Abstract—The Cloud Computing has an epochal technology now a day. Managing the incoming request (tasks) to avail-able resources is a challenge for scientist and researchers. This paper proposes a Standard Deviation based Modified Cuckoo Optimization Algorithm (SDMCOA) for task scheduling to efficiently manage the resources. The proposed sys-tem works, in two phases. In the first phase, the sample initial population have been calculated among the available number of task’s population. Rather to take the sample randomly, if an appropriate population’s sample for an experiment are chosen then there are more chances to get optimal result. In second phase, the Cuckoo Optimization Algorithm has been modified with respect to immigration and laying stage. This helps to improve the performance of the system. The experimental results using Cybershake Scientific Workflow shows that the proposed SDMCOA performs better than existing methods BATS, COA in terms of finish time and response time. 
 

Index Terms—Cloud Computing, task scheduling, modified cuckoo optimization, resource utilization

Cite: Mahendra Bhatu Gawali and Subhash K. Shinde, "Standard Deviation Based Modified Cuckoo Optimization Algorithm for Task Scheduling to Efficient Resource Allocation in Cloud Computing," Vol. 8, No. 4, pp. 210-218, November, 2017. doi: 10.12720/jait.8.4.210-218