A Trust-Aware Multi-Objective Task Scheduling Model Using Whale Optimization Algorithm for Cloud Environment

Task scheduling is a great challenge in the cloud computing model, because in order to draw diverse tasks from different resources, there must be an efficient scheduling mechanism that dynamically allocates resources to users based on their corresponding requests. Inefficient scheduling leads to increased task completion time, energy consumption, and violation of the service level agreement established between the cloud user and the service provider, and as a result, service quality decreases as well as trust in the cloud service provider. Trust is usually defined based on quality of service parameters such as availability of virtual resources, task success rate, and task turnaround efficiency included in the service level agreement. In this paper, a multi-objective trust-aware scheduling algorithm is designed that prioritizes tasks, assigns virtual machines, schedules tasks to appropriate virtual resources, and at the same time, minimizes task completion time and energy consumption. The meta-heuristic whale optimization algorithm is used to model the proposed solution. The results of the proposed approach of this research are compared to similar meta-heuristic approaches, i.e. ant colony optimization, genetic algorithm and particle swarm optimization approach, and the observations show a significant improvement in task completion time, energy consumption, availability, and success rate of task execution.

کلیدواژه ها:

Cloud Computing ، Task Scheduling ، Energy Consumption ، Meta-Heuristic Algorithms ، Whale Optimization Algorithm.