A comparison study on node clustering techniques used in target tracking WSNs for efficient data aggregation

Omar Adil Mahdi, Ainuddin Wahid Abdul Wahab, Mohd. Yamani Idna Idris, Ammar MA Abu znaid, Suleman Khan, Yusor Rafid Bahar Al-Mayouf, Nadra Guizani

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregation process. In this paper, we have highlighted the gains of the existing schemes for node clustering‐based data aggregation along with a detailed discussion on their advantages and issues that may degrade the performance. Also, the boundary issues in each type of clustering technique have been analyzed. Simulation results reveal that the efficacy and validity of these clustering‐based data aggregation algorithms are limited to specific sensing situations only, while failing to exhibit adaptive behavior in various other environmental conditions.
Original languageEnglish
Pages (from-to)2663-2676
Number of pages14
JournalWireless Communications and Mobile Computing
Volume16
Issue number16
Early online date5 Aug 2016
DOIs
Publication statusPublished - Nov 2016

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