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Journal Article Towards Network Lifetime Enhancement of Resource Constrained IoT Devices in Heterogeneous Wireless Sensor Networks
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Authors
Muhammad Salah ud din, Muhammad Atif Ur Rehman, Rehmat Ullah, Chan-Won Park, Byung Seo Kim
Issue Date
2020-08
Citation
Sensors, v.20, no.15, pp.1-23
ISSN
1424-8220
Publisher
MDPI
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.3390/s20154156
Abstract
The participating nodes in Wireless Sensor Networks (WSNs) are usually resource-constrained in terms of energy consumption, storage capacity, computational capability, and communication range. Energy is one of the major constraints which requires an efficient mechanism that takes into account the energy consumption of nodes to prolong the network lifetime. Particularly in the large scale heterogeneous WSNs, this challenge becomes more critical due to high data collection rate and increased number of transmissions. To this end, clustering is one of the most popular mechanisms which is being used to minimize the energy consumption of nodes and prolong the lifetime of the network. In this paper, therefore, we propose a robust clustering mechanism for energy optimization in heterogeneous WSNs. In the proposed scheme, nodes declare themselves as cluster head (CH) based on available resources such as residual energy, available storage and computational capability. The proposed scheme employs the multi criteria decision making technique named as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) which allows the child nodes to select the optimal CH among several potential CH candidates. Moreover, we also propose mechanisms such as CH-acquaintanceship and CH-friendship in order to prolong the network lifetime. Simulation results show that our proposed scheme minimizes the control overhead, reduces the power consumption and enhances overall lifetime of the network by comparing with the most recent and relevant proposed protocol for WSNs.
KSP Keywords
Cluster Head(CH), Communication range, Data Collection, Decision making technique, Heterogeneous WSN, IoT devices, Number of transmissions, Power Consumption, Residual Energy, Resource-constrained, Robust clustering
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