Design of an improved PSO algorithm for workflow scheduling in cloud computing environment
N Sadhasivam, P. Thangaraj · Intelligent Automation & Soft Computing · 2016
AbstractWorkflows have been used to represent a variety of applications involving high processing and storage demands. As a solution to supply this necessity, the cloud computing paradigm has emerged as an on demand resource provider. Cloud computing environments facilitate applications by providing virtualized resources that can be provisioned dynamically. User applications may incur large data retrieval and execution costs when they are scheduled taking into account of ‘execution time’ only. In this work, proposed is an Improved Particle Swarm Optimization (IPSO) to schedule applications in cloud resources. The IPSO is used to minimize the total cost of placement of tasks on available resources. Total cost values are obtained by varying the communication cost between the resources, task dependency cost values, and the execution cost of compute resources. Compared with standard PSO, the results show that the improved algorithm is efficient.