An Optimized Resource Allocation Model for Cloud Computing Using Ant Colony-based Auction Method

Authors

  • G. B. Hima Bindu The Apollo University, Chittoor-India
  • Kasarapu Ramani Mohan Babu University, Tirupati-India
  • G. Reddy Hemantha Madanapalle Institute of Technology & Science, Madanapalli-India
  • N. Pushpalatha Annamacharya Institute of Technology and Sciences,Tirupati-India
  • I. Suneetha Annamacharya Institute of Technology and Sciences, Tirupati-India
  • P. Harish Annamacharya Institute of Technology and Sciences,Tirupati-India
  • A. B. Manju The Apollo University, Chittoor-India

Keywords:

Cloud Computing, Auction Model, Ant colony method, Resource Optimization, pheromone, Resource scheduling, MakeSpan

Abstract

Cloud computing is a recent technical advancement in the distributed environment. The cloud offers different types of services to clients with rental policies. The increasing number of smart devices is continuously offloading the task to the cloud for processing. The major issues the Cloud environment faces are resource scheduling and cost management. The cost-based model for resource selection and optimization technique for resource scheduling in cloud computing is developed. The auction model proposed is used to select the resources based on the offers provided by the cloud service provider. The ant colony optimization mechanism is applied to schedule the tasks to the resource based on time and cost constraints. The proposed Ant colony-based Auction method is implemented using cloudsim and compared with Ant colony optimization, genetic algorithm, and min-min approach. The results prove that the proposed method is efficient in terms of completion time, energy consumption, and cost required for task processing.

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Published

16.07.2023

How to Cite

Bindu, G. B. H. ., Ramani, K. ., Hemantha, G. R. ., Pushpalatha, N. ., Suneetha, I. ., Harish, P. ., & Manju, A. B. . . (2023). An Optimized Resource Allocation Model for Cloud Computing Using Ant Colony-based Auction Method. International Journal of Intelligent Systems and Applications in Engineering, 11(3), 818–824. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3288

Issue

Vol. 11 No. 3 (2023)

Section

Research Article

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