The rapid standardization and specialization of cloud computing services have led to the development of cloud spot markets on which cloud service providers and customers can trade in near real-time. Frequent changes in demand and supply give rise to spot prices that vary throughout the day. Cloud customers often have temporal flexibility to execute their jobs before a specific deadline. In this paper, the authors apply real options analysis (ROA), which is an established valuation method designed to capture the flexibility of action under uncertainty. They adapt and compare multiple discrete-time approaches that enable cloud customers to quantify and exploit the monetary value of their short-term temporal flexibility. The paper contributes to the field by guaranteeing cloud job execution of variable-time requests in a single cloud spot market, whereas existing multi-market strategies may not fulfill requests when outbid. In a broad simulation of scenarios for the use of Amazon EC2 spot instances, the developed approaches exploit the existing savings potential up to 40 percent – a considerable extent. Moreover, the results demonstrate that ROA, which explicitly considers time-of-day-specific spot price patterns, outperforms traditional option pricing models and expectation optimization.

中文翻译：

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调度云计算现货市场的灵活需求

云计算服务的快速标准化和专业化导致了云现货市场的发展，云服务提供商和客户可以在这些市场上近乎实时地进行交易。需求和供应的频繁变化导致现货价格全天变化。云客户通常具有在特定截止日期之前执行工作的时间灵活性。在本文中，作者应用了实物期权分析 (ROA)，这是一种既定的估值方法，旨在捕捉不确定性下行动的灵活性。他们采用并比较多种离散时间方法，使云客户能够量化和利用其短期时间灵活性的货币价值。该论文通过保证单个云现货市场中可变时间请求的云作业执行对该领域做出了贡献，而现有的多市场策略在出价高时可能无法满足要求。在对 Amazon EC2 Spot 实例使用场景的广泛模拟中，开发的方法利用了高达 40% 的现有节省潜力——相当大的程度。此外，结果表明，明确考虑特定时间的现货价格模式的 ROA 优于传统的期权定价模型和预期优化。