The Effects of Untruthful Bids on User Utilities and Stability in Computing Markets

Abstract

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 paper we study a real system that is capable of preemptive process migration (i.e. moving jobs across nodes) and that 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 experience degraded performance. The main result and the contribution of this paper is that using the k-th price payment scheme, which is a natural adaptation of the classical second-price scheme, discourages these users from attempting to game the market. 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 several cases.