Our proposed dynamic mechanism is robust, achieves revenue up to 89% of the Optimal Single Price auction, and computes the allocation in polynomial time making ...
Abstract—Modern large-scale computing deployments consist of complex elastic applications running over machine clusters.
A mechanism design and learning approach for revenue maximization on cloud dynamic spot markets. A Tsiourvas, C Bitsakos, I Konstantinou, D Fotakis, N Koziris.
A Mechanism Design and Learning Approach for Revenue Maximization on Cloud Dynamic Spot Markets. IEEE International Conference on Cloud Computing, CLOUD.
We study a stylized revenue maximization problem for a provider of cloud computing services, where the service provider (SP) operates an infinite capacity ...
Missing: Learning Approach
A Mechanism Design and Learning Approach for Revenue Maximization on Cloud Dynamic Spot Markets pp. 427-432. SODA: A Semantics-Aware Optimization Framework ...
This article proposes the Online Extended Consensus Revenue Estimate mechanism, which is envy-free, has a high probability of being truthful, and generates ...
A mechanism design and learning approach for revenue maximization on cloud dynamic spot markets. A Tsiourvas, C Bitsakos, I Konstantinou, D Fotakis, N Koziris.
The fundamental challenge is to design an optimal dynamic pricing policy, with the presence of stochastic demand and perishable resources, so that the expected ...
Abstract—Cloud service pricing plays a pivotal role towards the success of cloud computing. Existing pricing schemes, how- ever, either provide no service ...
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