Double-Sided Market Mechanism for Trading Cloud Resources.

The increasingly growing supply and demand of infrastructure as a service (IaaS) makes cloud trading possible and desirable in open cloud exchange (OCX) marketplaces. The automation of cloud services trading in such marketplaces is an essential next step in the cloud market evolution. It can be realised with automated agent-based marketplaces with proper market mechanisms to effectively and efficiently trade IaaS. Due to the high problem complexity, associated with complex cloud services configurations, the research conducted so far has not resulted in an efficient and effective market allocation schemes for trading large public clouds. In this paper, we address this problem by designing and evaluating the market mechanisms for trading cloud resources. We propose a combinatorial greedy allocation scheme which operates based on sorted order of candidates for allocation. We design the buyers' pricing mechanism which derives the prices based on critical-value and prove that it is truthful. We propose and analyse two mechanisms for seller pricing: proportional-value pricing and buyer-based pricing. We perform extensive experiments in order to investigate the allocative performance and strategic manipulation opportunity of the proposed mechanisms. The results reveal near-optimal allocation quality in majority of market scenarios. Furthermore, we discover that the buyer-based pricing almost completely eliminates strategic misreporting while the proportional-value pricing can be vulnerable to the seller's price overstating strategy.