Tutorial Speakers:

Dr. Rajkumar Buyya

The University of Melbourne, Australia

Short Abstract:

In spite of a number of advances in Grid computing, resource management and application scheduling in such environments continues to be a challenging and complex undertaking. This is due to geographic distribution of Grid resources owned by different organizations with different usage policies, cost models and varying load and availability patterns with time. This tutorial introduces fundamental principles of Grid computing and computational economy and discusses how they impact on emerging Computational and Data Grid technologies. It identifies resource management challenges and presents a Grid Architecture for Computational Economies that can be realized by leveraging existing technologies. It then introduces new challenges and requirements introduced by the Grid Economy on Grid Service Providers (GSPs) and Grid Service Consumers. We present solutions to these challenges based on our experience in designing and developing computational and Data Grid technologies such as Nimrod-G, GridSim, Gridbus (e.g., Grid Market Directory, Grid Bank, Grid Service Broker, Grid Federation) and their utilization in driving eScience and eBusiness applications such as molecular docking, natural language processing, and portfolio analysis.

Intended Audience:

This tutorial should be of interest to a large number of participants from academia, government, and commercial organizations as it focuses on both theory and practice of Grid Economy. They include: (A) students, researchers, and developers interested in creating technologies and applications for Next Generation Grids with focus on Grid economy, (B) participants from commercial organizations interested in creating online Grid marketplace, and (C) users of Grid Computing as we will be offering a live demonstration of current Grid Economy-based technologies and their applications during the tutorial.

Background:

We expect participants to have knowledge of Grid computing at the introductory level. A familiarity of low-level Grid middleware such as Globus Toolkit will be an advantage.

Extended Abstract:

Grids aim at exploiting synergies that result from cooperation of autonomous distributed entities. The synergies that result for Grid cooperation include the sharing, exchange, selection, and aggregation of geographically distributed resources (such as computers, data bases, scientific instruments) for solving large-scale problems in science, engineering, and commerce. For this cooperation to be sustainable, participants need to have (economic) incentive. Therefore, “incentive” mechanisms should be considered as one of key design parameters of Grid architectures.

The Grid community has embraced the integration of commodity Web services and Grid technologies that led to the development of Grid services. The recent widespread interested in Grid computing from commercial organisations is pushing Grid computing towards mainstream computing and Grid services to become valuable economic commodities.

In spite of a number of advances in Grid computing, resource management and scheduling in such environments continues to be a challenging and complex undertaking. The geographic distribution of resources owned by different organizations with different usage policies, cost models and varying load and availability patterns is problematic. The Grid service providers (resource owners) and Grid service consumers (resource users) have different goals, objectives, strategies, and requirements. To address these resource management challenges, a distributed computational economy has been recognized as an effective metaphor for the management of Grid resources as it: (1) enables the regulation of supply and demand for resources, (2) provides economic incentive for Grid service providers, and (3) motives the Grid service consumers to trade-off between deadline, budget, and the required level of quality-of-service. These factors also promote Grid services to become valuable economic commodities.

This tutorial introduces fundamental principles of Grid computing and computational economy and discusses how they impact on emerging Computational and Data Grid technologies. It identifies resource management challenges and presents a Grid Architecture for Computational Economies that can be realized by leveraging existing technologies. It then introduces new challenges and requirements introduced by the Grid Economy on Grid Service Providers (GSPs) and Grid Service Consumers. We present solutions to these challenges based on our experience in designing and developing computational and Data Grid technologies such as Nimrod-G, GridSim, Gridbus (e.g., Grid Market Directory, Grid Bank, Grid Service Broker, Grid Federation).

We introduce (a) Grid Market Directory that allow GSPs to publish their resources and GSC to discover service providers, (b) different Grid economy models for resource management, (c) Grid Bank that provides Grid accounting, authorization, and payment services, (d) Grid Broker that allows users to lease Grid services at runtime based on their price and users’ QoS requirements such as the deadline and budget. We present a number of Grid economy based scheduling algorithms for compute and data intensive applications on Global Grids.

We demonstrate effectiveness of Grid economy in resource management by deploying applications such as molecular docking, natural language processing, and portfolio analysis on our experimental World-Wide Grid testbed. We also demonstrate how one can make trade-off QoS requirements such as the deadline and budget. Results show that the economic algorithms better utilize computational, storage and network resources than traditional algorithms.

We conclude the tutorial by (a) identifying a number of open research topics in Grid computing with a focus on Grid Economy, (b) discussing our thoughts on new opportunities for commercial companies to develop a new Grid technologies/products that help in the realization Grid Exchanges and online Grid marketplaces, and (c) highlighting sociological and intellectual implications of this new Grid paradigm and its impact on the computing marketplace.

Outline of the Tutorial:

• Grid Challenges
• Grid Resource Management Challenges
• A Case for Grid Economy
• Service Oriented Grid Architecture and Grid Economy
• Economic Models for Grid Computing
• A Grid Service Publication Directory
• Virtual Organization Services and Grid Economy
• Grid Service Pricing Issues
• Grid Bank and Grid Accounting Services Architecture
• Grid Resource Broker
• Economic Scheduling Algorithms for Computational Grids
• Economic Scheduling Algorithms for Data Grids
• A Case Study in Grid Economy based Systems such as Nimrod-G and Gridbus
• A Case Study in Creation of Grid Applications from Legacy Software Components
• Demonstration of On Demand Application Deployment and Resource Provisioning within a Grid Economy Environment
• Advance Reservation and Grid Economy
• Grid Simulator
• Evaluation of Optimisation Strategies
• Performance Metrics
• Simulation and Experimental Results
• Open Research Opportunities in Grid Economy
• Summary and Concluding Remarks