Title: An energy efficient optimal path selection technique for IoT using genetic algorithm

Authors: J. Shreyas; Dharamendra Chouhan; Sowmya T. Rao; P.K. Udayaprasad; N.N. Srinidhi; S.M. Dilip Kumar

Addresses: Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, India ' Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, India ' Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, India ' Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, India ' Department of Computer Science and Engineering, Sri Krishna Institute of Technology, Bengaluru, India ' Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, India

Abstract: In the real world, it is essential to establish efficient routes in the internet of things (IoT) since sensor nodes operate mainly on battery and have limited energy. An energy efficient optimal routing technique is proposed to find an optimal path from source to destination. The proposed work obtains the optimal path by selecting an efficient cluster head in the homogeneous IoT network. GA is an optimisation technique that is integrated into the proposed work to achieve the optimal routing benefit. The proposed fitness function enables determining the optimal directions in selecting the multipath routing while exchanging messages from all positions in the network. Extensive mapping of genetic algorithm to proposed IoT routing is presented. Since the proposed method selects an optimal path from source cluster head to the sink, this reduces an energy consumption and improvises the overall network lifetime. The validity of the proposed algorithm is evaluated in the MATLAB and results generate superiority while considering parameters such as energy consumption, end to end delay and number of failed nodes.

Keywords: internet of things; IoT; cluster head; genetic algorithm; routing challenges; optimal route.

DOI: 10.1504/IJIITC.2021.115705

International Journal of Intelligent Internet of Things Computing, 2021 Vol.1 No.3, pp.230 - 248

Received: 01 Nov 2020
Accepted: 10 Dec 2020
Published online: 17 Jun 2021 *

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