A Multi-objective Optimization Scheduling Algorithm in Cloud Computing
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Task scheduling plays a major role in cloud computing that creates a direct impact on performance issues and reduces the system load. In this paper, a novel task scheduling algorithm has proposed for the optimization of multi-objective problem in the cloud environment. It addresses a model to define the demand of resources by a job. It gives a relationship between the resources and costs within a project. The scheduling of multi-objective problem is optimized with the use of ant colony optimization algorithm. The evaluation of the cost and performance of the task has two major constraints considered as makespan and budget’s cost. The two considered constraints will make the algorithm to achieve the optimal result within time and enhance the quality of performance of the system considered. This method is very powerful than other methods with single objectives considered such as makespan, utilization of resources, violation of deadline rate and cost.
KeywordsCloud computing Task Resources Ant colony algorithm Pheromone Fitness function
- 5.Shin S, Kim Y, Lee S (2015) Deadline-guaranteed scheduling algorithm with improved resource utilization for cloud computing. In: Proceedings of 12th annual IEEE consumer communication networking conference (CCNC), pp 814–819Google Scholar
- 7.Van den Bossche R, Vanmechelen K, Broeckhove J (2011) Costefficient scheduling heuristics for deadline constrained workloads on hybrid clouds. In: Proceedings of IEEE 3rd international conference on cloud computing technology science (CloudCom), pp 320–327Google Scholar
- 11.Myneni MB, Narasimha Prasad LV, Naveen Kumar D (2017) Intelligent hybrid cloud data hosting services with effective cost and high availability. Int J Electr Comput Eng 7(4):2176–2189Google Scholar