Dear All,

Kurt Stockinger and I are presenting a tutorial on:
Grid Economy and the Management of Computational and Data Grids
[See below for detailed description]
at the upcoming Global Grid Forum Conference (GGF-11) in Honolulu,
Hawaii on June 6, 2004. Those of you attending GGF-11, you may be
interested in attending our tutorial! Please note that early
registration deadline is May 31 (registration fee US$75 for IEEE
members) and after this date it doubles. Please check out GGF web site
(http://www.ggf.org/) for details on how to register.

Please share this message with colleagues/friends interested in this topic.
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Cheers
Raj
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Tutorial Title:
Grid Economy and the Management of Computational and Data Grids

When: Global Grid Forum (GGF11), Honolulu, June 6, 2004 (Sunday) afternoon.
Time: 1pm - 4:30pm Location: Nautilus 1. 3 hours plus break.
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Level of Tutorial: 25% Introductory, 25% Intermediate, and 50% Advanced.

Tutorial Speakers:

Dr. Rajkumar Buyya
The University of Melbourne, Australia

Dr. Kurt Stockinger
Lawrence Berkeley National Laboratory, USA

Intended Audience:

This tutorial should be of interest to a large number of GGF/HPDC
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) GGF/HPDC 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 from 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 widespread interested in Grid computing from commercial
organisations in recent times 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, Gridbus, GridSim, and OptorSim.

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 and high energy physics
on our experimental Grid testbed having resources located in different
organisations around the world. We also demonstrate how one can make
trade-off QoS requirements such as the deadline and budget.

The last part of the tutorial is dedicated to OptorSim, a Grid simulator
for studying scheduling and replica optimisation strategies. OptorSim
uses an auction model with a Peer-to-Peer infrastructure for buying and
selling files on the Grid. We will discuss the design and implementation
of OptorSim and evaluate the performance for various data intensive jobs
that are typical for large scientific analysis studies. 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.
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