Multi-Objective Task Scheduling Using Smart MPI-Based Cloud Resources

Task Scheduling and Resource Allocation (TSRA) is the key focus of cloud computing. This paper utilizes Smart Message Passing Interface based Approach (SMPIA) Roulette Wheel selection method in order to determine best Alternative Virtual Machine (AVM). To do so, MPI Bus (VMPIB) employed for efficient communication among Machines (VMs) using SMPIA. In this matter, SMPIA applied on different resource allocation task scheduling strategies. MakeSpan (MS) was chosen as an optimization factor solutions with minimum MS value mapping performance reduced consumption. The simulation conducted MATLAB. analysis proves that applying Total Execution Time (TET) allocation, maximum time, increase Utilization (RU), compared non-SMPIA Greedy, Max-Min, Min-Min algorithms. It observed can outperform non-SMPIA. effect more obvious change number workloads increase. Furthermore, regarding TET tasks, significantly reduce starvation problem well lack sufficient resources. addition, approach improves system's than previous methods, what reflects effectiveness proposed concerning (MPI) time network virtualization. mentioned text mining work prepared concurrently after practical evaluation.