AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, MMCI   Info

Public Audience

English

60 Minutes

Saarbrücken

Markets of computing resources typically consist of a cluster (or a multi-cluster) and jobs that arrive over time and request computing resources in exchange for payment. In this work we study a real system that is capable of preemptive process migration (i.e. moving jobs across nodes) and uses a market-based resource allocation mechanism for job allocation. Specifically, we formalize our system into a market model and employ simulation-based analysis (performed on real data) to study the effects of users’ behavior on performance and utility. Typically, online settings are characterized by a large amount of uncertainty; therefore, it is reasonable to assume that users will consider simple strategies to game the system. We thus suggest a novel approach to modeling users’ behavior called the Small Risk-aggressive Group model. We show that under this model untruthful users can achieve certain benefits. The main result and the contribution of this work is that the k-th price payment scheme, which is an adaptation of the classical second-price scheme, discourages these users from attempting to game the market by removing the incentives to do that. The preemptive capability makes it possible not only to use the k-th price scheme, but also makes our scheduling algorithm superior to other non-preemptive algorithms. Finally, we design a simple one-shot game to model the interaction between the provider and the consumers. We then show using the same simulation-based analysis that market stability in the form of symmetric Nash-equilibrium is likely to be achieved in some of the cases.

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