Abstract— Cycle-harvesting software on commodity computers is available from a number of companies and a significant part of the Grid computing landscape. However, creating commercial service contracts based on resources made available by cycle-harvesting is a significant challenge for two reasons. Firstly, the characteristics of the harvested resources are inherently stochastic. Secondly, in a commercial environment, purchasers can expect the providers of such contracts to optimize against the quality of service (QoS) definitions provided. These challenges have been successfully met in conventional commodities, e.g. Random Length Lumber, traded on financial exchanges and we draw inspiration from there. The essential point for creating commercially valuable QoS definitions is to guarantee a set of statistical parameters for each and every contract instance. In statistical terms this is the difference between guaranteeing the properties of what is delivered versus the source fro...