Discount Schemes for the Preemptible Service of a Cloud Platform with Unutilized Capacity

Rapid growth in the cloud industry not only provides tremendous opportunities to cloud providers who have invested heavily in computing capacities, but also leads to low utilization of capacities at times. To alleviate this problem, some providers have launched a low-priority service with the so-called preemptible or spot instances, which allows them to reclaim capacities when necessary. This study focuses on an emerging market segment of customers with fault-tolerant computing jobs, who are the potential users of the preemptible instances. Through an analytical model that captures the underlying supply-demand dynamics, we examine a prevalent discount scheme, which provides all users the same discount, and its impact on key performance measures. Having realized that this is a relatively new market segment and there is room for improvement in discount-scheme designs, we propose an interruption-based discount scheme, which provides compensation to users based on the frequency of interruptions encountered by each of them. Our study suggests that the proposed scheme is fairer than the prevalent scheme from the customers’ perspective and that, in the presence of risk-averse customers, the cloud provider could be better off by adopting the proposed scheme when the supply of the surplus capacity is highly uncertain.

Rapid growth in the cloud services market provides tremendous opportunities to cloud providers who have invested heavily in computing capacities but also has led, at time, to low utilization of capacities. To alleviate this problem, some providers have launched a low-priority service with preemptible (spot) instances, which allows them to attract more customers while keeping the right to reclaim capacities when necessary. In this study, we consider a provider who faces a heterogeneous pool of customers with fault-tolerant (interruptible) computing jobs. We develop an analytical framework that consists of a customer-choice model and a diffusion model to capture the underlying supply-demand dynamics and the resulting preemption probability. First, we examine a commonly used discount scheme for preemptible instances, namely, the uniform discount scheme, and derive the optimal discounted price, given customers’ expectation of the preemption probability. Then, we propose another practical discount scheme, namely, the interruption-based discount scheme, which provides customers with compensation for interruptions. As long as the provider interrupts the preemptible instances randomly and customers are risk neutral, the two discount schemes are equivalent from the provider’s perspective. That said, the proposed scheme is fairer than the uniform discount scheme from the customers’ perspective, as the former provides more discounts to customers who experience more interruptions. Finally, in the presence of risk-averse customers, through a numerical study, we find that the provider would be better off by adopting the uniform discount scheme in an environment in which the level of surplus capacity stays high and stable. Overall, however, the provider would be better off by adopting the proposed scheme when the level of the surplus capacity is moderate and volatile; the relative advantage of the proposed scheme enlarges as the average surplus capacity decreases and its volatility increases.