A Reverse Auction Based Allocation Mechanism in the Cloud Computing Environment

Abstract

In the cloud computing, idle resources can be integrated and allocated to users in the form of service. A resource allocation mechanism is in need to effectively allocate resources, motivate users to join the resource pool and avoid fraud among users. Unfortunately, there is little literature addressing this issue. In this paper, we tackle this issue by introducing microeconomic methods into the resource management and allocation in the cloud environment. With the combination of batch matching and reverse auction, a reverse batch matching auction mechanism is proposed for resource allocation. On that basis, we further introduce the strategy of twicepunishment and the pursuit of QoS (Quality of Service) for the purpose of trading fraud prevention. The winner of the auction is then determined by solving an optimization problem that maximizes a weighted sum of three evaluation criteria, i.e., the market efficiency, user satisfaction and QoS. The optimization solution can be readily derived by an improved immune evolutionary algorithm with the application of Vogel’s approximation method. We also conduct empirical studies to demonstrate the feasibility and effectiveness of the proposed mechanism.