Scheduling Algorithm for Bag-of-Tasks with Due Date Constraints on Hybrid Clouds

Abstract

Bag-of-Tasks (BoT) applications consisting of multiple tasks are widely used in various fields.Different from the traditional deadline constraint in scheduling problems,a due date constraint allows the BoT applications to finish more than a predetermined due date,but would result in the tardiness penalty.In this case,in order to reduce the total cost,the efficient harmony search (EHS) algorithm is proposed to optimize the scheduling tasks in hybrid clouds.The algorithm obtains the initial task sequence by random search and fine tuning.By improving the harmony search steps and the way of generating new harmony memory,a large number of high-quality harmony can be obtained in one search process,which greatly improves the efficiency of harmony search and speeds up the convergence speed of the algorithm.Through continuous iteration,the global optimal solution is obtained,that is to say,BoT application scheduling scheme has the lowest total cost.Experimental results show that compared with other algorithms,the proposed algorithm has significant improvement in performance,which can effectively reduce the total cost of scheduling BoT applications.