Abstract
The accelerated development in Peer-to-Peer (P2P) and Grid computing has
positioned them as promising next generation computing platforms. They enable
the creation of Virtual Enterprises (VE) for sharing resources distributed
across the world. However, resource management, application development and
usage models in these environments is a complex undertaking. This is due to the
geographic distribution of resources that are owned by different organizations
or peers. The resource owners of each of these resources have different usage or
access policies and cost models, and varying loads and availability. In order to
address complex resource management issues, we have proposed a computational
economy framework for resource allocation and for regulating supply and demand
in Grid computing environments. This framework provides mechanisms for
optimizing resource provider and consumer objective functions through trading
and brokering services. In a real world market, there exist various economic
models for setting the price of services based on supply-and-demand and their
value to the user. They include commodity market, posted price, tender and
auction models. In this paper, we discuss the use of these models for
interaction between Grid components to decide resource service value, and the
necessary infrastructure to realize each model. In addition to usual services
offered by Grid computing systems, we need an infrastructure to support
interaction protocols, allocation mechanisms, currency, secure banking, and
enforcement services. We briefly discuss existing technologies that provide some
of these services and show their usage in developing the Nimrod-G grid resource
broker. Furthermore, we demonstrate the effectiveness of some of the economic
models in resource trading and scheduling using the Nimrod/G resource broker
with deadline and cost constrained scheduling for two different optimization
strategies on the World Wide Grid (WWG) testbed that has resources distributed
across five continents.