An Efficient Approach to Genetic Algorithm for Task Scheduling in Cloud Computing Environment

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Shaminder Kaur 1,* Amandeep Verma 1

1. Department of IT, UIET, Panjab University, Chandigarh, India

* Corresponding author.


Received: 18 Jan. 2012 / Revised: 3 May 2012 / Accepted: 15 Jul. 2012 / Published: 8 Sep. 2012

Index Terms

Cloudlets, Cloud Computing, Genetic Algorithm, Makespan, Task-Scheduling


Cloud computing is recently a booming area and has been emerging as a commercial reality in the information technology domain. Cloud computing represents supplement, consumption and delivery model for IT services that are based on internet on pay as per usage basis. The scheduling of the cloud services to the consumers by service providers influences the cost benefit of this computing paradigm. In such a scenario, Tasks should be scheduled efficiently such that the execution cost and time can be reduced. In this paper, we proposed a meta-heuristic based scheduling, which minimizes execution time and execution cost as well. An improved genetic algorithm is developed by merging two existing scheduling algorithms for scheduling tasks taking into consideration their computational complexity and computing capacity of processing elements. Experimental results show that, under the heavy loads, the proposed algorithm exhibits a good performance.

Cite This Paper

Shaminder Kaur, Amandeep Verma, "An Efficient Approach to Genetic Algorithm for Task Scheduling in Cloud Computing Environment", International Journal of Information Technology and Computer Science(IJITCS), vol.4, no.10, pp.74-79, 2012. DOI:10.5815/ijitcs.2012.10.09


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