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Title: Adaptive Scheduling of Cloud Tasks Using Ant Colony Optimization
Authors: Mishra, Sambit Kumar
Sahoo, Bibhudatta
Manikyam, P. Satya
Keywords: Ant Colony Optimization (ACO)
Cloud computing
Task scheduling
Issue Date: 2017
Citation: 3rd International Conference on Communication and Information Processing (ICCIP 2017), Tokyo, Japan, 24 - 26 November, 2017
Abstract: Efficient scheduling of heterogeneous tasks to heterogeneous processors for any application is crucial to attain high performance. Cloud computing provides a heterogeneous environment to perform various operations. The scheduling of user requests (tasks) in the cloud environment is a NP-hard optimization problem. Researchers present various heuristic and metaheuristic techniques to provide the sub-optimal solution to the problem. In this paper, we have proposed an Ant Colony Optimization (ACO) based task scheduling (ACOTS) algorithm to optimize the makespan of the system and reducing the average waiting time. The designed algorithm is implemented and simulated in CloudSim simulator. Results of simulations are compared to Round Robin and Random algorithms which show satisfactory output.
Description: Copyright of this document belongs to proceedings publisher.
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