TY - GEN
T1 - The effects of untruthful bids on user utilities and stability in computing markets
AU - Shudler, Sergei
AU - Amar, Lior
AU - Barak, Amnon
AU - Mu'alem, Ahuva
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
KW - Market stability
KW - Marketbased scheduling
KW - Pricing
KW - Resource allocation
KW - Strategic behavior
UR - http://www.scopus.com/inward/record.url?scp=77954920236&partnerID=8YFLogxK
U2 - 10.1109/CCGRID.2010.57
DO - 10.1109/CCGRID.2010.57
M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???
AN - SCOPUS:77954920236
SN - 9781424469871
T3 - CCGrid 2010 - 10th IEEE/ACM International Conference on Cluster, Cloud, and Grid Computing
SP - 205
EP - 214
BT - CCGrid 2010 - 10th IEEE/ACM International Conference on Cluster, Cloud, and Grid Computing
T2 - 10th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2010
Y2 - 17 May 2010 through 20 May 2010
ER -