A metaheuristic method for joint task scheduling and virtual machine placement in cloud data centers

The virtual machine (VM) allocation problem is one of the main issues in cloud data centers. This article proposes a new metaheuristic method to optimize joint task scheduling and VM placement (JTSVMP) center. JTSVMP problem, though composed two parts, namely placement, treated as be resolved by using optimization algorithms (MOAs). proposed co-optimization process aims schedule into which has least execution cost within deadline constraint then place selected on most utilized physical host (PH) capacity constraint. To evaluate performance our process, we compare performances different scenarios, i.e., integrateion MOAs, basic glowworm swarm (GSO), moth-flame (MFGSO) genetic algorithm (GA). Simulation results show that optimizing leads better overall terms minimizing cost, makespan degree imbalance maximizing PHs resource utilization.