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To Sell or Not To Sell: Trading Your Reserved Instances in Amazon EC2 Marketplace

机译:销售或不卖:在亚马逊EC2市场中交易您的保留实例

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Recently, Amazon EC2 offers a reserved instance marketplace, where cloud users can sell their idle reserved instances varying in contract lengths and pricing options for avoiding the waste of their unused reservations. However, without knowing the future demands, it is hard for users to determine how to sell instances optimally, for it would incur more cost if new demands arrive after selling their reserved instances. For dealing with this problem, in this paper we first propose three online selling algorithms to guide cloud users in making decisions whether or not to sell their reservations in Amazon EC2 marketplace while guaranteeing competitive ratios. We prove theoretically that the three proposed online algorithms can guarantee bounded competitive ratios, whose values are specific to the type of reserved instances under consideration. Specifically, for all standard instances (Linux, US East) for 1-year terms in Amazon EC2, compared with a benchmark optimal offline algorithm, our algorithm A_(3T/4) can achieve a ratio of 2-α-α/4 in managing instance purchasing cost, where α is the entitled discount due to reservation and a is the selling discount specified by the user who sells its reservations. Finally, through extensive experiments based on workload data collected from real-world applications, we validate the effectiveness of our online instance selling algorithms by showing that it can bring significant cost savings to cloud users compared with always keeping their reservations in Amazon EC2 reserved instance marketplace.
机译:近日,Amazon EC2提供了一个保留的实例市场,云用户可以在合同长度和定价选项中销售他们的空闲保留的实例,以避免浪费未使用的预订。但是,在不了解未来的需求的情况下,用户很难确定如何最佳地销售实例,因为如果在销售保留实例后,如果新的需求到达,则会产生更多费用。为了处理这个问题,在本文中,我们首先提出了三个在线销售算法,以指导云用户决定是否在保证竞争比率的同时在亚马逊EC2市场上销售他们的预订。从理论上,我们证明这三种在线算法可以保证有界竞争比率,其价值观对所考虑的保留实例的类型特定。具体而言,对于亚马逊EC2的所有标准实例(Linux,USEAD)进行1年的术语,与基准最优离线算法相比,我们的算法A_(3T / 4)可以实现2-α/ 4的比率管理实例购买费用,其中α是由于预订而授权的折扣,A是销售其保留的用户指定的销售折扣。最后,通过基于从现实世界应用收集的工作量数据的广泛实验,我们通过表明它可以将云用户节省大量成本节省的销售算法验证了我们的在线实例销售算法的有效性与始终保留在Amazon EC2保留实例市场中的预订。

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