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Truthful Online Auction for Cloud Instance Subletting
Yifei Zhu, Silvery Fu, Jiangchuan Liu and Yong Cui
Simon Fraser University, Simon Fraser University, Simon Fraser University, Tsinghua University

Despite that IaaS users are busy scaling up/out their cloud instances to meet the ever-increasing demands, the dynamics of their demands, as well as the coarse-grained billing options offered by leading cloud providers, have led to substantial instance underutilization in both temporal and spatial domains. This paper systematically examines an instance subletting service, where underutilized instances are leased to others within user-specified periods. It serves as a secondary market that complements the existing instance market of IaaS providers. We identify the unique challenges and opportunities in this secondary market, and design an online auction mechanism to make allocation and pricing decisions for the instances to be sublet. For static supplies of instances, our mechanism guarantees truthfulness and individual rationality with the best possible competitive ratio. We then incorporate a multi-stage discount strategy to gracefully handle dynamic supplies. Extensive trace-driven simulations show that our service achieves significant performance gains in both cost and social welfare. We further validate our modeling assumptions through a container-based prototype implemented over Amazon EC2.