IMBA: IoT-Mist Bat-Inspired Algorithm for Optimising Resource Allocation in IoT Networks

Author:

Almudayni Ziyad1,Soh Ben1ORCID,Li Alice2

Affiliation:

1. Department of Computer Science and Information Technology, School of Computing, Engineering and Mathematical Sciences, La Trobe University, Bundoora, VIC 3086, Australia

2. La Trobe Business School, La Trobe University, Bundoora, VIC 3086, Australia

Abstract

The advent of the Internet of Things (IoT) has revolutionised our interaction with the environment, facilitating seamless connections among sensors, actuators, and humans. Efficient task scheduling stands as a cornerstone in maximising resource utilisation and ensuring timely task execution in IoT systems. The implementation of efficient task scheduling methodologies can yield substantial enhancements in productivity and cost-effectiveness for IoT infrastructures. To that end, this paper presents the IoT-mist bat-inspired algorithm (IMBA), designed specifically to optimise resource allocation in IoT environments. IMBA’s efficacy lies in its ability to elevate user service quality through enhancements in task completion rates, load distribution, network utilisation, processing time, and power efficiency. Through comparative analysis, IMBA demonstrates superiority over traditional methods, such as fuzzy logic and round-robin algorithms, across all performance metrics.

Publisher

MDPI AG

Reference18 articles.

1. Almudayni, Z., Soh, B., and Li, A. (2023). Enhancing Energy Efficiency and Fast Decision Making for Medical Sensors in Healthcare Systems: An Overview and Novel Proposal. Sensors, 23.

2. Almudayni, Z., Soh, B., and Li, A. (2021). Energy Inefficacy in IoT Networks: Causes, Solutions and Enabling Techniques, Springer.

3. Bat algorithm for multi-objective optimisation;Yang;Int. J. Bio-Inspired Comput.,2011

4. MLITS: Multi-Level tasks scheduling model for IoT Service Provisioning;FCAI-Inform. Bull.,2020

5. Barik, R.K., Patra, S.S., Kumari, P., Mohanty, S.N., and Hamad, A.A. (2021, January 17–19). A new energy aware task consolidation scheme for geospatial big data application in mist computing environment. Proceedings of the 2021 8th international Conference on Computing for Sustainable Global Eevelopment (INDIACom), New Delhi, India.

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