Title: Hybrid energy-efficient and QoS-aware algorithm for intelligent transportation system in IoT

Authors: N.N. Srinidhi; G.P. Sunitha; S. Raghavendra; S.M. Dilip Kumar; Victor Chang

Addresses: Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore, India ' Master of Computer Application, Jawaharlal Nehru National College of Engineering, Shivamogga, India ' Vivekananda College of Engineering and Technology, Dakshina Kannada, India ' Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore, India ' IBSS and RIBDA, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, China

Abstract: The Internet of Things (IoT) consists of large amount of energy consuming devices which are pre-figured to progress the effective competence of several industrial applications. It is very much essential to bring down the energy use of every device deployed in the IoT network without compromising the Quality of Service (QoS) for intelligent transportation system. To achieve this objective, a multiobjective optimisation problem to accomplish the aim of estimating the outage performance of clustering process and the network lifetime is devised. Subsequently, a Hybrid Energy Efficient and QoS Aware (HEEQA) algorithm that is a combination of Quantum Particle Swarm Optimisation (QPSO) along with improved Non-dominated Sorting Genetic Algorithm (NSGA) to achieve energy balance among the devices is proposed. NSGA is applied to solve the problem of multiobjective optimisation and the QPSO algorithm is used to find the optima cooperative nodes and cluster head in the clusters.

Keywords: energy efficiency; intelligent transportation system; IoT; network lifetime; QoS.

DOI: 10.1504/IJGUC.2020.110897

International Journal of Grid and Utility Computing, 2020 Vol.11 No.6, pp.815 - 826

Received: 06 Apr 2019
Accepted: 31 May 2019
Published online: 01 Nov 2020 *

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