Journal of Soft Computing and Information Technology

Journal of Soft Computing and Information Technology

Scheduling IoT Tasks in Cloud Computing Using Equilibrium Optimizer Algorithm

Document Type : Persian Original Article

Authors
Mobin Yousefi
Jamal Zarepour-Ahmadabadi
Sepehr Ebrahimi Mood
Department of Computer Science, Yazd University, Yazd, Iran.
Abstract
The Internet of Things (IoT) describes the global and universal connection of objects to the Internet, enabling them to function as smart devices capable of sensing their environment, transmitting data, processing it, and providing feedback. With the expansion of IoT-based applications, the volume of processing requests has increased significantly, posing new challenges for managing and processing this data. Cloud computing enables the execution of complex computations in a short time and at an affordable cost. Efficient resource management and cost reduction can be achieved through metaheuristic algorithms such as the Equilibrium Optimizer (EO), which is inspired by physical principles. In this paper, a multi-objective optimization problem is formulated, encompassing criteria such as makespan, delay, load balancing, stability, energy consumption, and processing cost in an integrated cloud environment. The problem is solved using the EO algorithm, and the results are compared with prominent metaheuristic algorithms. Simulation results demonstrate significant improvements achieved by the proposed algorithm. Specifically, in terms of makespan, the proposed algorithm outperforms PSO, GSA, GWO, and FA by 9%, 6.2%, 9%, and 11%, respectively. Regarding delay reduction, it achieves 8%, 6.7%, 9.4%, and 9% better performance compared to the same algorithms. The algorithm also shows improvements of 1.3% to 2% in processing cost and reductions of 2% to 3.6% in energy consumption. Overall, for simultaneous optimization of all objectives, the proposed algorithm achieves 5.6% to 10% better performance than its competitors. These results highlight the superiority of the proposed algorithm in optimizing multiple objectives and enhancing the efficiency of cloud computing systems.
Keywords
Meta-heuristics algorithms
Internet of things
Equilibrium optimizer
Task scheduling
Makespan
Quality of service
Cloud computing
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Journal of Soft Computing and Information Technology
Volume 13, Issue 4
Winter - March
Winter 2025
Pages 65-79