Workflow Scheduling in Cloud Computing Environment Using Bat Algorithm

Abstract

The data handling and processing capabilities of current computing systems are increasing, owing to applications involving the bigger size of data. Hence, the services have become more expensive. To maintain the popularity of cloud environment due to less cost for such requirements, an appropriate scheduling technique is essential, which will decide what task will be executed on which resource in a manner that will optimize the overall costs. This paper presents an application of the Bat Algorithm (BA) for scheduling a workflow application (i.e., a data intensive application), in cloud computing environment. The algorithm is successfully implemented and the results compared with two popular existing algorithms, namely Particle Swarm Optimization (PSO) and Cat Swarm Optimization (CSO). The proposed BA algorithm gives an optimal processing cost with better convergence and fair load distribution.