CARREON | GUERRERO | RODRIGUEZ Grid Computing
2 Grid Computing  Definition:  Grid computing is distributed computing performed transparently across multiple administrative domains.  Distributed high-performance computing.  Large geographically distributed networks of computers.  Provides a means for using distributed resources to solve large problems.  “What the Web did for communication, grids endeavor to do for computation.”
3 Grid Computing  Very general computing applications:  Database searches and queries.  Scientific applications.  Weather prediction.  Cryptography.  Business applications.  Transparency:  Distributing computational resources among multiple and widely separated sources and users is a difficult algorithmic problem.
4 Grid Computing  Grid Computing is a distributed computing model.  Grid computing technology integrates servers, storage systems, and networks distributed within the network to form an integrated system and provide users with powerful computing and storage capacity.  For the grid end users or applications, the grid looks like a virtual machine with powerful capabilities.  The essence of grid computing is to manage heterogeneous and loosely coupled resources in an efficient way in this distributed system, and to coordinate these resources through a task scheduler so they can complete specific cooperative computing tasks.
5 Grid Computing  A Grid computing network mainly consists of these three types of machines: CONTROL NODE PROVIDER USER
6 Grid Computing
7 Characteristics of Grids  Grids coordinate resources that are not subject to centralized control.  Grids use standard, open, general-purpose protocols and interfaces.  Grids deliver high qualities of service.  http://devresource.hp.com/drc/technical_papers/grid_soa/04.png
8 Grid vs. Parallel Computing SHARCNet – University of Western Ontario compneuro.uwaterloo.ca/beowulf.html Beowulf cluster
9 Grid vs. Parallel Computing  Grid computing is distinguished from parallel computing on one or more multiprocessors:  Parallel computing: locally “clustered” machines or large supercomputers.  Grid computing: computation across different administrative domains. www.chemistry.msu.edu/Facilities/Supercomputer/
10 Two Tenets of Grid Computing  Virtualization  Individual resources, such as computers, disks, information sources, and applications) are pooled together and made available by abstractions.  Overcomes “hard-coded” connections between providers and consumers of resources.  Provisioning  When a request for a resource is made, a specific resource is identified to fulfill the request.  The system determines how to meet the need, and optimizes system performance.
11 Characteristics of Grid Applications  Data acquired by scientific instruments.  Data are stored in archives on separate, perhaps geographically-separated sites.  Data are managed by teams belonging to different organizations.  Large quantities of data (tera- or petabytes) are collected.  Software used to analyze and summarize the raw data.
12 The Importance of Standardization  Without standardization, grid computing practitioners would need to acquire accounts at many different computer centers, managed by different organizations.  Different security and authentication protocols and accounting practices would have to be applied.  Very heterogeneous software environment.
13 Importance of Middleware  Middleware eases grid users’ experience and provides them with levels of abstraction.  Middleware extends the Web’s information and database management capabilities.  Allowing remote deployment of computational resources.
14 Globus Toolkit  Most widely-used middleware for grids.  Open source toolkit for building computing grids.  Provides a standard platform upon which other services build.  Provides directory services, security, and resource management. www.globus.org
15 CPU Scavenging  Unused PC resources worldwide are harnessed. Also known as shared computing.  CPU-scavenging systems gain and lose machines at unpredictable times as users interact with their computers, or as network connections fail.  CPU-scavengers can migrate jobs to allow smooth operation.
16 SETI@home  Search for Extraterrestrial Intelligence  Goal: to analyze vast amounts of data from the Arecibo radio telescope.  Initiated by the Space Sciences Laboratory at the University of California, Berkeley www.ras.ucalgary.ca/svlbiimages/arecibo.jpg, www.artscouncil.org.uk/spaceart
17 SETI@home  Uses a free screen saver, available to the public.  When activated, the screensaver program downloads time sequences of radio telescope data and searches them for radio sources.  SETI@home has more than 5 million participants.  Inspiration for other scientific applications in need of large computing resources.
18 SETI@home  Main purpose: A program downloads and analyzes radio telescope data.  Data is recorded at the Arecibo Observatory in Puerto Rico.  The data is sent to Berkeley, where it is processed into units of 107 seconds of data.  These work units are sent from the SETI@home server over the Internet to participating computers around the world for analysis.
19 SETI@home  The analysis software can search for signals with about one-tenth the strength of those sought in previous surveys, because it makes use of a very computationally intensive algorithm.  Data is merged into a database using SETI@home computers in Berkeley. Various pattern-detection algorithms are applied to search for the most interesting signals.
20 SETI@home User Client
21  Berkeley Open Infrastructure for Network Computing.  Funded by the National Science Foundation.  Used in the SETI project.  Client-server architecture:  Client – Used by the computer supplying resources for one or more BOINC projects. Performs the computations.  Server – System software, such as database services and project’s web site. BOINC
22 Remote Procedure Calls  Mechanism by which the server communicates with the client in BOINC.  Like a regular function call or method invocation, but one computer executes the function on another computer.
23 Remote Procedure Calls - Examples  Return screensaver mode: get_screensaver_mode(int& status)  Get a list of results for jobs in progress: get_results(RESULTS&)  Get a list of file transfers in progress: get_file_transfers(FILE_TRANSFERS&)  Get the client’s current state: get_state(CC_STATE&)
24 Human Proteome Folding Project (HPFP)  Goal: to predict the structure of human proteins.  Devised at the Institute for Systems Biology, University of Washington.  Produces the likely structures for each of the proteins using a set of predefined rules.  Improved knowledge of human proteins is important in developing new therapies.  Officially completed on July 18, 2006.  Second stage now underway.
25 Human Proteome Folding Project http://msnbcmedia.msn.com/j/msnbc/Components/Photos/041116/folding2.hmedium.jpg http://ndg.gunzclan.org/Charlotte/graphics/2/images/IMG0153_JPG.jpg Typical desktop screensaver setup for HPFP WCG desktop console - users monitor progress on protein-folding project.
26 Business Applications  Business application grid (BAG).  Major focus is using existing grid computing technologies to unite all of an organizations desktops, workstations, servers, printers, peripherals, etc., to perform useful work during idle time.  Usually focused on well-defined problems:  Calculating performance averages for a mutual fund.  Reducing processing time in wealth management systems.  Database applications.
27 Business Applications  A large financial services company uses specialized grid software for new corporate banking applications.  Oracle Corporation offers a grid database system.
28 Business Grid Middleware  Provides an IT-level infrastructure to support business applications.  Middleware provides services for composing, submitting, and managing business applications.  Business functions (e.g. credit card authorization and shipping-and-handling services) are not provided.  Globus Toolkit 4 makes it easier to build an application that taps into existing distributed computing resources (e.g. servers, storages, databases).
29 Conclusions  Grid computing is an “enabling technology” that is rapidly gaining popularity in:  Science.  Medicine.  Engineering.  Business and financial applications.  Many software vendors offer grid computing toolkits and middleware.  In 2004, 20% of companies were seeking grid computing solutions (Evans Data Corp.).
30 Benefits of Grid Computing  Collaboration.  Increased productivity.  Efficient use of resources and storage.  Cost-effectiveness.  Heterogeneous environments.  Failure tolerance.  Transparency.
31 ADVANTAGES OF GRID COMPUTING  It is not centralized, as there are no servers required, except the control node which is just used for controlling and not for processing.  Multiple heterogeneous machines i.e. machines with different Operating Systems can use a single grid computing network.  Tasks can be performed parallelly across various physical locations and the users don’t have to pay for them (with money).
32 Challenges  Lack of control over resources, administration.  Security.  Middleware.  Network failures.  Cultural issues.
33 DISADVANTAGES OF GRID COMPUTING  The software of the grid is still in the involution stage.  A super fast interconnect between computer resources is the need of hour.  Licensing across many servers may make it prohibitive for some applications.  Many groups are reluctant with sharing resources .
34 Open grid services architecture  OGSA – standard for grid-based applications.  Framework for meeting grid requirements. Application specific grid services web services application specific OGSI services: naming, service data (metadata) OGSA services: directory, management, security service creation and deletion, fault model, service groups GridService e.g. interfaces e.g. astronomy, biomedical informatics, high-energy physics Factory grid service interfaces standard Open-grid services infrastructure
35 Globus toolkit http://gdp.globus.org/gt3-tutorial/multiplehtml/ch01s04.html Restricts access to grid services so that only authorized clients can use them. Provides another layer of security on top of firewalls. Job management – checking status of jobs, pausing, stopping if necessary. Index services – helping to locate grid resources to meet specific needs. Reliable file transfer service (RFT) – performs large file transfers from a client to a grid service. Replica management – keeps track of subsets of large data sets that are being worked on. Other non-GT3 services can run on top of the GT3 architecture. Low-level functions
36 Other grid tools  Resource management:  Grid Resource Allocation and Management Protocol (GRAM)  Information Services:  Monitoring and Discovery Service (MDS)  Security Services:  Grid Security Infrastructure (GSI)  Data Movement and Management:  Global Access to Secondary Storage (GASS) and GridFTP
37 World-Wide Telescope (2002)  Goal: deployment of data resources shared by astronomers.  Data:  Archives of observations over a particular period of time, part of the EM spectrum, and area of the sky.  Observations collected at different sites around the world.  Data on same celestial objects are combined over different periods of time and different parts of the EM spectrum.
38 World-Wide Telescope (2)  Data archives ( terabyte) managed locally by the teams that collect the data.  As data is acquired, it is analyzed and stored as transformed data so that it can be used by remote astronomy sites.  Librarian role of scientists.  Metatdata is required to describe:  Time the data was collected.  Part of the sky observed.  Instruments used.
39 WCG ongoing projects  FightAIDS@Home  Launched by WCG in 2005.  Each computer processes one potential drug molecule and tests how well it would dock with HIV protease, inhibiting viral reproduction.  Human Proteome Folding Phase 2  Released in 2006.  Extension of HPF1, focusing on human-secreted proteins.  Better protein models, but more computationally intensive.
40 World Community Grid (WCG)  Goal: to create the world's largest public computing grid for humanitarian concerns.  Administered and funded by IBM.  Platforms: Windows, Linux, and Mac OS X.  Uses the idle time of Internet-connected desktop computers.  The agent works as a screen saver (like SETI@home), only using a computer's resources when it would otherwise be idle, and returning resources to the users when requested.  Projects are approved by an advisory board: representatives of major research institutions, universities, UN, WHO.
41 WCG – Smallpox research  Completed project.  WCG largely began due to the success of this project in shaving years off research time.  Analysis of therapeutic candidates to fight the small virus.  About 35 million potential drug molecules were screened against several smallpox proteins, resulting in 44 new potential treatments.
42 WCG Ongoing projects  Help Defeat Cancer (2006)  Processes large numbers of tissue samples using tissue microarrays.  Genome Comparison (2006)  Compares gene sequences of different organisms to find similarities.  Goal: determining the purpose of specific gene sequences in particular functions by comparing it with similar sequences with known functions in another organism.
43 Other grid projects Description of the project Reference 1. Aircraft engine maintenance using fault histories and sensors for predictive diagnostics www.cs.york.ac.uk/dame 2. Telepresence for predicting the effects of earthquakes on buildings, using simulations and test sites www.neesgrid.org 3. Bio-medical informatics network providing researchers with access to experiments and visualizations of results nbcr.sdsc.edu 4. Analysis of data from the CMS high energy particle detector at CERN by physicists world-wide over 15 years www.uscms.org 5. Testing the effects of candidate drug molecules for their effect on the activity of a protein, by performing parallel computations using idle desktop computers [Taufer et al. 2003] [Chien 2004] 6. Use of the Sun Grid Engine to enhance aerial photographs by using spare capacity on a cluster of web servers www.globexplorer.com 7. The butterfly Grid supports multiplayer games for very large numbers of players on the internet over the Globus toolkit www.butterfly.net 8. The Access Grid supports the needs of small group collaboration, for example by providing shared workspaces www.accessgrid.org
44 Requirements of grid systems  Remote access to resources, specifically, to archived data.  Data processing at the site where the data is managed.  Remote requests (queries) result in a visualization or results from a small quantity of data.  Resource manager of a data archive create instances of services when they are needed.  Similar to distributed object model, where servant objects are created when needed.
45 Requirements of grid systems (2)  Metadata to describe characteristics of archived data.  Directory services based on the metadata.  Software for:  Query management.  Data transfer.  Resource reservation.

GRID COMPUTING.ppt

  • 1.
    CARREON | GUERRERO| RODRIGUEZ Grid Computing
  • 2.
    2 Grid Computing  Definition: Grid computing is distributed computing performed transparently across multiple administrative domains.  Distributed high-performance computing.  Large geographically distributed networks of computers.  Provides a means for using distributed resources to solve large problems.  “What the Web did for communication, grids endeavor to do for computation.”
  • 3.
    3 Grid Computing  Verygeneral computing applications:  Database searches and queries.  Scientific applications.  Weather prediction.  Cryptography.  Business applications.  Transparency:  Distributing computational resources among multiple and widely separated sources and users is a difficult algorithmic problem.
  • 4.
    4 Grid Computing  GridComputing is a distributed computing model.  Grid computing technology integrates servers, storage systems, and networks distributed within the network to form an integrated system and provide users with powerful computing and storage capacity.  For the grid end users or applications, the grid looks like a virtual machine with powerful capabilities.  The essence of grid computing is to manage heterogeneous and loosely coupled resources in an efficient way in this distributed system, and to coordinate these resources through a task scheduler so they can complete specific cooperative computing tasks.
  • 5.
    5 Grid Computing  AGrid computing network mainly consists of these three types of machines: CONTROL NODE PROVIDER USER
  • 6.
  • 7.
    7 Characteristics of Grids Grids coordinate resources that are not subject to centralized control.  Grids use standard, open, general-purpose protocols and interfaces.  Grids deliver high qualities of service.  http://devresource.hp.com/drc/technical_papers/grid_soa/04.png
  • 8.
    8 Grid vs. ParallelComputing SHARCNet – University of Western Ontario compneuro.uwaterloo.ca/beowulf.html Beowulf cluster
  • 9.
    9 Grid vs. ParallelComputing  Grid computing is distinguished from parallel computing on one or more multiprocessors:  Parallel computing: locally “clustered” machines or large supercomputers.  Grid computing: computation across different administrative domains. www.chemistry.msu.edu/Facilities/Supercomputer/
  • 10.
    10 Two Tenets ofGrid Computing  Virtualization  Individual resources, such as computers, disks, information sources, and applications) are pooled together and made available by abstractions.  Overcomes “hard-coded” connections between providers and consumers of resources.  Provisioning  When a request for a resource is made, a specific resource is identified to fulfill the request.  The system determines how to meet the need, and optimizes system performance.
  • 11.
    11 Characteristics of GridApplications  Data acquired by scientific instruments.  Data are stored in archives on separate, perhaps geographically-separated sites.  Data are managed by teams belonging to different organizations.  Large quantities of data (tera- or petabytes) are collected.  Software used to analyze and summarize the raw data.
  • 12.
    12 The Importance of Standardization Without standardization, grid computing practitioners would need to acquire accounts at many different computer centers, managed by different organizations.  Different security and authentication protocols and accounting practices would have to be applied.  Very heterogeneous software environment.
  • 13.
    13 Importance of Middleware Middleware eases grid users’ experience and provides them with levels of abstraction.  Middleware extends the Web’s information and database management capabilities.  Allowing remote deployment of computational resources.
  • 14.
    14 Globus Toolkit  Mostwidely-used middleware for grids.  Open source toolkit for building computing grids.  Provides a standard platform upon which other services build.  Provides directory services, security, and resource management. www.globus.org
  • 15.
    15 CPU Scavenging  UnusedPC resources worldwide are harnessed. Also known as shared computing.  CPU-scavenging systems gain and lose machines at unpredictable times as users interact with their computers, or as network connections fail.  CPU-scavengers can migrate jobs to allow smooth operation.
  • 16.
    16 SETI@home  Search forExtraterrestrial Intelligence  Goal: to analyze vast amounts of data from the Arecibo radio telescope.  Initiated by the Space Sciences Laboratory at the University of California, Berkeley www.ras.ucalgary.ca/svlbiimages/arecibo.jpg, www.artscouncil.org.uk/spaceart
  • 17.
    17 SETI@home  Uses afree screen saver, available to the public.  When activated, the screensaver program downloads time sequences of radio telescope data and searches them for radio sources.  SETI@home has more than 5 million participants.  Inspiration for other scientific applications in need of large computing resources.
  • 18.
    18 SETI@home  Main purpose:A program downloads and analyzes radio telescope data.  Data is recorded at the Arecibo Observatory in Puerto Rico.  The data is sent to Berkeley, where it is processed into units of 107 seconds of data.  These work units are sent from the SETI@home server over the Internet to participating computers around the world for analysis.
  • 19.
    19 SETI@home  The analysissoftware can search for signals with about one-tenth the strength of those sought in previous surveys, because it makes use of a very computationally intensive algorithm.  Data is merged into a database using SETI@home computers in Berkeley. Various pattern-detection algorithms are applied to search for the most interesting signals.
  • 20.
  • 21.
    21  Berkeley OpenInfrastructure for Network Computing.  Funded by the National Science Foundation.  Used in the SETI project.  Client-server architecture:  Client – Used by the computer supplying resources for one or more BOINC projects. Performs the computations.  Server – System software, such as database services and project’s web site. BOINC
  • 22.
    22 Remote Procedure Calls Mechanism by which the server communicates with the client in BOINC.  Like a regular function call or method invocation, but one computer executes the function on another computer.
  • 23.
    23 Remote Procedure Calls- Examples  Return screensaver mode: get_screensaver_mode(int& status)  Get a list of results for jobs in progress: get_results(RESULTS&)  Get a list of file transfers in progress: get_file_transfers(FILE_TRANSFERS&)  Get the client’s current state: get_state(CC_STATE&)
  • 24.
    24 Human Proteome FoldingProject (HPFP)  Goal: to predict the structure of human proteins.  Devised at the Institute for Systems Biology, University of Washington.  Produces the likely structures for each of the proteins using a set of predefined rules.  Improved knowledge of human proteins is important in developing new therapies.  Officially completed on July 18, 2006.  Second stage now underway.
  • 25.
    25 Human Proteome FoldingProject http://msnbcmedia.msn.com/j/msnbc/Components/Photos/041116/folding2.hmedium.jpg http://ndg.gunzclan.org/Charlotte/graphics/2/images/IMG0153_JPG.jpg Typical desktop screensaver setup for HPFP WCG desktop console - users monitor progress on protein-folding project.
  • 26.
    26 Business Applications  Businessapplication grid (BAG).  Major focus is using existing grid computing technologies to unite all of an organizations desktops, workstations, servers, printers, peripherals, etc., to perform useful work during idle time.  Usually focused on well-defined problems:  Calculating performance averages for a mutual fund.  Reducing processing time in wealth management systems.  Database applications.
  • 27.
    27 Business Applications  Alarge financial services company uses specialized grid software for new corporate banking applications.  Oracle Corporation offers a grid database system.
  • 28.
    28 Business Grid Middleware Provides an IT-level infrastructure to support business applications.  Middleware provides services for composing, submitting, and managing business applications.  Business functions (e.g. credit card authorization and shipping-and-handling services) are not provided.  Globus Toolkit 4 makes it easier to build an application that taps into existing distributed computing resources (e.g. servers, storages, databases).
  • 29.
    29 Conclusions  Grid computingis an “enabling technology” that is rapidly gaining popularity in:  Science.  Medicine.  Engineering.  Business and financial applications.  Many software vendors offer grid computing toolkits and middleware.  In 2004, 20% of companies were seeking grid computing solutions (Evans Data Corp.).
  • 30.
    30 Benefits of GridComputing  Collaboration.  Increased productivity.  Efficient use of resources and storage.  Cost-effectiveness.  Heterogeneous environments.  Failure tolerance.  Transparency.
  • 31.
    31 ADVANTAGES OF GRID COMPUTING It is not centralized, as there are no servers required, except the control node which is just used for controlling and not for processing.  Multiple heterogeneous machines i.e. machines with different Operating Systems can use a single grid computing network.  Tasks can be performed parallelly across various physical locations and the users don’t have to pay for them (with money).
  • 32.
    32 Challenges  Lack ofcontrol over resources, administration.  Security.  Middleware.  Network failures.  Cultural issues.
  • 33.
    33 DISADVANTAGES OF GRID COMPUTING The software of the grid is still in the involution stage.  A super fast interconnect between computer resources is the need of hour.  Licensing across many servers may make it prohibitive for some applications.  Many groups are reluctant with sharing resources .
  • 34.
    34 Open grid servicesarchitecture  OGSA – standard for grid-based applications.  Framework for meeting grid requirements. Application specific grid services web services application specific OGSI services: naming, service data (metadata) OGSA services: directory, management, security service creation and deletion, fault model, service groups GridService e.g. interfaces e.g. astronomy, biomedical informatics, high-energy physics Factory grid service interfaces standard Open-grid services infrastructure
  • 35.
    35 Globus toolkit http://gdp.globus.org/gt3-tutorial/multiplehtml/ch01s04.html Restricts accessto grid services so that only authorized clients can use them. Provides another layer of security on top of firewalls. Job management – checking status of jobs, pausing, stopping if necessary. Index services – helping to locate grid resources to meet specific needs. Reliable file transfer service (RFT) – performs large file transfers from a client to a grid service. Replica management – keeps track of subsets of large data sets that are being worked on. Other non-GT3 services can run on top of the GT3 architecture. Low-level functions
  • 36.
    36 Other grid tools Resource management:  Grid Resource Allocation and Management Protocol (GRAM)  Information Services:  Monitoring and Discovery Service (MDS)  Security Services:  Grid Security Infrastructure (GSI)  Data Movement and Management:  Global Access to Secondary Storage (GASS) and GridFTP
  • 37.
    37 World-Wide Telescope (2002) Goal: deployment of data resources shared by astronomers.  Data:  Archives of observations over a particular period of time, part of the EM spectrum, and area of the sky.  Observations collected at different sites around the world.  Data on same celestial objects are combined over different periods of time and different parts of the EM spectrum.
  • 38.
    38 World-Wide Telescope (2) Data archives ( terabyte) managed locally by the teams that collect the data.  As data is acquired, it is analyzed and stored as transformed data so that it can be used by remote astronomy sites.  Librarian role of scientists.  Metatdata is required to describe:  Time the data was collected.  Part of the sky observed.  Instruments used.
  • 39.
    39 WCG ongoing projects FightAIDS@Home  Launched by WCG in 2005.  Each computer processes one potential drug molecule and tests how well it would dock with HIV protease, inhibiting viral reproduction.  Human Proteome Folding Phase 2  Released in 2006.  Extension of HPF1, focusing on human-secreted proteins.  Better protein models, but more computationally intensive.
  • 40.
    40 World Community Grid(WCG)  Goal: to create the world's largest public computing grid for humanitarian concerns.  Administered and funded by IBM.  Platforms: Windows, Linux, and Mac OS X.  Uses the idle time of Internet-connected desktop computers.  The agent works as a screen saver (like SETI@home), only using a computer's resources when it would otherwise be idle, and returning resources to the users when requested.  Projects are approved by an advisory board: representatives of major research institutions, universities, UN, WHO.
  • 41.
    41 WCG – Smallpoxresearch  Completed project.  WCG largely began due to the success of this project in shaving years off research time.  Analysis of therapeutic candidates to fight the small virus.  About 35 million potential drug molecules were screened against several smallpox proteins, resulting in 44 new potential treatments.
  • 42.
    42 WCG Ongoing projects Help Defeat Cancer (2006)  Processes large numbers of tissue samples using tissue microarrays.  Genome Comparison (2006)  Compares gene sequences of different organisms to find similarities.  Goal: determining the purpose of specific gene sequences in particular functions by comparing it with similar sequences with known functions in another organism.
  • 43.
    43 Other grid projects Descriptionof the project Reference 1. Aircraft engine maintenance using fault histories and sensors for predictive diagnostics www.cs.york.ac.uk/dame 2. Telepresence for predicting the effects of earthquakes on buildings, using simulations and test sites www.neesgrid.org 3. Bio-medical informatics network providing researchers with access to experiments and visualizations of results nbcr.sdsc.edu 4. Analysis of data from the CMS high energy particle detector at CERN by physicists world-wide over 15 years www.uscms.org 5. Testing the effects of candidate drug molecules for their effect on the activity of a protein, by performing parallel computations using idle desktop computers [Taufer et al. 2003] [Chien 2004] 6. Use of the Sun Grid Engine to enhance aerial photographs by using spare capacity on a cluster of web servers www.globexplorer.com 7. The butterfly Grid supports multiplayer games for very large numbers of players on the internet over the Globus toolkit www.butterfly.net 8. The Access Grid supports the needs of small group collaboration, for example by providing shared workspaces www.accessgrid.org
  • 44.
    44 Requirements of gridsystems  Remote access to resources, specifically, to archived data.  Data processing at the site where the data is managed.  Remote requests (queries) result in a visualization or results from a small quantity of data.  Resource manager of a data archive create instances of services when they are needed.  Similar to distributed object model, where servant objects are created when needed.
  • 45.
    45 Requirements of gridsystems (2)  Metadata to describe characteristics of archived data.  Directory services based on the metadata.  Software for:  Query management.  Data transfer.  Resource reservation.