Multi-Objective Workflow Scheduling using DWGWO algorithm in Cloud Computing

Abstract

This research introduces an approach for workflow scheduling, which assumes diverse quality of service needs in cloud computing. The main objective of the scheduling is to minimise total execution time (TET) and total execution cost (TEC) while scheduling to meet the service level agreement (SLA). Workflow scheduling is an NP-hard problem with significant issues in cloud computing systems. The existing traditional algorithms cannot solve the workflow scheduling problem in polynomial time. This paper proposes a multi-objective system for the workflow scheduling problem using a dynamic weights grey wolf optimisation (DWGWO) algorithm for cloud computing. This algorithm has a balance between exploration and exploitation capabilities.
This algorithm is used to reduce the TET and TEC of the interdependent tasks. The experimental results indicate that the DWGWO algorithm outperformed the ACO and GWO algorithms in terms of TET and TEC.