A Customer-Oriented Task Scheduling for Heterogeneous Multi-Cloud Environment

Task scheduling is widely studied in various environments such as cluster, grid and cloud computing systems. Moreover, it is NP-Complete as the optimization criteria is to minimize the overall processing time of all the tasks (i.e., makespan). However, minimization of makespan does not equate to customer satisfaction. In this paper, the authors propose a customer-oriented task scheduling algorithm for heterogeneous multi-cloud environment. The basic idea of this algorithm is to assign a suitable task for each cloud which takes minimum execution time. Then it balances the makespan by inserting as much as tasks into the idle slots of each cloud. As a result, the customers will get better services in minimum time. They simulate the proposed algorithm in a virtualized environment and compare the simulation results with a well-known algorithm, called cloud min-min scheduling. The results show the superiority of the proposed algorithm in terms of customer satisfaction and surplus customer expectation. The authors validate the results using two statistical techniques, namely T-test and ANOVA.