A case for economy grid architecture for service oriented grid computing

TLDR

Computational grids promise large‑scale resource‑intensive computing, yet their heterogeneous, distributed nature and diverse ownership create complex challenges in resource management, scheduling, and scalability, with existing systems largely lacking a computational‑economy component. The authors contend that embedding a computational economy is essential to scale grids, as it regulates supply and demand, incentivizes resource owners, and guides consumers toward cost‑effective, timely usage. They propose a computational‑economy framework that extends current grid middleware to provide infrastructure for resource management and trading. Applying this framework to the Nimrod/G broker, they demonstrate deadline‑ and cost‑based scheduling experiments that illustrate the effectiveness of economic models for resource trading on the grid.

Abstract

Computational Grids are a promising platform for executinglarge-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 acomputational economy. We argue that a computationaleconomy is required in order to create a real world scalableGrid because it provides a mechanism for regulating the Gridresources demand and supply. It offers incentive for resourceowners to be part of the Grid and encourages consumers tooptimally utilize resources and balance timeframe and accesscosts. We propose a 'computational economy framework' thatbuilds on the existing Grid middleware systems and offers aninfrastructure for resource management and trading in theGrid environment. We discuss the usage economic models forresource trading in the Nimrod/G resource broker and presentdeadline and cost-based scheduling experimental results onthe Grid.