Contemporary Report



C&C Research Laboratories

NEC Europe Ltd.

Rathausallee 10

D-53757 St. Augustin

Germany

Junwei Cao

From Scientific Grids to Business Grids

The State-of-the-Art of Grid Computing

April 2003

From Scientific Grids to Business Grids

The State-of-the-Art of Grid Computing

1. Introduction

Grid computing originated from a new computing infrastructure [Stevens1997, Foster1998] and is now becoming a mainstream technology for large-scale distributed resource sharing [Foster2001] and system integration [Foster2002a]. In this report, a brief overview of the state of the art in grid computing is presented; both academic and industrial efforts towards a global grid infrastructure are surveyed; and future challenges for developing business grids are summarized.

2. Grid Computing

The development of grid computing research can be split into three main phases:

Exploration phase (- 1998). Several early attempts in high performance distributed computing [HPDC], which are now considered as classical projects in grid research, started with different motivation and together built an umbrella termed Computational Grids. These projects include Globus [Foster1997], Legion [Grimshaw1997], NetSolve [Casanova1998], AppLeS [Berman1996], Condor [Litzkow1988], Ninf [Sato1998], Nimrod [Abramson1995] and UNICORE [Romberg1999]. The publication of the book in 1998, The GRID – Blueprint for a New Computing Infrastructure [Foster1998], indicates that the concept of the grid comes into being.

Spreading phase (1998 - 2001). During this period, the concept of the grid has spread very rapidly. Researchers from the high performance computing community and others give annotations to the concepts from different views. Many projects begin to fit their research backgrounds into this new context. The key sign of this phase is that in March 2001, 360 researchers from USA, Europe, and Japan attended the first global grid forum [GGF] held in Amsterdam, which indicates that an international research community on grid computing comes into being.

Exploding phase (2001 -). Entering the new millennium, grid computing is considered to be an active research field with great potential and well known by most of computer scientists. Researchers from different fields of computer science contribute work in this context. Companies support related activities on grid research. Governments begin to make plans to support national grid research and development. A very good selection of latest grid computing research can be found in [Berman2003]. In this report, a brief overview introduction to the state of the art in scientific grid computing research is provided in Section 3, and current industrial efforts and future challenges for developing business grids are summarized in Section 4.

3. Scientific Grids

Most of current grid computing research projects and activities are designed to be used for scientific collaborations. These can be organized into three catalogues: standards and protocols, tools and services, testbeds and applications.

Standards and Protocols

Earlier grid computing tools use self-defined data models and communication protocols that are different from each other and difficult to achieve cooperation. Since the grid is expected to be a globally open computing infrastructure, it has to be implemented in a standard way.

Current standard work on grid computing is led by the GGF and shows a trend to adopt web services standards. Basic web services related standards (or those are potential to become standards) includes XML [Bray2000], WSDL [Christensen2001], WSIL [Ballinger2001], SOAP [Box2000], UDDI [Bellwood2002], BPEL4WS [Curbera2002], etc.

Ongoing grid computing standard works include Open Grid Services Architecture (OGSA) [Foster2002], Grid Security Infrastructure (GSI) [Meder2002], GridFTP [Allcock2002], Grid Resource Allocation Agreement Protocol (GRAAP) [Roy2002], etc.

Tools and Services

Grid services and tools act between grid fabrics (hardware, networks, and operating systems) and grid applications and facilitate application developments for accessing grid resources. These are the most active research area in the grid computing community.

Earlier grid projects are evolving very quickly. Globus is emerging with web services standards starting from the Globus Toolkit 3 (GT3) and the OGSA is becoming the de facto standard of grid computing architecture. Legion is commercialized into the Avaki Corporation [Avaki] that provides data grid solutions. NetSolve and AppLeS are continued as parts of the project Grid Application Development Software [GrADS]. Other projects provide the Globus integration, including Condor-G [Frey2002], Ninf-G [Nakata2003], Nimrod-G [Buyya2000] and UNICORE – Globus interoperability [Rambadt2002].

Numerous tools and services are emerging in recent years. Some new projects that have emphasis on tools and services implementation include Distributed Application and Middleware for Industrial Use of European Networks [DAMIEN], Grid Application Toolkit [GridLab], Grids for Industrial Applications [GRIA], Grid Interoperability Project [Grip], Grid Search and Categorization Engine [GRACE], Grid Datafarm for Petascale Data Intensive Computing [GFarm], and so on.

Here we go through recent years’ HPDC proceedings and summarize related research topics in grid computing tools and services as follows:

Resource management: ClassAd matchmaking framework in Condor [Raman1998], resource management in Legion [Chapin1999], Globus resource co-allocation [Czajkowski1999], the resource and service description (RSD) [Brune1999], a pipelined resource management architecture for PUNCH [Royo2001], active frames for resource selection [López2001], a resource selection service for locating grid resources that match application requirements by extending the Condor matchmaking framework [Liu2002], an enterprise-based grid resource management system [Snell2002], etc.

Scheduling: meta-scheduling models [Weissman1998], task assignment policies [Schroeder2000], implicit coscheduling strategies [Anglano2000], deadline scheduling for client-server systems using the Bricks simulation models [Takefusa2001], a metascheduler for the grid [Vadhiyar2002], decoupling computation and data scheduling in distributed data-intensive applications [Ranganathan2002], etc.

Information services: the Globus MDS [Fitzgerald1997] and information services [Czajkowski2001], information services for the ASCI grid [Johnson2002], InfoGram: a grid service that supports both information queries and job execution [Laszewski2002], etc.

Data and storage management: data management using a meta-data management system (MDMS) and a hierarchical storage system (HSS) [Choudhary1999], a distributed multi-storage resource architecture that can satisfy both performance and capacity requirements by employing multiple storage resources [Shen2000], the Legion I/O model [White2000], flexible access to distributed storage resources [Patten2000], file and object replication in data grids using GDMP [Stockinger2001], sequential data access through meta-data [Terekhov2001], the Kangaroo approach to data movement in Condor [Thain2001], the PUNCH virtual file system [Figueiredo2001], NeST: a flexible software-only storage appliance supporting GridFTP and NFS [Bent2002], load-managed active storage [Wickremesinghe2002], a decentralized, adaptive replica location mechanism [Ripeanu2002], the storage resource broker (SRB) [Rajasekar2002], Mingle: a secure distributed search system [Xie2002], etc.

Programming models and application frameworks: Common Component Architecture (CCA) [Armstrong1999] and corresponding toolkit CAT [Villacis1999], web-based collaborative access and peer-to-peer integration of geographically distributed computational collaboratories [Mann2001], collective interactions and data transfers in PAWS [Keahey2001], interactive and descriptor-based deployment of object-oriented grid applications [Baude2002], the Harness system: a software backplane enabling reconfigurable distributed concurrent computing [Kurzyniec2002], a distributed model coupling framework [Bettencourt2002], etc.

Security: security implications of typical grid computing usage scenarios [Humphrey2001], MyProxy that allows grid portals to use the GSI to interact with grid resources in a standard, secure manner [Novotny2001], security considerations for computational and data grids [Johnston2001], etc.

QoS and adaptation support: QoS-aware resource management [Nahrstedt1999], QoS and Contention-aware multi-resource reservation [Xu2000], adaptive application programming using a tunability interface and a virtual execution environment [Chang2000], QoS based resource discovery in a grid based multimedia environment [Huang2002], A scalable QoS-aware service aggregation model [Gu2002], partitionable services with run-time support for dynamic component deployment [Ivan2002], self-organization frameworks for metacomputing [Sunderam2002], IQ-RUDP: coordinating application adaptation with network transport [He2002], software architecture-based adaptation for grid computing [Cheng2002], adaptive online data compression [Jeannot2002], an automated mechanism for run-time adaptation of application parameters to the local system architecture [Corey2002], etc.

Performance: host load prediction [Dinda1999] and online prediction of the running time of tasks [Dinda2001] using signal processing techniques and , application predictive performance modeling in PUNCH [Kapadia1999], the Bricks performance evaluation system for Ninf using NWS [Takefusa1999], performance evaluation of grid information services [Smith2000], performance evaluation of TCP in grids [Weigle2001], application timeout prediction using the NWS [Allen2002], dynamic right-sizing in FTP (drsFTP) to enhance grid performance in user-space [Gardner2002], using kernel couplings to predict parallel application performance [Taylor2002], performance prediction of the GridFTP [Vazhkudai2002], performance evaluation of web services based implementations of GridRPC [Shirasuna2002], SOAP performance for scientific computing [Chiu2002], FOBS performance comparison with TCP [Dickens2002], etc.

Monitoring and measurement: MPI broadcast measurements in grids [Supinski1999], predicting the CPU availability in NWS [Wolski1999], an agent-based system to automate the execution of monitoring sensors and the collection of event data [Tierney2000], NAS grid benchmark (NGB) [Frumkin2001], a light-weight instrumentation system that can be dynamically activated to collect detailed end-to-end monitoring information from distributed applications [Gunter2002], GridMapper: a tool for monitoring and visualizing the behavior of grid systems [Allcock2002a], etc.

Portals and PSEs: the Cactus code: a problem solving environment for the grid [Allen2000], the ASC grid portal using the Cactus toolkit [Russell2001], the GridPort toolkit for building grid portals [Thomas2001], the Coven framework for construction of PSEs for parallel computers [DeBardeleben2002], etc.

Misc. topics: fault tolerance [Weissman1999], livelock avoidance [Jardine2001], error handling [Thain2002], event management [Eisenhauer2000], commercialization [Kenyon2002], etc.

Each above work actually covers multiple topics. For example, resource management and scheduling are sometimes coupled together. The development of grid portals and PSEs is usually related to corresponding programming models and application frameworks. QoS awareness and application adaptation cannot be supported without other services like performance and monitoring.

The works included in this section are only sourced from the HPDC proceedings. Other grid computing papers can be found in proceedings of ACM/IEEE Supercomputing [SC], IEEE/ACM International Symposium on Cluster Computing and the Grid [CCGrid], IEEE International Parallel and Distributed Processing Symposium [IPDPS], International Workshop on Grid Computing [GRID], IEEE International Heterogeneous Computing Workshop [HCW], and International Euro-Par Conference [Euro-Par] grid computing section, and grid computing special issues of International Journal of High Performance Computing Applications [IJHPCA], Journal of Parallel and Distributed Computing [JPDC], Future Generation Computer Systems [FGCS], Parallel Computing [ParCo], Cluster Computing [CC], Scientific Programming [SP], Parallel Processing Letters [PPL], Concurrency and Computation: Practice and Experience [CCPE], and IEEE Internet Computing [IC]. There is also an upcoming Journal of Grid Computing [JGC].

There are obviously many other research areas that are discussing similar research topics described above. These include cluster computing, peer-to-peer computing, Internet computing, pervasive computing, agent-based computing, etc. The introduction to these works is out of the scope of this report.

Testbeds and Applications

Most current government funded grid projects focus on building grid testbeds and grid enabled applications using existing tools and services (see the section above). These include US grid projects funded by NSF, DOE and NASA, EC/IST FP5/6 projects [EC/IST], UK e-Science Programme [eScience], and so on.

International testbeds: International Virtual Data Grid Laboratory [iVDGL], Data TransAtlantic Grid [DataTAG], EU Data Grid [DataGrid], Application Testbed for European GRID computing [EuroGrid], Grids in Nordic countries [NorduGrid], World Wide Grid [WWG], etc.

National testbeds: TeraGrid [TeraGrid], NASA Information Power Grid [IPG], The National Technology Grid [NCSA], UK National e-Science Centers [NESC], Grids in Netherlands [DutchGrid], INFN Grid in Italy [INFNGrid], Science Information Network in Japan [SINET], Thailand High-performance Advanced Infrastructure Grid [ThaiGrid], Grid Canada [GridCanada], Vega Grid in China [Xu2001], National Grid project in Korea [GFK], etc.

Misc. testbeds: Distance Computing [DisCom], DOE Science Grid [ScienceGrid], Scalable Intracampus Research Grid [SInRG], Beta Grid [BetaGrid], an e-Science Testbed for High Throughput Informatics [Discovery Net], etc.

Physical and chemical applications: Particle Physics Data Grid [PPDG], Grid Physics Network [GriPhyN], Structure-Property Mapping: Combinatorial Chemistry and the Grid [Comb-e-chem], RealityGrid: a tool for investigating condensed matter and materials [RealityGrid], The Grid for UK Particle Physics [GridPP], Fusion Grid [FusionGrid], etc.

Biological and medical applications: Grid Enabled Medical Simulation Services [GEMSS], MammoGrid project for breast cancer screening [MammoGrid], BioGrid [BioGrid], MyGrid [MyGrid], Virtual Laboratory: Molecular Modeling for Drug Design on the World Wide Grid [VirtualLaboratory], NeuroGrid: Brain Activity Analysis on Global Grids [NeuroGrid], Singapore BioMed Grid [BioMed], etc.

Misc. applications: The Earth System Grid [ESG], European Grid of Solar Observations [ESGO], Network for Earthquake Engineering Simulation grid [NEESgrid], human interaction across the grid [AccessGrid], Distributed Aircraft Maintenance Environment [DAME], Grid Enabled Optimisation and DesIgn Search for Engineering [GEODISE], Large scale interactive simulation and visualization [CrossGrid], on-demand flow simulation [FlowGrid], etc.

4. Business Grids

Apart from academic research on scientific grids, grid computing attracted industrial attentions from the beginning and most of current computer companies are putting efforts on building grid-like systems. In this section, industrial activities on grid computing are listed and future challenges on turning business grids into reality are summarized.

Industrial Efforts

In general, hardware providers expect to add grid capabilities to their products and values to their services, and software companies aim to provide unique solutions to address challenges in grid computing. A list of involved companies can be found below, each with a brief description of corresponding grid activities.

Axceleon. Axceleon provides real-time distributed and grid computing solutions [Axceleon]. The latest released product is the EnFuzion 7.2.

Avaki. Avaki is the commercialization of the Legion project, providing solutions of wide-area access to critical resources: processing power, data and applications [Avaki]. The latest released products include the Avaki Data Grid 3.0.

. provides distributed server technology that uses open grid computing protocols in large-scale immersive game networks and supports unlimited numbers of players [Butterfly]. Products include Butterfly Grid 1.5.

Compaq. Compaq announced in November 2001 a Grid Computing Solutions Program which will provide customers with Grid software, computer systems, and custom installation and support services to enable users to share computing, storage, data, software and other resources, through an alliance with Platform Computing [Compaq].

DataSynapse. DataSynapse has deployed its distributed computing solution, LiveCluster, in various customer environments in the financial services and energy sectors to solve compute bottlenecks and enhance performance of mission critical applications [DataSynapse].

Entropia. Entropia’s grid computing solutions harness and manage the untapped processing power of desktop PCs within an enterprise network to process computationally intensive jobs for business and scientific applications [Entropia]. The latest released products include DCGrid 5.1.

Fujitsu. Fujitsu launched in June 2002 a new solution for scientific applications called the Grid Solution for the Sciences, which combines the construction of a Grid system environment, education, and operational support [Fujitsu]. Fujitsu is participating in the UNICORE project.

Gateway. Merging Gateway’s national, private network of nearly 8,000 PCs with United Devices’s Metaprocessor grid technology, Gateway processing on demand service delivers more than 14 teraflops of processing power [Gateway].

GridIron. GridIron aims to make it simple to develop and use software applications with the added speed of parallel processing [GridIron]. Products include GridIron XLR8 1.0.

GridSystems. GridSystems carries out research and development on new grid computing technologies [GridSystems]. Spanish Science and Technology Ministry funds several of GridSystems grid projects. Products include InnerGrid 2.0.

HP. HP utility computing shares the same idea as grid computing, aiming to harness computing power in a distributed fashion [HP]. HP provides customers with grid-enabled systems and grid software solutions from partners such as Platform Computing and Avaki.

IBM. IBM grid computing is the industry-leading supplier of grid solutions, services and expertise [IBM]. IBM autonomic computing is an approach to self-managed computing systems with a minimum of human interference.

Intel. Intel peer-to-peer computing is the sharing of computer resources and services by direct exchange between systems [Intel]. Products include its Peer-to-Peer Accelerator kit for Microsoft .NET.

McAfee. The initiative “Grid Security Services” uses distributed computing techniques to provide real-time dynamic security for customers [McAfee].

Microsoft. Microsoft contributed $1 million to research in grid computing and to the Globus Project. Microsoft UK is participating in the GEODISE project.

NEC. NEC's blade server system will be used as the platform of GSIC (Global Scientific Information and Computing Center in Tokyo Institute of Technology)’s grid computing project [NEC]. NEC C&C research laboratories based in Germany is leading the GEMSS project [CCRLE].

Platform. Platform’s distributed and grid computing software solutions help enterprises effectively connect, measure, manage and optimize enterprise resources [Platform]. Products include Platform LSF [Zhou1992], MultiCluster and Globus.

SGI. SGI works with Platform to deploy Platform grid computing solutions with SGI grid solutions [SGI].

Sony. Sony Computer Entertainment partnered with IBM and to bring the power of grid computing to its PlayStation 2 customers’ online gaming experiences [Sony].

SUN. Sun Microsystems is one of the first companies that provide commercial grid software, e.g. Sun Grid Engine. Sun’s Grid Computing Solutions Program aims to help customers with the adoption and deployment of all levels of grids, providing customers with improved access and utilization of compute resources and increased productivity [SUN].

United Devices. United Devices provide secure grid solutions for any size business and has delivered scaleable and secure deployments in heterogeneous environments in a variety of industries [UD]. Products include MetaProcessor (SDK).

For the latest news on industrial grid computing activities, several news archives can be accessed, including GridComputingPlanet [GCP], GRIDtoday [GRIDtoday], EnterTheGrid [ETG], and GGF news archives.

Future Challenges

While there have been a lot of academic and industrial efforts, there is a long way to go to build a global grid computing infrastructure, especially for business usage. A business grid will bring more challenges than those grids currently being developed for scientific applications. These will include issues on:

Dynamics and adaptability. Grids for business usage will be quite different from those for scientific research and cooperation. For example, in general, partners of a scientific grid are both resource owners and service providers and collaborate with each other using applications that only regular transactions are involved. However, in a business grid, service consumers and providers are always separated and transactions a grid service is required to process will be always irregular. This means a grid service will receive absolutely different computing requirements from different customers all the time and has to provide adaptability to support various and changing QoS with a low cost.

Usage patterns. Business grid users may think of or use the grid in different ways. Some users prefer a grid portal that hides grid details; some users only care about the job submission and result return; some users would also like to know where the job is executed; some users need QoS support along with the job submission; some users require deeper insight and control to the job execution, which needs high level grid services like monitoring, debugging, tracking, checkpointing, error handling, and so on. Different grid usage patterns have to be satisfied as much as possible so as to facilitate grid users to access resources.

Application enabling. Most current research in the grid computing community are focusing on issues that enable basic grid services, which is not enough to provide business grid services, since it is difficult to build complex grid applications directly on top of current core and basic grid services. Application enabling technologies include high level services that hide detailed core and basic grid services and facilitate application development. These may include grid services for performance prediction, business process management, workflow simulation and execution, and even some domain specific services.

Cost estimation. People will always prefer local to grid solutions if the costs are same. A customer must be provided with ways to compare the cost of grid computing with that of local management. A provider cannot expect to build a grid service that a few customers will access quite frequently, since in this case the customers might prefer to build and manage local systems themselves. A success grid service will be those required by large number of customers that access the service only occasionally. Cost estimation will be essential to both service consumers and providers in a business grid.

Legal and organizational politics. According to a recent Platform survey, 89% respondents say that organizational politics are a barrier to implement the grid. Some European legal issues are also potential to prevent grid solutions from being adopted. For example grid processing of sensitive data can be illegal if the responsible persons are considered to lose full control of the data. Organizations are advised to take a service-oriented approach and care more about services than servers. These issues can only be addressed by social studies and efforts.

Other issues on building business grids include security, reliability, accounting, licensing, etc. Most issues mentioned here are not concerned enough in scientific grid development but essential for business grid implementation. To address these challenges, new grid computing paradigms are required and new grid services and standards are to be developed.

References

[Abramson1995] D. Abramson, R. Sosic, J. Giddy, B. Hall, “Nimrod: a Tool for Performing Parameterised Simulations Using Distributed Workstations”, in Proc. of 4th IEEE Int. Symp. on High Performance Distributed Computing, pp. 112-121, 1995. .

[AccessGrid] Access Grid. .

[Allcock2002] W. Allcock, J. Bester, J. Bresnahan, A. Chervenak, L. Liming, S. Meder, S. Tuecke, “GridFTP Protocol Specification”, GridFTP Working Group Document, Global Grid Forum, September 2002. .

[Allcock2002a] W. Allcock, J. Bester, J. Bresnahan, I. Foster, J. Gawor, J. A. Insley, J. M. Link, and M. E. Papka, “GridMapper: A Tool for Visualizing the Behavior of Large-Scale Distributed Systems”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Allen2000] G. Allen, W. Benger, T. Goodale, H. Hege, G. Lanfermann, A. Merzky, T. Radke, E. Seidel, and J. Shalf, “The Cactus Code: A Problem Solving Environment for the Grid”, in Proc. of 9th IEEE Int. Symp. on High Performance Distributed Computing, Pittsburgh, Pennsylvania, USA, 2000.

[Allen2002] M. S. Allen, R. Wolski, and J. S. Plank, “Adaptive Timeout Discovery Using the Network Weather Service”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Anglano2000] C. Anglano, “A Comparative Evaluation of Implicit Coscheduling Strategies for Networks of Workstations”, in Proc. of 9th IEEE Int. Symp. on High Performance Distributed Computing, Pittsburgh, Pennsylvania, USA, 2000.

[Armstrong1999] R. Armstrong, D. Gannon, A. Geist, K. Keahey, S. Kohn, L. McInnes, S. Parker, and B. Smolinski, “Toward a Common Component Architecture for High-Performance Scientific Computing”, in Proc. of 8th IEEE Int. Symp. on High Performance Distributed Computing, Redondo Beach, California, USA, 1999.

[Avaki] Avaki. .

[Axceleon] Axceleon. .

[Ballinger2001] K. Ballinger, P. Brittenham, A. Malhotra, W. A. Nagy, and S. Pharies, “Specification: Web Services Inspection Language (WS-Inspection) 1.0”, November 2001.

[Baude2002] F. Baude, D. Caromel, F. Huet, L. Mestre, and J. Vayssière, “Interactive and Descriptor-Based Deployment of Object-Oriented Grid Applications”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Bellwood2002] T. Bellwood, L. Clément, D. Ehnebuske, A. Hately, M. Hondo, Y. L. Husband, K. Januszewski, S. Lee, B. McKee, J. Munter, and C. von Riegen, “UDDI Version 3.0”, OASIS Published Specification, July 2002. .

[Bent2002] J. Bent, V. Venkataramani, N. LeRoy, A. Roy, J. Stanley, A. C. Arpaci-Dusseau, R. H. Arpaci-Dusseau, and M. Livny, “Flexibility, Manageability, and Performance in a Grid Storage Appliance”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Berman1996] F. Berman, R. Wolski, S. Figueira, J. Schopf, and G. Shao, “Application-level Scheduling on Distributed Heterogeneous Networks”, in Proc. of Supercomputing, 1996. .

[Berman2003] F. Berman, A. J. G. Hey, and G. Fox, Grid Computing: Making The Global Infrastructure a Reality, John Wiley & Sons, 2003.

[BetaGrid] Beta Grid. .

[Bettencourt2002] M. T. Bettencourt, “Distributed Model Coupling Framework”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[BioGrid] BioGrid. .

[BioMed] Singapore BioMed Grid. .

[Box2000] D. Box, D. Ehnebuske, G. Kakivaya, A. Layman, N. Mendelsohn, H. F. Nielsen, S. Thatte, and D. Winer, “Simple Object Access Protocol (SOAP) 1.1”, W3C Note, May 2000. .

[Bray2000] T. Bray, J. Paoli, C. M. Sperberg-McQueen, and E. Maler, “Extensible Markup Language (XML) 1.0 (Second Edition)”, W3C Recommendation, October 2000. .

[Brune1999] M. Brune, A. Reinefeld, and J. Varnholt, “A Resource Description Environment for Distributed Computing Systems”, in Proc. of 8th IEEE Int. Symp. on High Performance Distributed Computing, Redondo Beach, California, USA, 1999.

[Butterfly] . .

[Buyya2000] R. Buyya, D. Abramson, and J. Giddy, “Nimrod/G: An Architecture for a Resource Management and Scheduling System in a Global Computational Grid”, in Proc. of 4th Int. Conf. on High Performance Computing in Asia-Pacific Region, Beijing, China, 2000.

[Casanova1998] H. Casanova, and J. Dongarra, “Applying NetSolve’s Network-Enabled Server”, IEEE Computational Science & Engineering, Vol. 5, No. 3, pp. 57-67, 1998. .

[CC] Cluster Computing. .

[CCGrid] IEEE/ACM International Symposium on Cluster Computing and the Grid. .

[CCPE] Concurrency and Computation: Practice and Experience. .

[CCRLE] C&C Research Laboratories, NEC Europe Ltd. .

[Chang2000] F. Chang, and Vijay Karamcheti, “Automatic Configuration and Run-time Adaptation of Distributed Applications”, in Proc. of 9th IEEE Int. Symp. on High Performance Distributed Computing, Pittsburgh, Pennsylvania, USA, 2000.

[Chapin1999] S. J. Chapin, D. Katramatos, J. Karpovich, and A. Grimshaw, “Resource Management in Legion”, Future Generation Computer Systems, Vol. 15, No. 5, pp. 583-594, 1999.

[Cheng2002] S. Cheng, D. Garlan, B. Schmerl, P. Steenkiste, and N. Hu, “Software Architecture-Based Adaptation for Grid Computing”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Chiu2002] K. Chiu, M. Govindaraju, and R. Bramley, “Investigating the Limits of SOAP Performance for Scientific Computing”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Choudhary1999] A. Choudhary, M. Kandemir, H. Nagesh, J. No, X. Shen, V. Taylor, S. More, and R. Thakur, “Data Management for Large-Scale Scientific Computations in High Performance Distributed Systems”, in Proc. of 8th IEEE Int. Symp. on High Performance Distributed Computing, Redondo Beach, California, USA, 1999.

[Christensen2001] E. Christensen, F. Curbera, G. Meredith, and S. Weerawarana, “Web Services Description Language (WSDL) 1.1”, W3C Note, March 2001. .

[Comb-e-chem] Structure-Property Mapping: Combinatorial Chemistry and the Grid. .

[Compaq] Compaq Grid Computing Program; Aligns with Platform for Grid-Enabled Solutions. .

[Corey2002] I. R. Corey, J. R. Johnson, and J. S. Vetter, “Local Discovery of System Architecture - Application Parameter Sensitivity: An Empirical Technique for Adaptive Grid Applications”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[CrossGrid] CrossGrid. .

[Curbera2002] F. Curbera, Y. Goland, J. Klein, F. Leymann, D. Roller, S. Thatte, S. Weerawarana, “Business Process Execution Language for Web Services, Version 1.0”, July 2002. .

[Czajkowski1999] K. Czajkowski, I. Foster, and C. Kesselman, “Resource Co-Allocation in Computational Grids”, in Proc. of 8th IEEE Int. Symp. on High Performance Distributed Computing, Redondo Beach, California, USA, 1999.

[Czajkowski2001] K. Czajkowski, C. Kesselman, S. Fitzgerald, and I. Foster, “Grid Information Services for Distributed Resource Sharing”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[DAME] Distributed Aircraft Maintenance Environment.

[DAMIEN] Distributed Application and Middleware for Industrial Use of European Networks. .

[DataGrid] EU Data Grid. .

[DataSynapse] DataSynapse. .

[DataTAG] Data TransAtlantic Grid. .

[DeBardeleben2002] N. A. DeBardeleben, W. B. Ligon III, S. Pandit, and D. C. Stanzione Jr., “Coven — A Framework for High Performance Problem Solving Environments”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Dickens2002] P. M. Dickens, and W. Gropp, “An Evaluation of Object-Based Data Transfers on High Performance Networks”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Dinda1999] P. A. Dinda, and D. R. O'Hallaron, “An Evaluation of Linear Models for Host Load Prediction”, in Proc. of 8th IEEE Int. Symp. on High Performance Distributed Computing, Redondo Beach, California, USA, 1999.

[DisCom] Distance Computing. .

[Discovery Net] An e-Science Testbed for High Throughput Informatics. .

[DutchGrid] Grids in Netherlands. .

[EC/IST] European Commission / Information Society Technologies. .

[Eisenhauer2000] G. Eisenhauer, F. E. Bustamante, and K. Schwan, “Event Services for High Performance Computing”, in Proc. of 9th IEEE Int. Symp. on High Performance Distributed Computing, Pittsburgh, Pennsylvania, USA, 2000.

[Entropia] Entropia PC Grid Computing. .

[eScience] UK e-Science Programme. .

[ESG] The Earth System Grid. .

[ESGO] European Grid of Solar Observations. .

[ETG] Enter The Grid. .

[EuroGrid] Application Testbed for European GRID computing. .

[Euro-Par] International Euro-Par Conference. .

[FGCS] Future Generation Computer Systems. .

[Figueiredo2001] R. J. Figueiredo, N. H. Kapadia, and J. A. B. Fortes, “The PUNCH Virtual File System: Seamless Access to Decentralized Storage Services in a Computational Grid”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[Fitzgerald1997] S. Fitzgerald, I. Foster, C. Kesselman, G. von Laszewski, W. Smith, and S. Tuecke, “A Directory Service for Configuring High-Performance Distributed Computations”, in Proc. of 6th IEEE Symp. on High Performance Distributed Computing, Portland, OR, USA, pp. 365-375, 1997.

[FlowGrid] FlowGrid. .

[Foster1997] I. Foster, and C. Kesselman, “Globus: A Metacomputing Infrastructure Toolkit”, Int. J. Supercomputer Applications, Vol. 11, No. 2, pp. 115-128, 1997. .

[Foster1998] I. Foster, and C. Kesselman, The Grid: Blueprint for a New Computing Infrastructure, Morgan-Kaufmann, 1998.

[Foster2001] I. Foster, C. Kesselman, and S. Tuecke, “The Anatomy of the Grid: Enabling Scalable Virtual Organizations”, Intl. J. High Performance Computing Applications, Vol. 15, No. 3, pp. 200-222, 2001.

[Foster2002] I. Foster, C. Kesselman, J. M. Nick, and S. Tuecke, “The Physiology of the Grid: an Open Grid Services Architecture for Distributed Systems Integration”, Open Grid Service Infrastructure Working Group, Global Grid Forum, June 2002. .

[Foster2002a] I. Foster, C. Kesselman, J. M. Nick, and S. Tuecke, “Grid Services for Distributed System Integration”, IEEE Computer, Vol. 35, No. 6, pp. 37-46, 2002.

[Frey2002] J. Frey, T. Tannenbaum, M. Livny, I. Foster, and S. Tuecke, “Condor-G: a Computation Management Agent for Multi-institutional Grids”, Cluster Computing, Vol. 5, No. 3, pp. 237-246, 2002.

[Frumkin2001] M. Frumkin, and R. F. Van der Wijngaart, “NAS Grid Benchmarks: A Tool for Grid Space Exploration”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[Fujitsu] Fujitsu Introduces Grid Solution for the Sciences. .

[FusionGrid] Fusion Grid. .

[Gardner2002] M. K. Gardner, W. Feng, and M. Fisk, “Dynamic Right-Sizing in FTP (drsFTP): Enhancing Grid Performance in User-Space”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Gateway] Gateway Processing on Demand: processing power when you need it. .

[GCP] Grid Computing Planet. .

[GEMSS] Grid Enabled Medical Simulation Services. .

[GEODISE] Grid Enabled Optimisation and DesIgn Search for Engineering. .

[GFarm] Grid Datafarm for Petascale Data Intensive Computing. .

[GFK] Grid Forum Korea. .

[GGF] Global Grid Forum.

[GRACE] Grid Search and Categorization Engine. .

[GrADS] Grid Application Development Software. .

[GRIA] Grids for Industrial Applications.

[GRID] International Workshop on Grid Computing. .

[GridCanada] Grid Canada. .

[GridIron] GridIron Software. .

[GridLab] Grid Application Toolkit. .

[GridPP] The Grid for UK Particle Physics. .

[GridSystems] GridSystems. .

[GRIDtoday] GRIDtoday. .

[Grimshaw1997] A. S. Grimshaw, W. A. Wulf, and the Legion team, “The Legion Vision of a Worldwide Virtual Computer”, Communications of the ACM, Vol. 40, No. 1, pp. 39-45, 1997. .

[Grip] Grid Interoperability Project. .

[GriPhyN] Grid Physics Network. .

[Gu2002] X. Gu, and K. Nahrstedt, “A Scalable QoS-Aware Service Aggregation Model for Peer-to-Peer Computing Grids”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Gunter2002] D. Gunter, B. Tierney, K. Jackson, J. Lee, and M. Stoufer, “Dynamic Monitoring of High-Performance Distributed Applications”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[HCW] IEEE International Heterogeneous Computing Workshop. .

[He2002] Q. He, and K. Schwan, “IQ-RUDP: Coordinating Application Adaptation with Network Transport”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[HP] HP and Grid Computing. .

[HPDC] IEEE International Symposium on High Performance Distributed Computing. .

[Huang2002] Y. Huang, and N. Venkatasubramanian, “QoS-Based Resource Discovery in Intermittently Available Environments”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Humphrey2001] M. Humphrey, and M. R. Thompson, “Security Implications of Typical Grid Computing Usage Scenarios”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[IBM] IBM Grid Computing. .

[IC] IEEE Internet Computing. .

[IJHPCA] International Journal of High Performance Computing Applications. .

[INFNGrid] INFN Grid. .

[Intel] Intel P2P. .

[IPDPS] IEEE International Parallel and Distributed Processing Symposium. .

[IPG] NASA Information Power Grid. .

[Ivan2002] A. Ivan, J. Harman, M. Allen, and V. Karamcheti, “Partitionable Services: A Framework for Seamlessly Adapting Distributed Applications to Heterogeneous Environments”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[iVDGL] International Virtual Data Grid Laboratory. .

[Jardine2001] J. Jardine, Q. Snell, and M. Clement, “Livelock Avoidance for Meta-Schedulers”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[Jeannot2002] E. Jeannot, B. Knutsson, and M. Bj?rkman, “Adaptive Online Data Compression”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[JGC] Journal of Grid Computing. .

[Johnson2002] W. R. Johnson, “Design and Implementation of Secured Information Services for the ASCI Grid”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Johnston2001] W. E. Johnston, S. Talwar, and K. R. Jackson, “Overview of Security Considerations for Computational and Data Grids”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[JPDC] Journal of Parallel and Distributed Computing. .

[Kapadia1999] N. H. Kapadia, J. A. B. Fortes, and C. E. Brodley, “Predictive Application-Performance Modeling in a Computational Grid Environment”, in Proc. of 8th IEEE Int. Symp. on High Performance Distributed Computing, Redondo Beach, California, USA, 1999.

[Keahey2001] K. Keahey, P. Fasel, and S. Mniszewski, “PAWS: Collective Interactions and Data Transfers”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[Kenyon2002] C. Kenyon, and G. Cheliotis, “Architecture Requirements for Commercializing Grid Resources”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Kurzyniec2002] D. Kurzyniec, V. Sunderam, and M. Migliardi, “On the Viability of Component Frameworks for High Performance Distributed Computing: A Case Study”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Laszewski2002] G. von Laszewski, J. Gawor, C. J. Pe?a, and I. Foster, “InfoGram: A Grid Service that Supports Both Information Queries and Job Execution”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Litzkow1988] M. Litzkow, M. Livny, and Matt Mutka, “Condor - A Hunter of Idle Workstations”, in Proc. of 8th Int. Conf. on Distributed Computing Systems, pp. 104-111, 1988. .

[Liu2002] C. Liu, L. Yang, I. Foster, and D. Angulo, “Design and Evaluation of a Resource Selection Framework for Grid Applications”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[López2001] J. C. López, and D. R. O'Hallaron, “Evaluation of a Resource Selection Mechanism for Complex Network Services”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[MammoGrid] MammoGrid. .

[Mann2001] V. Mann, and M. Parashar, “Middleware Support for Global Access to Integrated Computational Collaboratories”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[McAfee] Unveils Security ‘grid’. .

[Meder2002] S. Meder, V. Welch, S. Tuecke, and D. Engert, “GSS-API Extensions”, Grid Security Infrastructure Working Group Document, Global Grid Forum, August 2002. .

[MyGrid] MyGrid. .

[Nahrstedt1999] K. Nahrstedt, “To Overprovision or To Share via QoS-aware Resource Management?”, in Proc. of 8th IEEE Int. Symp. on High Performance Distributed Computing, Redondo Beach, California, USA, 1999.

[Nakata2003] H. Nakada, Y. Tanaka, S. Matsuoka, and S. Sekiguchi, “Ninf-G: a GridRPC System on the Globus Toolkit”, in [Berman2003].

[NCSA] The National Computational Science Alliance. .

[NEC] NEC Wins Large Order for Blade Server for Grid Computing from Tokyo Institute of Technology. .

[NEESgrid] Network for Earthquake Engineering Simulation grid. .

[NESC] UK National e-Science Centers. .

[NeuroGrid] NeuroGrid: Brain Activity Analysis on Global Grids. .

[NorduGrid] Grids in Nordic countries. .

[Novotny2001] J. Novotny, S. Tuecke, and V. Welch, “An Online Credential Repository for the Grid: MyProxy”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[ParCo] Parallel Computing. .

[Patten2000] C. J. Patten, and K. A. Hawick, “Flexible High-Performance Access to Distributed Storage Resources”, in Proc. of 9th IEEE Int. Symp. on High Performance Distributed Computing, Pittsburgh, Pennsylvania, USA, 2000.

[Platform] Platform Computing Inc. .

[PPDG] Particle Physics Data Grid. .

[PPL] Parallel Processing Letters. .

[Rajasekar2002] A. Rajasekar, M. Wan, and R. Moore, “MySRB & SRB: Components of a Data Grid”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Raman1998] R. Raman, M. Livny, and M. Solomon, “Matchmaking: Distributed Resource Management for High Throughput Computing”, in Proc. of 7th IEEE Int. Symp. on High Performance Distributed Computing, Chicago, USA, pp.140-147, 1998.

[Rambadt2002] M. Rambadt, and P. Wieder, “UNICORE — Globus Interoperability: Getting the Best of Both Worlds”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, pp. 422, 2002.

[Ranganathan2002] K. Ranganathan, and I. Foster, “Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[RealityGrid] RealityGrid. .

[Ripeanu2002] M. Ripeanu, and Ian Foster, “A Decentralized, Adaptive Replica Location Mechanism”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Romberg1999] M. Romberg, “The UNICORE Architecture: Seamless Access to Distributed Resources”, in Proc. of 8th IEEE Int. Symp. on High Performance Distributed Computing, pp. 287-293, 1999. .

[Roy2002] A. Roy, and V. Sander, “Advanced Reservation API”, Scheduling Working Group Document, Global Grid Forum, May 2002.

[Royo2001] D. Royo, L. D. de Cerio, N. H. Kapadia, and J. A. B. Fortes, “A Pipelined Resource Management Architecture for Wide-Area Network Computing”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[Russell2001] M. Russell, G. Allen, G. Daues, I. Foster, E. Seidel, J. Novotny, J. Shalf, and G. von Laszewski, “The Astrophysics Simulation Collaboratory Portal: A Science Portal Enabling Community Software Development”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[Sato1998] M. Sato, H. Tezuka, A. Hori, Y. Ishikawa, S. Sekiguchi, H. Nakada, S. Matsuoka, and U. Nagashima, “Ninf and PM: Communication Libraries for Global Computing and High-performance Cluster Computing”, Future Generation Computer Systems, Vol. 13, No. 4-5, pp. 349-359, 1998. .

[SC] The SCxy Conference Series. .

[Schroeder2000] B. Schroeder, and M. Harchol-Balter, “Evaluation of Task Assignment Policies for Supercomputing Servers: The Case for Load Unbalancing and Fairness”, in Proc. of 9th IEEE Int. Symp. on High Performance Distributed Computing, Pittsburgh, Pennsylvania, USA, 2000.

[ScienceGrid] DOE Science Grid. .

[SGI] SGI and Platform Computing Announce Global Alliance for Grid Computing Solutions. .

[Shen2000] X. Shen, and A. Choudhary, “A Distributed Multi-Storage Resource Architecture and I/O Performance Prediction for Scientific Computing”, in Proc. of 9th IEEE Int. Symp. on High Performance Distributed Computing, Pittsburgh, Pennsylvania, USA, 2000.

[Shirasuna2002] S. Shirasuna, H. Nakada, S. Shirasuna, and S. Sekiguchi, “Evaluating Web Services Based Implementations of GridRPC”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[SINET] Science Information Network. .

[SInRG] Scalable Intracampus Research Grid. .

[Smith2000] W. Smith, A. Waheed, D. Meyers, and J. Yan, “An Evaluation of Alternative Designs for a Grid Information Service”, in Proc. of 9th IEEE Int. Symp. on High Performance Distributed Computing, Pittsburgh, Pennsylvania, USA, 2000.

[Snell2002] Q. Snell, K. Tew, J. Ekstrom, and M. Clement, “An Enterprise-Based Grid Resource Management System”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Sony] Sony Takes PlayStation 2 to the Grid. .

[SP] Scientific Programming. .

[Stevens1997] R. Stevens, P. Woodward, T. DeFanti, and C. Catlett, “From the I-WAY to the National Technology Grid”, Communications of the ACM, Vol. 40, No. 11, pp. 50-60, 1997.

[Stockinger2001] H. Stockinger, A. Samar, K. Holtman, B. Allcock, I. Foster, and B. Tierney, “File and Object Replication in Data Grids”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[SUN] SUN Grid Technology. .

[Sunderam2002] V. Sunderam, and D. Kurzyniec, “Lightweight Self-Organizing Frameworks for Metacomputing”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Supinski1999] B. R. de Supinski, and Nicholas T. Karonis, “Accurately Measuring MPI Broadcasts in a Computational Grid”, in Proc. of 8th IEEE Int. Symp. on High Performance Distributed Computing, Redondo Beach, California, USA, 1999.

[Takefusa1999] A. Takefusa, S. Matsuoka, K. Aida, H. Nakada, and U. Nagashima, “Overview of a Performance Evaluation System for Global Computing Scheduling Algorithms”, in Proc. 8th IEEE Int. Symp. on High Performance Distributed Computing, Redondo Beach, California, USA, 1999.

[Takefusa2001] A. Takefusa, S. Matsuoka, H. Casanova, and F. Berman, “A Study of Deadline Scheduling for Client-Server Systems on the Computational Grid”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[Taylor2002] V. Taylor, X. Wu, J. Geisler, and R. Stevens, “Using Kernel Couplings to Predict Parallel Application Performance”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[TeraGrid] TeraGrid. .

[Terekhov2001] I. Terekhov, R. Pordes, V. White, L. Lueking, L. Carpenter, J. Trumbo, S. Veseli, M. Vranicar, S. White, and H. Schellman, “Distributed Data Access and Resource Management in the D0 SAM System”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[ThaiGrid] Thailand High-performance Advanced Infrastructure Grid. .

[Thain2001] D. Thain, J. Basney, S. Son, and M. Livny, “The Kangaroo Approach to Data Movement on the Grid”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[Thain2002] D. Thain, and M. Livny, “Error Scope on a Computational Grid: Theory and Practice”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Thomas2001] M. Thomas, S. Mock, M. Dahan, K. Mueller, D. Sutton, and J. R. Boisseau, “The GridPort Toolkit: A System for Building Grid Portals”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[Tierney2000] B. Tierney, B. Crowley, D. Gunter, M. Holding, J. Lee, and M. Thompson, “A Monitoring Sensor Management System for Grid Environments”, in Proc. of 9th IEEE Int. Symp. on High Performance Distributed Computing, Pittsburgh, Pennsylvania, USA, 2000.

[UD] United Devices. .

[Vadhiyar2002] S. S. Vadhiyar, and J. J. Dongarra, “A Metascheduler For The Grid”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Vazhkudai2002] S. Vazhkudai, and J. M. Schopf, “Predicting Sporadic Grid Data Transfers”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Villacis1999] J. Villacis, M. Govindaraju, D. Stern, A. Whitaker, F. Breg, P. Deuskar, B. Temko, D. Gannon, and R Bramley, “CAT: A High Performance, Distributed Component Architecture Toolkit for the Grid”, in Proc. of 8th IEEE Int. Symp. on High Performance Distributed Computing, Redondo Beach, California, USA, 1999.

[VirtualLaboratory] Virtual Laboratory: Molecular Modeling for Drug Design on the World Wide Grid. .

[Weigle2001] E. Weigle, and W. Feng, “A Case for TCP Vegas in High-Performance Computational Grids”, in Proc. of 10th IEEE Int. Symp. on High Performance Distributed Computing, San Francisco, CA, USA, 2001.

[Weissman1998] J. B. Weissman, “Metascheduling: A Scheduling Model for Metacomputing Systems”, in Proc of 7th IEEE Int. Symp. on High Performance Distributed Computing, Chicago, USA, pp. 438-439, 1998.

[Weissman1999] J. B. Weissman, “Fault Tolerant Computing on the Grid: What are My Options?”, in Proc. of 8th IEEE Int. Symp. on High Performance Distributed Computing, Redondo Beach, California, USA, 1999.

[White2000] B. S. White, A. S. Grimshaw, and A. Nguyen-Tuong, “Grid-Based File Access: The Legion I/O Model”, in Proc. of 9th IEEE Int. Symp. on High Performance Distributed Computing, Pittsburgh, Pennsylvania, USA, 2000.

[Wickremesinghe2002] R. Wickremesinghe, J. S. Chase, and J. S. Vitter, “Distributed Computing with Load-Managed Active Storage”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Wolski1999] R. Wolski, N. Spring, and J. Hayes, “Predicting the CPU Availability of Time-Shared Unix Systems on the Computational Grid”, in Proc. of 8th IEEE Int. Symp. on High Performance Distributed Computing, Redondo Beach, California, USA, 1999.

[WWG] World Wide Grid. .

[Xie2002] Y. Xie, D. O’Hallaron, and M. K. Reiter, “A Secure Distributed Search System”, in Proc. of 11th IEEE Int. Symp. on High Performance Distributed Computing, Edinburgh, Scotland, 2002.

[Xu2000] D. Xu, K. Nahrstedt, A. Viswanathan, and D. Wichadakul, “QoS and Contention-Aware Multi-Resource Reservation”, in Proc. of 9th IEEE Int. Symp. on High Performance Distributed Computing, Pittsburgh, Pennsylvania, USA, 2000.

[Xu2001] Z. Xu, N. Sun, D. Meng, and W. Li, “Cluster and Grid Superservers: The Dawning Experiences in China”, in Proc. of 3rd IEEE Int. Conf. on Cluster Computing, Newport Beach, CA, USA, 2001.

[Zhou1992] S. Zhou, “LSF: Load Sharing in Large-Scale Heterogeneous Distributed Systems”, in Proc. of 1992 Workshop on Cluster Computing, 1992.

-----------------------

.

.

.

.

.

.

.

.

.

.

.

.

.

.

..

.

.

.

..........

[pic]

.

.

.

.

.

.

..

.

.

................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download