Modeling Resource Prices in Grid Markets

Abstract

Economic principles have been proposed in the literature to underpin the algorithms for managing resources in complex distributed systems such as grids or peer-to-peer systems. Such principles represents a shift away from traditional system-centric management towards user-centric management. It allows each user to formulate an individual valuation of the requested resources by indicating an acceptable price level for their usage. in a computational commodity market, the price for CPU usage is set by equilibrating supply and demand. We investigate the possibility of modeling the price evolution in a computational market with number of techniques (support vector machines, back propagation neural networks and sequence patterns). If such models have predictive capability, they may be used to optimize resource usage. This study extends previous work. It now includes more differentiated resource model with several categories of CPU's differing in their performance levels and it also adds new modeling approaches for the CPU price evolution. Our study indicates no significant difference in the capabilities of the approaches.