The Effects of Market Demand on Truthfulness in a Computing Resource Options Market

Grid, cluster and cloud computing provide the opportunity for computing resources to be traded as commodities in an open marketplace. An options market for computing resources would allow users to reserve a resource for a fee, and then pay an additional fee later should they actually need to use it. However, a major issue is ensuring that users do not falsify their likely requirements with the objective of reducing costs while keeping their right to use the resource. This paper describes an exploratory simulation implementation of a two-period model that was proposed by Wu, Zhang and Huberman (2008) which they claimed promoted truth-telling among the population of resource-buyers who interact with a Coordinator (a central vendor) of resources. Wu et al. provided a theoretical description and analysis of their model, but presented no empirical analysis of its commercial suitability. Our work, reported in this paper, explores the model's performance where demand for resources is variable and unpredictable. Using techniques similar to replicator dynamics (from studies of evolutionary processes in biology), we explore the behaviour of heterogeneous buyer populations under different market conditions. Through empirical and theoretical analysis, we determine the optimum honesty for which the Coordinator will most effectively prosper across a range of market conditions, and show how this data can be used to protect against risk.