Dynamic bidding in spot market for profit maximization in the public cloud

In public cloud domain, some cloud providers sell surplus resources in the form of spot instances to improve their profits. The average spot price is much cheaper than the on-demand options, which drives more and more cloud users to use spot instances to accelerate their services. However, the cloud user faces a challenge in determining the instance rental and management policy due to the unconventional pricing structure in the spot market and fluctuations in workload and spot price. In this work, we propose a dynamic bidding and resource management algorithm for the cloud user to cut down the instance rental bill in the spot market. The proposed algorithm operates in two timescales, i.e., it determines the bidding, instance rental, and job dispatching policy hourly and makes instances allocation decision in a finer granularity. The advantages of our approach are that it has a simple structure and needs no a priori statistical information of spot price and workload. We prove the optimality of the proposed algorithm and use extensive simulations to study its performance. It is shown that D-bid can save up to almost 70% of the rental cost compared to a baseline nonwork-conserving strategy.