Bi-direction adjust heuristic for Workflow Scheduling in Clouds

This paper considers the workflow scheduling problem in Clouds with the hourly charging model and data transfer times. It deals with the allocation of tasks to suitable VM instances while maintaining the precedence constraints on one hand and meeting the workflow deadline on the other. A bi-direction adjust heuristic (BDA) is proposed for the considered problem. Matching of tasks and the VM types is modeled as Mixed Integer Linear programming (MILP) problem and solved using CPLEX at the first stage of BDA. In the second stage, forward and backward scheduling procedures are applied to allocate tasks to VM instances according to the result of the first stage. In the backward scheduling procedure, a priority rule considering the finish time, wasted time fractions and added hours is developed to make appropriate matches of tasks and free time slots. Extensive experimental results show that the proposed BDA heuristic outperforms the existing state-of-the-art heuristic ICPCP in all cases. Further, compared with ICPCP, about 80% percentage of VM renting cost is saved for instances with 900 tasks at most.