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Improved Chameleon Swarm Optimization-Based Load Scheduling for IoT-Enabled Cloud Environment

Manar Ahmed Hamza1,*, Shaha Al-Otaibi2, Sami Althahabi3, Jaber S. Alzahrani4, Abdullah Mohamed5, Abdelwahed Motwakel1, Abu Sarwar Zamani1, Mohamed I. Eldesouki6

1 Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam Bin Abdulaziz University, Al-Kharj, 16278, Saudi Arabia
2 Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, 11671, Saudi Arabia
3 Department of Computer Science, College of Science & Art at Mahayil, King Khalid University, Muhayel Aseer, 62529, Saudi Arabia
4 Department of Industrial Engineering, College of Engineering at Alqunfudah, Umm Al-Qura University, Mecaa, 24382, Saudi Arabia
5 Research Centre, Future University in Egypt, New Cairo, 11845, Egypt
6 Department of Information System, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, AlKharj, Saudi Arabia

* Corresponding Author: Manar Ahmed Hamza. Email:

Computer Systems Science and Engineering 2023, 46(2), 1371-1383.


Internet of things (IoT) and cloud computing (CC) becomes widespread in different application domains such as business, e-commerce, healthcare, etc. The recent developments of IoT technology have led to an increase in large amounts of data from various sources. In IoT enabled cloud environment, load scheduling remains a challenging process which is applied for ensuring network stability with maximum resource utilization. The load scheduling problem was regarded as an optimization problem that is solved by metaheuristics. In this view, this study develops a new Circle Chaotic Chameleon Swarm Optimization based Load Scheduling (C3SOA-LS) technique for IoT enabled cloud environment. The proposed C3SOA-LS technique intends to effectually schedule the tasks and balance the load uniformly in such a way that maximum resource utilization can be accomplished. Besides, the presented C3SOA-LS model involves the design of circle chaotic mapping (CCM) with the traditional chameleon swarm optimization (CSO) algorithm for improving the exploration process, shows the novelty of the work. The proposed C3SOA-LS model computes an objective with the minimization of energy consumption and makespan. The experimental outcome implied that the C3SOA-LS model has showcased improved performance and uniformly balances the load over other approaches.


Cite This Article

M. A. Hamza, S. Al-Otaibi, S. Althahabi, J. S. Alzahrani, A. Mohamed et al., "Improved chameleon swarm optimization-based load scheduling for iot-enabled cloud environment," Computer Systems Science and Engineering, vol. 46, no.2, pp. 1371–1383, 2023.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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