Resources Renting with Reserved and On-Demand Instances for Cloud Workflow Applications

摘要

Cloud computing enables users to access different resources conveniently based on the "pay-as-you-go" model. However, the unit cost of this on-demand manner are usually higher than the reserved ones. Reallocating some high-usage on-demand instances to reserved instances can save considerable costs when renting resources from the cloud. It is a big challenge to determine the appropriate amount of reserved and on-demand instances in terms of users' requirements. In this paper, we consider deadline constrained workflow scheduling problems to minimize total renting costs with both reserved and on-demand instances. An integer programming model is constructed for the problem under study. A Precedence Tree based Heuristic (PTH) is developed which includes a dynamic initial schedule construction methods. Based on the initial schedule, an improvement procedure is presented. The proposed methods are compared with existing algorithms for the related makespan based workflow scheduling problem. Experimental and statistical results demonstrate the effectiveness and efficiency of the proposed algorithm.