Defining the Grid: A Snapshot on the Current View .docDocument Transcript
Defining the Grid: A Snapshot on the Current View
Draft v0.4, 15 June 2006
Swiss Institute of Bioinformatics (Vital-IT)
CH-1015 Lausanne, Switzerland
Active contributions from:
Greg Astfalk, Malcolm Atkinson, Miguel Bote-Lorenzo, Rajkumar Buyya, Lorenzo Cerutti,
Walfredo Cirne, Brian Coghlan , Jose Cunha, Andrea Domenici, Flavia Donno, Dietmar Erwin,
Laurent Falquet, Stephen Flinter, Ian Foster, Geoffrey Fox, Fabrizio Gagliardi, Wolfgang
Gentzsch, Andrew Hanushevsky, Emir Imamagic, Fotis Karayannis, Dan Katz, Dieter
Kranzlmüller, Domenico Laforenza, Erwin Laure, Max Lemke, Rodrigo Fernandes de Mello,
Miron Livny, Gabriel Mateescu, Rodrigo Mello, André Merzky, Reagan Moore, John Morrison,
Maria S. Perez, Ron Perrot, Jean-Marc Pierson, Thierry Priol, Jean Salzemann, Dave Snelling,
Michela Taufer, Domenico Talia, Sathish Vadhiyar, Frank van Lingen, Gregor von Laszewski
The term “Grid” was introduced in early 1998 with the launch of the book “The Grid. Blueprint
for a new computing infrastructure”. Since that time many technological changes have occurred
in both hardware and software. One of the most important ones seems to be the wide acceptance
of Web services. Although the basic Grid idea has not changed much in the last decade, many
people have different ideas about what a Grid really is. In the following article we report on a
survey where we invited many people in the field of Grid computing to give us their current
“Computational Grids are the equivalent to the electrical power Grid” 
“With Web Services we allow a thousand flowers to bloom.
With a Grid we organize the planting and growth of a crop of plants to make harvesting easier.” [MA]
The ideas of Grid computing have been around for much longer than the advent of the famous
book  by Ian Foster and Carl Kesselman. However, the launch of the book started a new era in
computing which created an entire new research field: Grid computing. The original ideas and
definitions compare a computing Grid with the electric power Grid . Actually, the names are
even reflected in European companies such as the Austrian Power Grid, swissgrid, etc.
representing national electricity Grids. In addition to this original vision, Ian Foster gave the
following check list  that was widely accepted:
1) coordinates resources that are not subject to centralized control …
2) … using standard, open, general-purpose protocols and interfaces …
3) … to deliver nontrivial qualities of service
More recently, Ian Foster and Steve Tuecke gave a clear description of what they mean by Grid
and service-oriented architecture . The article also gives clear definitions for utility computing
and on-demand computing and the differences to Grid computing. Grid definitions from other
authors can be found in [8, 9, 10].
In general, computer science sometimes does not have as strict definitions as in the fields of
physics or mathematics which results in the fact that many Grid researchers or people working
with Grid technology have different views on what a Grid is. The most common discrepancies are
in the definition of the hardware (for some a local cluster with a middleware system on top is a
Grid) whereas others believe that a wide-area network connection has to be involved. Other main
discrepancies are on the software side: what actually makes a software a “Grid software”? Is any
kind of middleware using Grid security already a Grid software? etc. Most of us have had similar
discussions in the past which often did not reach a full conclusion.
Due to the recent changes in Web and Grid service technologies, it is often not clear any more
where to draw the border between Web services and Grid services . We are particularly
interested in the current view of Grid researchers and therefore conducted a survey in early 2006
to invite people to express their views. The following article reports on opinions collected from
many researchers in the world-wide Grid community and tries to focus on the basic
characteristics. Having an idea about the current view one can get an impression of how computer
scientists in the Grid domain perceive Grid concepts and how they can be applied to other science
2 Background on the Survey
In spring 2006 we started a survey where we contacted more than 170 Grid researchers all over
the globe to give us their current views on how they define the Grid. The criteria for the survey
was not to influence the answers, i.e. we refrained from giving questions or definitions to either
agree or disagree with. Contacted people should have the maximum freedom in their definitions.
The main guideline was the following:
Try to define what are the important aspects that build a Grid,
what is distinctive, and where are the borders to distributed
computing, Internet computing etc.
Additionally, people were asked to give precise answers of a maximum of 0.5-1 page. More than
40 people responded to this call, and a distilled summary can be found in the following article.
We are aware that the freedom we gave to people results in difficulties in making a summary for
all the opinions obtained. However, it also reflects reality since many researchers have different
views. Given the pool of answers we classify the responses according to a few categories that are
characteristic for computational Grids.
3 Survey Results
One of the main interests of the survey was to find out if people have more or less a common
understanding of a Grid or if there are many conflicting opinions. The result is of course biased in
the sense that we mainly asked researchers working actively in the field. This has the advantage
that we get a more condensed view of what the community thinks rather than the general public.
There is also no obvious way how to evaluate the received answers. We used the following
approach: in a first pass we highlighted all the main keywords that were used to describe the
Grid. Not surprisingly, the many similar words and phrases were used to describe the vision as
well as main characteristics. Therefore, in a second pass a classification method was used to
categorize the answers according to:
1) Grid Vision
2) Differences with respect to other computing domains such as distributed computing,
Internet and Web computing
3) Grid Characteristics
In the following subsections we describe the results of the survey based on the answers we
received. Often we cite people directly indicated by the initials. For details on the actual person
represented by the initial refer to Section 5. Sometimes people agree with certain definitions by
GGF  or CoreGRID . In this case, no direct citations are used.
In more detail, several people describe parts of the Grid, describe characteristics and what is
different with respect to traditional approaches. There are many overlaps and hardly any
contradictions. We consider this as a main message of the paper: the Grid community survey
here is actually rather coherent in what they understand by a Grid.
3.1 The Grid Vision
The overall vision that was given in  has not changed but a few more additions were given
such as the ones below. For instance, “in the Grid vision there is a distinction between (a) the
Grid approach, or paradigm, that represents a general concept and idea to promote a vision for
sophisticated international scientific and business-oriented collaborations and (b) the physical
instantiation of a production Grid based on available resources and services to enable the vision
for sophisticated international scientific and business-oriented collaborations” [GvL].
A Grid infrastructure must provide a set of technical capabilities, as follows :
• “Resource modeling. Describes available resources, their capabilities, and the relationships
between them to facilitate discovery, provisioning, and quality of service management.
• Monitoring and notification. Provides visibility into the state of resources—and notifies
applications and infrastructure management services of changes in state—to enable discovery
and maintain quality of service. Logging of significant events and state transitions is also
needed to support accounting and auditing functions.
• Allocation. Assures quality of service across an entire set of resources for the lifetime of their
use by an application. This is enabled by negotiating the required level(s) of service and
ensuring the availability of appropriate resources through some form of reservation—
essentially, the dynamic creation of a service-level agreement.
• Provisioning, life-cycle management, and decommissioning. Enables an allocated resource to
be configured automatically for application use, manages the resource for the duration of the
task at hand, and restores the resource to its original state for future use.
• Accounting and auditing. Tracks the usage of shared resources and provides mechanisms for
transferring cost among user communities and for charging for resource use by applications
• In addition to that security is an important aspect [GA].
“We can consider the grid as the combination of distributed, high-throughput and
collaborative systems for the effective sharing and distributed coordination of resources
which belong to different control domains [MP]”. Generally, a Grid provides a “distributed
computing power infrastructure. It is supposed to provide researchers (users) with a single entry
point to launch jobs” [LF]. Simply put, Grid means "distributed computing across multiple
administrative domains" [DS]. Sometimes the Grid is also called to be the “software
environment” [GA] that integrates, virtualizes, and manages distributed resources (software
and hardware). Another view is that a Grid is “a very large scale resource management
It is also important to point out that the Grid paradigm can be built with different technologies
which generally also means that there is no such thing as a ‘typical Grid technology’. “Web
services are merely a mechanism (out of many possible mechanisms) that can be used to build a
schedulable grid” [AH]. This is further stressed by the statement that “Grid services are the
current technological approach for the deployment of Grid infrastructures. However, it is very
important to notice that Grid services are the ‘current approach’ since other technologies not
related to services could be employed in order to build Grid infrastructures (e.g. software
components)” [MB]. “Therefore, a multiplicity of technologies is desirable and may need to be
employed concurrently in a heterogeneous Grid” [JM]. Consequently, other biotechnologies that
are not Web service based can and will be used to build Grids.
Others consider the Grid “more a concept or movement rather than a system” [ML] which brings
people together. It is an enabling factor, much “more sociological or cultural rather than
technical” [ML]. Along the same line is the following opinion “I think one should completely
dissociates the Grid definition which is rather a concept to be defined from a user’s point of view,
from technical implementation of the architecture, protocols, services and technology. So
definitely, defining the Grid, would rather be to define a set of features. If we observe a given
unidentified system that can achieve these features, then this system can be defined as a Grid”
To conclude, we also present already commonly agreed definitions by GGF and CoreGRID
Network of Excellence since they were suggested in the survey:
“A system that is concerned with the integration, virtualization, and management of
services and resources in a distributed, heterogeneous environment that supports
collections of users and resources (virtual organizations) across traditional administrative
and organizational domains (real organizations).”
CoreGRID (submitted by [TP] for the CoreGRID executive committee):
"A fully distributed, dynamically reconfigurable, scalable and autonomous infrastructure
to provide location independent, pervasive, reliable, secure and efficient access to a
coordinated set of services encapsulating and virtualizing resources (computing power,
storage, instruments, data, etc.) in order to generate knowledge."
Often, people try to classify different “Grid types” according to their main functionalities but this
classification is not always agreed. However, we try to convey the main ideas. In principle, most
people distinguish between pure Computational Grids and the more enhanced Data Grids.
However, there are also additional classifications such as [DS]:
1) “Collaboration Grids: These Grids involve multiple organizations (institutions) and
individuals, security domains, protocols, discovery mechanisms, etc.” Important aspects are:
• “Widely distributed, virtual organizations (VOs)
• Service level agreements & commercial partnerships
• Business model: increase overall revenue
2) Enterprise Grids: These Grids are in most ways as technically complex as in item 1) above
and involve the complete life cycle of service deployment, provision, management, and
decommissioning, just like Collaboration Grids. However, the multiple domains are either
absent or highly integrated, at least at a political level. These are the production Grids of
major data centers. Important aspects are:
• Virtualization of enterprise resources and applications
• Aggregation and centralization of management
• Business model: reduce total cost of ownership
“In the enterprise security and auditing is even of greater importance” [GA].
3) Cluster Grids: Aimed at high performance/throughput computing, these Grids are mostly
workload scheduling environments. They tend to be static, rather than dynamic like the
above. The services are either generic in nature, e.g. a job submission service, or provide the
same service all the time. They do not typically support the whole service life cycle.” [DS].
However, clusters themselves (if not connected to other clusters) are typically not called a
Another way of categorizing Grids is according to their “geographical distribution, their
organizational scope and resource ownership” [GM]: We can then distinguish between cluster
Grids, campus Grids, enterprise Grids, and global Grids. “A cluster Grid (also called
department Grid) contains resources located at one site within one organization, and belonging to
a single owner. A campus Grid differs from a cluster Grid in that its resources belong to multiple
owners. Unlike campus Grids, enterprise Grids contain resources located at multiple sites.
Finally, global Grids contain resources from multiple organizations” [GM]. Collaboration Grids
are sometimes also called “Beyond Firewall Grids” [DT]. An alternative way of naming different
Grids is “IntraGrid, ExtraGrid and InterGrid” [DT].
Clusters and Grids are sometimes used in the same context but a majority of people surveyed
makes a clear distinction between Grids and clusters: “The key distinction between clusters and
Grids is mainly in the way resources are managed. In case of clusters, the resource allocation is
performed by a centralized resource manager and all nodes cooperatively work together as a
single unified resource. In case of Grids, each node has its own resource manager and don't aim
for providing a single system view" [RB]. Another distinction is that “a Grid is composed by
different administrative domains, whose resources are managed by dynamic virtual
3.1.3 Hardware vs. Software
The physical instantiation of a Grid relies on hardware and software components. Whereas on the
hardware side no particular features are identified (sometimes wide-area network connections are
considered to be an important part of a Grid ), the software side is more distinct. For instance,
“the key distinction between the Grid and other distributed computing is the use of Grid
middleware” [DK]. However, the definition of middleware is also not always commonly agreed
on so others suggest to “avoid the definitions tied to resource or middleware level” [AM].
3.1.4 Basic Services
At least with the advent of the Open Grid Service Architecture it become clear that basically any
conventional “service” (in the meaning of Service Oriented Architecture) can be provided by or
via a Grid. However, the most basic ones are the following: resource selection, scheduling, secure
execution, data management, data integrity and privacy, authentication, and fault recovery.
3.2 Differences/communalities with other computing domains
In the late 1990ies Grid computing emerged as a new domain in computer science although
standard techniques and protocols are taken from related domains such as the Internet, distributed
computing or the database community. However, the Grid computing cannot be discussed in
isolation and has many overlaps with “traditional” domains. Nevertheless, a considerable part of
our surveyed contributors make clear distinctions between Grid computing, distributed computing
and Internet computing. This is also the most controversial part of the entire survey. A short
insight is given here.
3.2.1 Grid vs. Distributed Computing
Some people consider the Grid as a “general” [DT], some as a “special” form of distributed
computing  whereas others think that a distinctive feature is the complexity of the Grid in
several ways, characterized by scalability and transparency:
• “The borders with distributed computing might be defined as the point at which 2-way
contexts begin to be replaced by N-way contexts. By context I think we primarily mean
security, architecture and programming models” [BC].
• Number of organizations involved: “the main differences are the (potential) inter-
organizational characteristics and the looser dependence between the participating
partners (either services or institutions).” [JP]
• Transparency: a Grid should further be “platform agnostic” [SF] and be able to utilize
heterogeneous resources (both hardware and software).
However, we can also find opinions that go in the opposite direction such that there is no “line”
between distributed and Grid computing, rather “they complement each other and are part of each
3.2.2 Grid vs. Internet (Web)
The Grid community has adopted and enhanced many Internet and Web service technologies. For
instance, a Grid service is a Web service with additional features. However, there is no common
agreement about where the border is (if it exists at all) between Internet and Grid computing.
Some argue: “whereas in the Internet (Web) messages are exchanged between two points, a Grid
provides a higher level of abstraction” [DKr]. Furthermore, the vision goes even beyond that and
extends the Internet even more: “similar to today's World Wide Web as our global information
platform, we are building the World Wide Grid to become our global collaboration platform,
connecting computers and storage, applications and data, experiments, instruments, sensors and
other digital devices” [WG].
Along the lines of the metaphor used on the first page, [MA] makes the following distinction: “I
see web services as a computing subsystem that is independently developed and independently
deployed across heterogeneous platforms. They are independently managed services that may
be composed by other services, e.g. via a workflow enactment. There need not be any a priori
design and implementation consistency among the web services to make such composition
easy over and above adherence to WSI-like standards. There is no a priori arrangement to permit
distributed WS management. In the case of a Grid the available services are independently
developed and independently deployed across heterogeneous platforms. However, the designers
of a Grid choose to give up some independence between services; instead services comply with
commonly agreed higher standards, implementing virtual homogeneity. This chosen consistency
is intended to make it easier to deploy software and services across the Grid and easier to
compose services offered by a Grid” [MA]. A Grid typically provides a communication layer that
enables services to communicate with each other which leads to a similar argumentation as the
one above: “… discriminates Grids from the Web, which is a (large) set of independent servers”
A statement more commonly agreed to is that a Grid could be seen as an extension of the Internet.
“Therefore, same basic rule can be applied in the Grid world – integration of heterogeneous
resources can be achieved by using standardized protocols and services. Internet protocols
provide a good basis for linking resources. However, a wider set of standards is needed for
advanced functionalities, such as job execution, data management, security operations, etc.” [EI].
A representative argument to underline that the Grid extends the Internet: “Internet services are
not a different research field but a part of the Grid research “ [MT].
3.3 Grid Characteristics
Grids typically have a set of characteristics. The most dominant ones that people generally agree
on are the following ones:
• Service orientation
• Decentralized control
• Standardization and interoperability
• Access transparency
In addition to that we can identify a set of important topics and aspects:
• Application support
• Computing model
• Licensing model
• Procedures and policies
A commonly agreed aspect of a Grid is sharing of resources in a distributed fashion. Furthermore,
it “spans multiple administrative domains seamlessly” [AM]. It even goes as far as people
define “collaboration Grids” [GF]. It is furthermore important that the collaboration provides
positive synergies among users and service providers. “Done properly, it will result in synergistic,
and potentially emergent, advantages that otherwise will remain unreachable” [JM]. Finally, the
resources should be “shared in a fair way” [FvL].
A Grid is more than the sum of all parts: “A Grid aggregates many resources and therefore
provides an aggregation of the capacity of the individual resources into a higher capacity virtual
resource. The capability of individual resources is preserved. As a consequence, from a global
standpoint the Grid enables running larger applications faster (aggregation capacity), while from
a local standpoint the Grid enables running new applications” [GM]. The aggregation is also
used for “improved performance, higher quality of service, better utilization, and easier access to
data” [FD]. Finally, resources can (or should be) be added dynamically or statically [DE].
Grid services are often provided with a certain interface that hides the complexity of the
underlying resources. This is also known as virtualization which also provides an abstract “layer”
between clients and resources [GA]. Therefore, a Grid provides the “ability to virtualize the sum
of parts into a singular wide-area programming model” [BC]. Virtualization covers both, data
(flat files, databases etc.) and computing resources [WG]. The list of resources to virtualize can
be extended as follows [RM]:
• Grid as workflow virtualization – the use of Grid computing services to execute and manage
processes across multiple compute platforms
• Data Grid as data virtualization – the management of shared collections independently of the
remote storage systems where the data is stored
• Semantic Grid as information virtualization – the ability to reason on inferred attributes from
multiple independent information repositories.
“Virtualization is based on the ability to manage naming conventions, state information, access
methods, and remote operations independently of the remote resource. All of the grid
environments require” [RM]:
• Name space virtualization, logical names for resources, users, files, and metadata that are
independent of the name spaces used on the remote resource.
• Trust virtualization, the ability to manage authentication and authorization independently of
the remote resource.
• Constraint virtualization, the ability to manage access controls independently of the remote
• Access virtualization, the ability to port an arbitrary access mechanism on top of the Grid
middleware. For Data Grids, this is the ability to support access through multiple loadable
libraries (Windows, Perl, Python, C), Java, Digital libraries (DSpace, Fedora, OAI-PMH),
workflow actors (Kepler), Web browsers, etc.
• Network virtualization, the ability to manage transport in the presence of network devices
such as firewalls, load levelers, private virtual networks. This typically requires multiple
protocols to support client-initiated versus server-initiated I/O, bulk operations versus single-
• Latency management, the ability to minimize the number of messages sent over wide area
networks. Examples include execution of procedures at the remote resource when the
complexity (ratio of operations to bytes transmitted) is sufficiently small. The standard case
is data filtering or sub-setting.
• Federation, the ability to interoperate across multiple grid environments. This requires the
ability to share logical name spaces, and Shibboleth-style authentication. Grids establish trust
mechanisms to allow assertions about the authenticity of an individual to be verified from the
Grids provide services, following the concept of a service orient architecture. In the widest sense
“all large scale collections of services can be viewed as Grids” [GF].
A Grid typically consists of “heterogeneous computing resources” [RM], i.e. there is a variety of
different hardware and software components with different performance and latency
We have seen these characteristics already in the 3-point checklist by [IF] but we list it here again
since it was mentioned several times in the survey answers. In other words, “components are
under control of multiple entities, i.e. the key difficulties in Grids lay exactly in not having a
single "owner" of the whole system” [WC], i.e. the resources are “under different ownerships”
[JM]. “One of the requirements of a Grid is the use of distributed control mechanisms” [MP].
Standardization and Interoperability
A Grid “promotes standard interface definitions for services that need to inter-operate to
create a general distributed infrastructure to fulfill users’ tasks and provide user level utilities”
[FD]. “Grids systems that implement one standard must interoperate with Grids that adhere to the
same standard” [DE].
“Grid is exposing the need for increased levels of integration of distinct technologies and for
increased agreements in the standardization of services. The success of the implementation of
the Grid very much depends on these aspects” [JC]. Furthermore, the Grid should provide
uniform access to heterogeneous resources through virtualization [GM].
An even stronger statement on standards and interoperability is the following one: “Any Grid not
based on standards is wasteful. If you consider what I said years ago that "Grid will do for
services what the Web does for data" then if the Grids and their services are not interoperable it
just doesn't work. The rule in Grids for us in HP is 'ruthless standardization.'" [GA]
The Grid “should allow its users to access the computing infrastructure without having to be
intimately aware of the underlying architecture or network topology” [SF]. This is sometimes
considered “the most distinctive aspect of Grid Computing, that is, the levels of transparency
provided for the end-user, through the virtualization of resources” [JC].
Even if Grid implementations and infrastructures sometimes do not solve a “new problem”, it is
often the scale of data, resources and users that contributes to the additional complexity of a Grid.
This is also expressed by the fact that a Grid should be “non-trivial in the sense of what a user
was not able to solve earlier” [SV].
A Grid should be “dynamically reconfigurable” as it is specified in the definition from
Secure access to resources an essential feature of a Grid. Therefore, “authorized users and
applications have a limited number of operations (even none at all)” [JM]. Basically, Grid
security is one of the first things that real Grid users have to deal with and therefore is essential
for any Grid software system that spans multiple administrative domains.
In general, a Grid might support a large variety of different applications. “Applications should
also be part of the Grid and the whole Grid environment (where for environment I mean the
hardware, middleware, and applications) should be data-driven. In particular, it should be able
to react to changes of the system and application behaviors captured by application and system
In general, a Grid supports “several computational models (e.g., batch, interactive, distributed and
parallel computing...)” [AD].
Since Grids originate from the academic community, there is a “global emphasis on open source
software” [FK], which is also followed by several companies that are involved in Grid
Procedures and Policies
Grid users and service providers interact with each other in a similar way like on the open market
where certain rules have to be followed. Therefore, “procedure and polices” [FG] need to be in
place to allow for (coordinated) sharing of resources.
Although there is enthusiasm in the Grid community, not every one believes that the high goals
defined in the overall Grid vision are achieved satisfactory by today’s Grid implementations. This
was also partly evident in the responses we received. The following section reflects on the current
status as well as its relevance to the IT community.
Status and trend
“One of the biggest fears for Grid computing is that it might be seen as today's sexy technology
that will quickly get replaced by tomorrow's sexy technology” [SF]. The Grid researchers and
technologists have to start to point to results/applications that utilize the Grid to solve problems or
enable new applications that would have be unachievable without grid. A similar opinion is as
follows: “Contemporary Grid implementations are still far from initially described image and
from being widely adopted” [EI].
Relevance to wider IT community
In a recent market survey we analyzed mainly the middle European IT market and looked at how
Grid technologies are or can be applied in to a business and/or commercial IT environment .
The major outcome was that many companies are using distributed computing technologies but
are not yet ready to adopt a Grid computing model. This raises the question of why Grid is not yet
more wide-spread in the commercial world? Another question from our survey: “Is there
something that mainstream corporate IT can gain from the Grid, or is it just reserved for the
boffins running nuclear simulations, protein folding experiments, or whatever? How can an IT
manager of a bank or insurance company utilize grid technologies to solve his/her business and
technical problems?” [SF].
The presented survey is one of the first attempts to get an overall view on what the Grid research
community thinks about the definition of a Grid. We previously interviewed a set of companies
on their perception in Grid usability in a business environment  and found that the opinions of
IT leaders in industry are rather diverse with respect to Grid computing. Therefore, it was of
major interest to see what the Grid community itself thinks about the topic. An interesting result
is that there are hardly any big discrepancies seen within the research community.
Init. Name Organization Country
AD Andrea Domenici University of Pisa Italy
AH Andrew Hanushevsky Stanford Linear Accelerator Center USA
AM André Merzky University of Amsterdam The Netherlands
BC Brian Coghlan Trinity College Dublin Ireland
DE Dietmar Erwin Research Centre Jülich Germany
DK Dan Katz Louisiana State University USA
DKr Dieter Kranzlmüller University of Linz / CERN Austria / Switzerland
DL Domenico Laforenza CNR Pisa Italy
DS Dave Snelling Fujitsu UK
DT Domenico Talia University of Calabria Italy
EI Emir Imamagic Universiy of Zagreb Croatia
EL Erwin Laure CERN Switzerland
FD Flavia Donno CERN Switzerland
FG Fabrizio Gagliardi Microsoft Switzerland
FK Fotis Karayannis GRNet Greece
Init. Name Organization Country
FvL Frank van Lingen California Institute of Technology USA
GA Greg Astfalk HP USA
GF Geoffrey Fox Indiana University USA
GM Gabriel Mateescu National Research Council Canada Canada
GvL Gregor von Laszewski Argonne National Lab USA
IF Ian Foster Argonne National Lab / U. Chicago USA
JC Jose Cunha University of Lisbon Portugal
JM John Morrison University College Cork Ireland
JP Jean-Marc Pierson INSA Lyon France
JS Jean Salzemann CNRS Clermont-Ferrant France
LC Lorenzo Cerutti Swiss Institute of Bioinformatics Switzerland
LF Laurent Falquet Swiss Institute of Bioinformatics Switzerland
MA Malcolm Atkinson National e-Science Centre UK
MB Miguel Bote-Lorenzo University of Valladolid Spain
ML Max Lemke European Commission Belgium
ML Miron Livny University of Wisconsin USA
MP Maria S. Perez Technical University of Madrid Spain
MT Michela Taufer University of Texas, al Paso USA
RB Rajkumar Buyya University of Melbourne Australia
RM Reagan Moore San Diego Supercomputing Center USA
RM Rodrigo Ferandes de Mello University of São Paulo Brasil
RP Ron Perrot Queen's University Belfast UK
SF Stephen Flinter Science Foundation Ireland Ireland
SV Sathish Vadhiyar Indian Institute of Science India
TP Thierry Priol CoreGRID France
WC Walfredo Cirne Federal University of Campina Grande Brasil
WG Wolfgang Gentzsch D-Grid Initiative Germany
HS is supported by the EU project EMBRACE Grid which is funded by the European
Commission within its FP6 Programme, under the thematic area "Life sciences, genomics and
biotechnology for health", contract number LUNG-CT-2004-512092.
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