A case for economy grid architecture for service oriented grid computing

Computational Grids are a promising platform for executing large-scale resource intensive applications. However, resource management and scheduling in the Grid environment is a complex undertaking as resources are (geographically) distributed, heterogeneous in nature, owned by different individuals or organizations with their own policies, have different access and cost models, and have dynamically varying loads and availability. This introduces a number of challenging issues such as site autonomy, heterogeneous interaction, policy extensibility, resource allocation or co-allocation, online control, scalability, transparency, resource brokering, and "computational economy". A number of Grid systems (such as Globus and Legion) have addressed many of these issues with exception of a computational economy. We argue that a computational economy is required in order to create a real world scalable Grid because it provides a mechanism for regulating the Grid resources demand and supply. It offers incentive for resource owners to be part of the Grid and encourages consumers to optimally utilize resources and balance timeframe and access costs. We propose a 'computational economy framework' that builds on the existing Grid middleware systems and offers an infrastructure for resource management and trading in the Grid environment. We discuss the usage economic models for resource trading in the Nimrod/G resource broker and present deadline and cost-based scheduling experimental results on the Grid