Proceedings Abstracts of the Twenty-Fourth International Joint Conference on Artificial Intelligence

Selling Reserved Instances in Cloud Computing / 224
Changjun Wang, Weidong Ma, Tao Qin, Xujin Chen, Xiaodong Hu, Tie-Yan Liu

In this paper, we study the problem of designing new mechanisms for selling reserved instances (al-so referred to as virtual machines) in cloud computing. Unlike the practice in today's clouds in which users only have a few predefined options to reserve instances (i.e., either 1-year reservation or 3-year reservation), we allow users to reserve resources for any length and from any time point in the future. Our goal is to maximize the social welfare. We propose two mechanisms, one for the case where all the jobs are tight (their lengths are exactly their reservation time intervals), and the other for the more general case where jobs are delayable and have some flexibility on their reservations. Both of the mechanisms are prompt in the sense that the acceptance and the payment for a job is determined at the very moment of its arrival. We use competitive analysis to evaluate the performance of our mechanisms, and show that both of the mechanisms have a competitive ratio of O(ln(kT )) under some mild assumption, where k (res. T ) is the maximum ratio between per-instance-hour valuation (res. length) of any two jobs. We then prove that no algorithm can achieve a competitive ratio better than ln(2kT ) under the same assumption. Therefore, our mechanisms are optimal within a constant factor.