Title: IoT enabled adaptive clustering based energy efficient routing protocol for wireless sensor networks

Authors: Muhammad Asad; Muhammad Aslam; Yao Nianmin; Naeem Ayoub; Khalid Ibrahim Qureshi; Ehsan Ullah Munir

Addresses: School of Computer Science and Technology, Dalian University of Technology, Dalian, 116000, China ' Department of Computer Science, COMSATS University Islamabad, WAH CANTT, 47040, Pakistan ' School of Computer Science and Technology, Dalian University of Technology, Dalian, 116000, China ' School of Computer Science and Technology, Dalian University of Technology, Dalian, 116000, China ' School of Software Engineering, Dalian University of Technology, Dalian, 116000, China ' Department of Computer Science, COMSATS University Islamabad, WAH CANTT, 47040, Pakistan

Abstract: In this paper, we propose a new internet of things (IoT) enabled multi adaptive clustering (MAC) energy efficient routing protocol for wireless sensor networks (WSNs) to minimise energy dissipation and improve the network performance. This new technique holds the hybrid cluster formation algorithm in which the network topology is divided in two regions where the first region is centralised and the second region is distributed. Both regions contain homogeneous and heterogeneous nodes while the sink is static and located in the centre of both networks. Specifically, proposed IoT enabled MAC routing protocol holds the major three properties: enabling of resources to sensor nodes through IoT, hybrid cluster formation to distribute the network load evenly among sensor nodes and a new mechanism to minimise the energy consumption in long range data transmission. In all of our experiments MAC achieves greater performance than state-of-the-art routing protocols. Moreover, performance evaluation proofs that MAC outperforms in critical network environment.

Keywords: internet of things; IoT; wsnS; wireless sensor networks; energy efficient; routing protocols.

DOI: 10.1504/IJAHUC.2019.102453

International Journal of Ad Hoc and Ubiquitous Computing, 2019 Vol.32 No.2, pp.133 - 145

Received: 09 Dec 2017
Accepted: 30 Apr 2018
Published online: 26 Sep 2019 *

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