Multi objective trust aware task scheduling algorithm in cloud computing using whale optimization

Abstract

Task Scheduling is an enormous challenge in cloud computing model as to map diverse tasks arises from various sources there should be an efficient scheduling mechanism which provision resources dynamically to users based on their corresponding requests. Ineffective scheduling leads to increase in makespan, energy consumption and violates SLA made between cloud user and service provider thereby quality of service will be degraded and trust on the cloud service provider will be degraded. Trust typically based on quality-of-service parameters such as Availability of virtual resources, Success rate of tasks, Turnaround efficiency of tasks which are included in SLA. In this paper, we designed a Multi objective trust aware scheduler which takes priority of tasks, VMs and schedule tasks to appropriate virtual resources while minimizing makespan, energy consumption. Whale Optimization algorithm used to model our task scheduler. Entire simulation carried out on Cloudsim. Workload used in this simulation is of both fabricated and real-time worklogs captured from HPC2N and NASA. Our proposed approach compared against existing metaheuristic approaches i.e., ACO, GA, PSO approaches. From Simulation results, we observed that there is a significant improvement in makespan, Energy consumption, total running time and trust parameters i.e., Availability, Success rate, Turnaround efficiency.

Keywords

• Task Scheduling
• Makespan
• Energy Consumption
• Trust