance. To solve these issues in LAEEBA and DARE, the EEDLABA protocol has been proposed to overcome these. Path loss and energy consumption are the major concerns in this network. For that purpose, the path loss and distance models are proposed in which the cluster head (CH) node, coordinator (C) node, and other nodes, for a total of nine nodes, are deployed on a human body. The results have been derived from MATLAB simulations in which the performance of the suggested EEDLABA has been observed in assessment with the LAEEBA and DARE. From the results, it has been concluded that the proposed protocol can perform well in the considered situations for WBSNs.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Wireless Body Area Networks · Molecular Communication and Nanonetworks · Energy Efficient Wireless Sensor Networks
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Information Engineering School, Chang’an University, Xi’an 710061, China
Institute of Computer Science and Information Technology, The University of Agriculture, Peshawar 25000, Pakistan
School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China
Department of Accounting & Information Systems, College of Business & Economics, Qatar University, Doha 2713, Qatar
Department of Computer Science & IT, University of Malakand Pakistan, Dir Lower, Chakdara 1880, Pakistan
Funding
National Key Research and Development Program · National Natural Science Foundation of China
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