A Multi-Objective Workflow Allocation Strategyin IaaS Cloud Environment

IaaS Cloud provides infrastructural serviceon rental basis on demand by pooling of dynamically provisioned heterogeneous resources to cater the user's workflow applications. Workflows occur in business and industrial applications such as project management, supply chain management, molecular structure, blockchain, business process and require large distributed resource requirement. Workflow mapping while meeting the user's requirements in cloud environment has been proven as NP-Hard. In this work, we proposed a multi-objective workflow allocation (MOWA) strategy cloud to minimize makespan and flowtime simultaneously for IaaS. Level attributes has been taken to preserve precedence constraints. An experimental study has been conducted in MATLAB by producing a set of tradeoff solutions for MOWA and MOHEFT. Further, Pareto front performance measures of the tradeoff solutions are computed and compared. Study shows that the achieved solutions for MOWA are better Pareto-optimal solutions.