Information Systems Frontiers

, Volume 14, Issue 4, pp 925–951

GA-based cloud resource estimation for agent-based execution of bag-of-tasks applications

Article

DOI: 10.1007/s10796-011-9327-8

Cite this article as:
Gutierrez-Garcia, J.O. & Sim, K.M. Inf Syst Front (2012) 14: 925. doi:10.1007/s10796-011-9327-8

Abstract

Executing bag-of-tasks applications in multiple Cloud environments while satisfying both consumers’ budgets and deadlines poses the following challenges: How many resources and how many hours should be allocated? What types of resources are required? How to coordinate the distributed execution of bag-of-tasks applications in resources composed from multiple Cloud providers?. This work proposes a genetic algorithm for estimating suboptimal sets of resources and an agent-based approach for executing bag-of-tasks applications simultaneously constrained by budgets and deadlines. Agents (endowed with distributed algorithms) compose resources and coordinate the execution of bag-of-tasks applications. Empirical results demonstrate that the genetic algorithm can autonomously estimate sets of resources to execute budget-constrained and deadline-constrained bag-of-tasks applications composed of more economical (but slower) resources in the presence of loose deadlines, and more powerful (but more expensive) resources in the presence of large budgets. Furthermore, agents can efficiently and successfully execute randomly generated bag-of-tasks applications in multi-Cloud environments.

Keywords

Cloud resource estimationBag-of-tasks applicationsCloud resource managementMultiagent systemsGenetic algorithmsCloud computing

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Information and CommunicationsGwangju Institute of Science and TechnologyGwangjuRepublic of Korea