Load-balanced Task Scheduling Algorithm using Walrus Optimizer for Cloud Computing

Cloud computing allows users to access software and hardware resources over the network. To achieve cost-effective execution, task scheduling is a major problem. Scheduling tasks is intended to optimize one or more criteria by allocating them to resources. Metaheuristics provide promising solutions for task scheduling by leveraging bio-inspired techniques. In order to solve the task scheduling problem, we present an algorithm that uses a new meta-heuristic algorithm namely WO (Walrus optimizer). The proposed method is known as WOTSA (WO-based Task Scheduling Algorithm). Its main objective is to decrease execution cost, load balancing, resource utilization, and makespan. WOTSA is compared against several popular meta-heuristic algorithms, including FOX (Fox Optimizer), GEO (Golden Eagle Optimizer), ZOA (Zebra Optimization Algorithm), and STOA (Sooty Tern Optimization Algorithm). According to the experimental results, WOTSA improves performance in terms of makespan, resource utilization, execution cost, and degree of resource load balance.