Dragonfly soft-computing approach for workload scheduling resource utilization maximization using multi-cloud platform

Abstract

The execution of the real-time workload in the multi-cloud platform with the Service Level Agreement (SLA) requirements is a challenging task. Existing workload scheduling models have addressed issues related to minimizing execution time, cost, and energy with application reliability prerequisite. However, these models are not efficient in maximizing resource utilization under a multi-cloud platform. In addressing resource utilization issues, this paper presents a Workload Scheduling Resource Utilization Maximization (WS-RUM) technique for the multi-cloud platform. The WS-RUM technique leverages a multi-objective such as energy, processing efficiency, and fault-tolerant offloading mechanism employing a dragonfly soft computing algorithm. The WS-RUM improves resource utilization by minimizing both energy and processing time for real-time workload execution in comparison with existing workload execution.