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Jalali Khalil Abadi, Zahra, mansouri, najme, javidi, mohammad masoud, Mohammad Hasani Zade, Behnam. (1404). COTSA: A Load-Balanced Task Scheduling Algorithm using Coati Optimization in Cloud Computing Environment. نشریه مهندسی عمران امیرکبیر, (), -. doi: 10.22060/miscj.2025.23520.5381
Zahra Jalali Khalil Abadi; najme mansouri; mohammad masoud javidi; Behnam Mohammad Hasani Zade. "COTSA: A Load-Balanced Task Scheduling Algorithm using Coati Optimization in Cloud Computing Environment". نشریه مهندسی عمران امیرکبیر, , , 1404, -. doi: 10.22060/miscj.2025.23520.5381
Jalali Khalil Abadi, Zahra, mansouri, najme, javidi, mohammad masoud, Mohammad Hasani Zade, Behnam. (1404). 'COTSA: A Load-Balanced Task Scheduling Algorithm using Coati Optimization in Cloud Computing Environment', نشریه مهندسی عمران امیرکبیر, (), pp. -. doi: 10.22060/miscj.2025.23520.5381
Jalali Khalil Abadi, Zahra, mansouri, najme, javidi, mohammad masoud, Mohammad Hasani Zade, Behnam. COTSA: A Load-Balanced Task Scheduling Algorithm using Coati Optimization in Cloud Computing Environment. نشریه مهندسی عمران امیرکبیر, 1404; (): -. doi: 10.22060/miscj.2025.23520.5381

COTSA: A Load-Balanced Task Scheduling Algorithm using Coati Optimization in Cloud Computing Environment

AUT Journal of Modeling and Simulation
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 24 شهریور 1404
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22060/miscj.2025.23520.5381
نویسندگان
Zahra Jalali Khalil Abadi1؛ najme mansouri* 2؛ mohammad masoud javidi3؛ Behnam Mohammad Hasani Zade4
1Department of Computer Science, Shahid Bahonar University of Kerman, Kerman, Iran
2Shahid Bahonar University of Kerman
3Department of Computer Science ,Shahid Bahonar University,Kerman,Iran
4Computer Science Department, Shahid Bahonar University of Kerman, Kerman, Iran
چکیده
During scheduling process, it is important to respect the constraints given by the jobs and the cloud providers. In addition to maintaining a balance between Quality of Service (QoS), fairness, and efficiency of jobs, scheduling is challenging. This paper aims to propose an efficient algorithm for load-balanced task scheduling in the cloud. Our algorithm uses a new meta-heuristic algorithm called COA (Coati Optimization Algorithm) to solve the task scheduling problem. This method is called COTSA (Coati Optimization-based Task Scheduling Algorithm). Its main goal is to reduce execution costs, load balancing, resource consumption, and makepan. Additionally, experimental results indicate that COTSA contributes to reduced energy consumption and enhanced system scalability and fault tolerance under simulated conditions. These improvements suggest potential suitability for dynamic and large-scale cloud infrastructures, though performance may vary depending on workload characteristics and system configurations. It is compared with Walrus Optimizer (WO), Slap Swarm Algorithm (SSA), Whale Optimization Algorithm (WOA), Zebra Optimization Algorithms (ZOA), Grasshopper Optimization Algorithm (GOA), Sooty Tern Optimization Algorithm (STOA), Golden Eagle Optimizer (GEO), Grey Wolf Optimizer (GWO), Subtraction-Average-Based Optimizer (SABO), and Sand Cat Swarm Optimization (SCSO), which are popular meta-heuristics. Experimental results demonstrate that COTSA reduces makespan by approximately 9%, lowers execution cost by up to 40%, improves resource utilization by around 3%, and enhances load balance by up to 30%, energy consumption about 36%, scalability near 17%, and fault tolerance about 16%, making it a robust and scalable solution for efficient cloud task scheduling.
کلیدواژه‌ها
Cloud Computing؛ Task Scheduling؛ Load Balancing؛ Meta-heuristic؛ Coati Optimization Algorithm
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