Grid Computing

Abstract

The vision of Grid computing is to develop a platform which gathers geographically distributed resources (such as computational power, data, and equipment) into one very powerful and easy to use system. In this chapter, we present the main motivations behind this technology. Furthermore, we outline the challenges that researchers need to face when constructing such a complex distributed system. To demonstrate the practical impact, we describe various tools and applications which are already been extensively used to solve real problems. Finally, we give some pointers to the future directions in which Grid computing will evolve.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Grid computing info center, http://www.gridcomputing.com (2008).
  2. 2.
    G. E. Moore, Cramming more components onto integrated circuits, Electronics (1965), pp. 114–117.Google Scholar
  3. 3.
    L. Roberts, Beyond moore’s law: Internet growth trends, Computer 33 (1) (2000) 117–119.CrossRefGoogle Scholar
  4. 4.
    I. Foster, C. Kesselman (Eds.), The Grid: Blueprint for a Future Computing Infrastructure, Morgan Kaufmann Publishers, San Francisco, USA, 1999.Google Scholar
  5. 5.
    C. S. Yeo, R. Buyya, M. D. de Assuncao, J. Yu, A. Sulistio, S. Venugopal, M. Placek, Utility computing on global grids, in: H. Bidgoli (Ed.), The Handbook of Computer Networks, Vol. III Part 1, John Wiley & Sons, New York, USA, 2007.Google Scholar
  6. 6.
    D. Abramson, J. Giddy, L. Kotler, High performance parametric modeling with nimrod/G: killer application for the global grid?, in: Proceedings of the 14th International Parallel and Distributed Processing Symposium(IPDPS’00), Cancun, Mexico, (2000), pp. 520–528.Google Scholar
  7. 7.
    W. Cirne, F. Brasileiro, J. Sauve, N. Andrade, D. Paranhos, E. Santos-Neto, R. Medeiros, Grid computing for bag of tasks applications, in: Proceedings of the 3rd IFIP Conference on E-Commerce, E-Business and E-Government, Sao Paolo, Brazil, (2003), pp. 591–609.Google Scholar
  8. 8.
    R. Buyya, D. Abramson, J. Giddy, Nimrod-G: An architecture for a resource management and scheduling system in a global computational grid, in: Proceedings of the 4th International Conference & Exhibition on High Performance Computing in Asia-Pacific Region (HPC Asia’00), Beijing, China, (2000), pp. 283–289.Google Scholar
  9. 9.
    D. P. Anderson, J. Cobb, E. Korpela, M. Lebofsky, D. Werthimer, SETI@home: An experiment in public-resource computing, Communications of the ACM 45 (11) (2002) 56–61.CrossRefGoogle Scholar
  10. 10.
    L. B. Costa, L. Feitosa, E. Araujo, G. Mendes, R. Coelho, W. Cirne, D. Fireman, MyGrid: A complete solution for running bag-of-tasks applications, in: Proceedings of the Simposio Brasileiro de Redes de. Computadores (SBRC’04), Gramado, Brazil, (2004).Google Scholar
  11. 11.
    A. Chervenak, I. Foster, C. Kesselman, C. Salisbury, S. Tuecke, The data grid: Towards an architecture for the distributed management and analysis of large scientific datasets, Network and Computer Applications 23 (2001) 187–200.CrossRefGoogle Scholar
  12. 12.
    W. Hoschek, F. J. Jaén-Martínez, A. Samar, H. Stockinger, K. Stockinger, Data management in an international data grid project, in: Proceedings of the 1st International Workshop on Grid Computing (Grid’00), Bangalore, India, (2000), pp. 77 – 90.Google Scholar
  13. 13.
    J. C. Jacob, D. S. Katz, T. Prince, G. B. Berriman, J. C. Good, A. C. Laity, E. Deelman, G. Singh, M.-H. Su, The montage architecture for grid-enabled science processing of large, distributed datasets, in: Proceedings of the Earth Science Technology Conference (ESTC’04), (2004).Google Scholar
  14. 14.
    M. J. Mineter, C. H. Jarvis, S. Dowers, From stand-alone programs towards grid-aware services and components: A case study in agricultural modelling with interpolated climate data, Environmental Modelling and Software 18 (4) (2003) 379–391.CrossRefGoogle Scholar
  15. 15.
    LCG Computing Fabric Area, http://lcg-computing-fabric.web.cern.ch (2008).
  16. 16.
  17. 17.
    International Virtual Observatory Alliance, http://www.ivoa.net (2008).
  18. 18.
    Avaki EII - Enterprise Data Integration Sofware, http://www.sybase.com/products/allproductsa-z/avakieii (2008).
  19. 19.
    K. Seymour, A. YarKhan, S. Agrawal, J. Dongarra, NetSolve: Grid enabling scientific computing environments, in: L. Grandinetti (Ed.), Grid Computing and New Frontiers of High Performance Processing, Vol. 14 of Advances in Parallel Computing, Elsevier, Netherlands, (2005), pp. 33–51.CrossRefGoogle Scholar
  20. 20.
    L. Childers, T. Disz, R. Olson, M. E. Papka, R. Stevens, T. Udeshi, Access grid: Immersive group-to-group collaborative visualization, in: Proceedings of the 4th International Immersive Projection Technology Workshop, Ames, USA, (2000).Google Scholar
  21. 21.
    M. Cannataro, D. Talia, The knowledge grid, Communications of the ACM 46 (1) (2003) 89–93.CrossRefGoogle Scholar
  22. 22.
    EU Data Mining Grid, http://www.datamininggrid.org (2008).
  23. 23.
    S. Graupner, J. Pruyne, S. Singhal, Making the utility data center a power station for the enterprise grid, Tech. Rep. HPL–2003–53, HP Labs, Palo Alto, USA (2003).Google Scholar
  24. 24.
    R. Buyya, S. Venugopal, The gridbus toolkit for service oriented grid and utility computing: An overview and status report, in: Proceedings of the 1st International Workshop on Grid Economics and Business Models (GECON’04), Seoul, Korea, (2004), pp. 19– 66.Google Scholar
  25. 25.
    S. Venugopal, R. Buyya, K. Ramamohanarao, A taxonomy of data grids for distributed data sharing, management and processing, ACM Computing Surveys 38 (1) (2006) 1–53.CrossRefGoogle Scholar
  26. 26.
    H. Stockinger, Database replication in world-wide distributed data grids, Ph.D. thesis, Fakultät für Wirtschaftswissenschaften und Informatik, Universität Wien (2001).Google Scholar
  27. M. Tang, B.-S. Lee, C.-K. Yeo, X. Tang, Dynamic replication algorithms for the multi-tier data grid, Future Generation Computer Systems 21 (5) (2005) 775–790.CrossRefGoogle Scholar
  28. 28.
    V. Agarwal, G. Dasgupta, K. Dasgupta, A. Purohit, B. Viswanathan, DECO: Data Replication and Execution CO-Scheduling for Utility Grids, in: Proceedings of the 4th International Conference on Service Oriented Computing, Chicago, USA, (2006), pp. 52–65.Google Scholar
  29. 29.
    Sun Grid Engine, http://gridengine.sunsource.net (2008).
  30. G. Sipos, P. Kacsuk, Multi-grid, multi-user workflows in the P-GRADE portal, Journal of Grid Computing 3 (3–4) (2005) 221–238.Google Scholar
  31. 31.
    H. Gibbins, K. Nadiminti, B. Beeson, R. Chhabra, B. Smith, R. Buyya, The Australian BioGrid Portal: Empowering the molecular docking research community, in: Proceedings of the 3rd APAC Conference and Exhibition on Advanced Computing, Grid Applications and eResearch (APAC’05), Gold Coast, Australia, (2005), pp. 26–30.Google Scholar
  32. 32.
  33. 33.
    I. Foster, C. Kesselman, S. Tuecke, The anatomy of the grid: enabling scalable virtual organizations, High Performance Computing Applications 15 (3) (2001) 200–222.CrossRefGoogle Scholar
  34. 35.
    L. Pearlman, V. Welch, I. Foster, C. Kesselman, S. Tuecke, A community authorization service for group collaboration, in: Proceedings of IEEE 3rd InternationalWorkshop on Policies for Distributed Systems and Networks, Monterey, USA, (2002).Google Scholar
  35. 35.
    B. Neuman, T. Ts’o, Kerberos: An authentication service for computer networks, IEEE Communications Magazine 32 (9) (1994) 33–38.CrossRefGoogle Scholar
  36. 36.
    R. Housley, W. Polk, W. Ford, D. Solo, Internet X. 509 Public Key Infrastructure Certificate and Certificate Revocation List (CRL) Profile (2002).Google Scholar
  37. 37.
    R. Alfieri, R. Cecchini, V. Ciashini, L. dell’Agnello, A. Frohner, K. Lorentey, F. Spataro, VOMS, an authorization system for virtual organizations, in: Proceedings of the 1st European Across Grids Conference, Santiago de Compostela, Spain, (2003).Google Scholar
  38. 38.
    R. O. Sinnott, D. W. Chadwick, J. Koetsier, O. Otenko, J. Watt, T. A. Nguyen, Supporting decentralized, security focused dynamic virtual organizations across the grid, in: Proceedings of the 2nd IEEE International Conference on e-Science and Grid Computing, Amsterdam, Netherlands, (2006).Google Scholar
  39. 39.
    B. Nasser, R. Laborde, A. Benzekri, F. Barrere, M. Kamel, Dynamic creation of interorganizational grid virtual organizations, in: Proceedings of the 1st IEEE International Conference on e-Science and Grid Computing, Melbourne, Australia, (2005).Google Scholar
  40. 40.
    A. A. E. Kalam, R. E. Baida, P. Balbiani, S. Benferhat, F. Cuppens, Y. Deswartes, A. Miege, C. Saurel, G. Trouessin, Organization based access control, in: Proceedings of the 4th International Workshop on Policies for Distributed Systems and Networks, Lake Como, Italy, (2003), pp. 120–131.Google Scholar
  41. 41.
    C. Morin, XtreemOS: A grid operating system making your computer ready for participating in virtual organizations, in: 10th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing (ISORC 2007). IEEE, (2007), pp. 393 – 402.Google Scholar
  42. 42.
    M. Coppola, Y. Jégou, B. Matthews, C. Morin, L. P. Prieto, Ó. David Sánchez, E. Y. Yang, H. Yu, Virtual organization support within a grid-wide operating system, IEEE Internet Computing 12 (2) (2008) 20–28.CrossRefGoogle Scholar
  43. 43.
    A. Sulistio, Advance reservation and revenue-based resource management for grid systems, Ph.D. thesis, The University of Melbourne, Australia (2008).Google Scholar
  44. 44.
    T. Roeblitz, F. Schintke, A. Reinefeld, Resource reservations with fuzzy requests, Concurrency and Computation: Practice & Experience (CCPE) 18 (13) (2006) 1681–1703.CrossRefGoogle Scholar
  45. 45.
    M. Siddiqui, A. Villazon, T. Fahringer, Grid capacity planning with negotiation-based advance reservation for optimized QoS, in: Proceedings of the 2006 ACM/IEEE conference on Supercomputing (SC’06), Florida, USA, (2006), p. 21.Google Scholar
  46. 46.
    S. Naiksatam, S. Figueira, Elastic reservations for efficient bandwidth utilization in lambdagrids, Future Generation Computer Systems 23 (1) (2007) 1–22.CrossRefGoogle Scholar
  47. 47.
    S. Venugopal, X. Chu, R. Buyya, A negotiation mechanism for advance resource reservation using the alternate offers protocol, in: Proceedings of the 16th International Workshop on Quality of Service (IWQoS’08, Twente, The Netherlands, (2008), pp. 40–49.Google Scholar
  48. 48.
    R. Buyya, D. Abramson, S. Venugopal, The grid economy, Proceedings of the IEEE 93 (3) (2005) 698–714.CrossRefGoogle Scholar
  49. 49.
    W. Smith, I. Foster, V. Taylor, Scheduling with advanced reservations, in: Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS’00), Cancun, Mexico, (2000), pp. 127–132.Google Scholar
  50. 50.
    R. L. Phillips, Pricing and Revenue Optimization, Stanford University Press, Pala Alto, CA, (2005).Google Scholar
  51. 51.
    S. Venugopal, R. Buyya, L. Winton, A grid service broker for scheduling e-science applications on global data grids: Research articles, Concurrency and Computation: Practice and Experience (CCPE) 18 (6) (2006) 685–699.CrossRefGoogle Scholar
  52. 52.
    S. Lalis, A. Karipidis, JaWS: An open market-based framework for distributed computing over the internet, in: Proceedings of the 1st IEEE/ACM International Workshop on Grid Computing (Grid’00), Bangalore, India, (2000), pp. 87–106.Google Scholar
  53. 53.
    M. Stonebraker, R. Devine, M. Kornacker, W. Litwin, A. Pfeffer, A. Sah, C. Staelin, An economic paradigm for query processing and data migration in Mariposa, in: Proceedings of the 3rd International Conference on Parallel and Distributed Information Systems (PDIS’94), Austin, USA, (1994), pp. 58 – 68.Google Scholar
  54. 54.
    O. Regev, N. Nisan, The POPCORN Market – An online market for computational resources, in: Proceedings of the 1st International Conference on Information and Computation Economies (ICE’98), Charleston, USA, (1998), pp. 148 – 157.Google Scholar
  55. 55.
    C. A. Waldspurger, T. Hogg, B. A. Huberman, J. O. Kephart, W. S. Stornetta, Spawn: A distributed computational economy, Software Engineering 18 (2) (1992) 103–117.CrossRefGoogle Scholar
  56. 56.
    P. Padala, C. Harrison, N. Pelfort, E. Jansen, M. Frank, C. Chokkareddy, OCEAN: The open computation exchange and arbitration network, a market approach to meta computing, in: Proceedings of the 2nd International Symposium on Parallel and Distributed Computing (ISPDS’ 03), Ljubljana, Slovenia, (2003), pp. 185–192.Google Scholar
  57. 57.
    K. Lai, B. A. Huberman, L. Fine, Tycoon: A distributed market-based resource allocation system, Tech. Rep. arXiv:cs.DC/0404013, HP Labs, Palo Alto, USA (April 2004).Google Scholar
  58. 58.
    B. F. Cooper, H. Garcia-Molina, Bidding for storage space in a peer-to-peer data preservation system, in: Proceedings of the 22nd International Conference on Distributed Computing Systems (ICDCS’02), Vienna, Austria, (2002), pp. 372–381.Google Scholar
  59. 59.
    A. Sulistio, R. Buyya, A time optimization algorithm for scheduling bag-of-task applications in auction-based proportional share systems, in: Proceedings of the 17th International Symposium on Computer Architecture and High Performance Computing, Rio de Janeiro, Brazil, (2005), pp. 235–242.Google Scholar
  60. 60.
    J. Broberg, S. Venugopal, R. Buyya, Market-oriented grids and utility computing: The stateof- the-art and future directions, Journal of Grid Computing 6 (3) (2008) 255–276.CrossRefGoogle Scholar
  61. 61.
    R. Moore, C. Baru, R. Marciano, A. Rajasekar, M.Wan, Data-intensive computing, the Grid: Blueprint for a new computing infrastructure, Morgan Kaufmann (1999) 105–129.Google Scholar
  62. 62.
    R. Sandhu, E. Coyne, H. Feinstein, C. Youman, Role-based access control models, computer (1996) 29(2) 38–47.CrossRefGoogle Scholar
  63. 63.
    R. Thomas, R. Sandhu, Task-based authorization controls (TBAC): a family of models for active and enterprise-oriented authorization management, Database Security 11 (1998) 166–181.Google Scholar
  64. 64.
    B. Allcock, J. Bester, J. Bresnahan, A. Chervenak, I. Foster, C. Kesselman, S.Meder, V. Nefedova, D. Quesnel, S. Tuecke, Data management and transfer in high-performance computational grid environments, Parallel Computing 28 (5) (2002) 749–771.CrossRefGoogle Scholar
  65. 65.
    A. Chervenak, M. Cai, Applying peer-to-peer techniques to grid replica location services, Journal of Grid Computing 4 (1) (2006) 49–69.CrossRefGoogle Scholar
  66. 66.
    U. Cˇ ibej, B. Slivnik, B. Robicˇ, The complexity of static data replication in data grids, Parallel Comput. 31 (8+9) (2005) 900–912.MathSciNetGoogle Scholar
  67. 67.
    W. H. Bell, D. G. Cameron, L. Capozza, A. P. Millar, K. Stockinger, F. Zini, Simulation of dynamic grid replication strategies in optorsim, in: Proc. IEEEWorkshop on Grid Computing (Grid’2002), Springer Verlag, Lecture Notes in Computer Science, (2002), pp. 46–57.Google Scholar
  68. 68.
    W. H. Bell, D. G. Cameron, R. Carvajal-Schiaffino, A. P. Millar, K. Stockinger, F. Zini, Evaluation of an economy-based file replication strategy for a data grid, in: Proc. International Workshop on Agent based Cluster and Grid Computing, IEEE Computer Society Press, (2003), p. 661.Google Scholar
  69. 69.
    C. Nicholson, D. G. Cameron, A. T. Doyle, A. P. Millar, K. Stockinger, Dynamic data replication in lcg 2008, in: Proc. UK e-Science All Hands Meeting, (2006), pp. 1259–1271.Google Scholar
  70. 70.
    K. Ranganathan, I. Foster, Decoupling computation and data scheduling in distributed dataintensive applications, in: Proc. International Symposium on High Performance Distributed Computing, (2002), pp. 352–358.Google Scholar
  71. 71.
    I. Foster, Globus toolkit version 4: Software for service-oriented systems, Journal of Computer Science and Technology 21 (4) (2006) 513–520.CrossRefGoogle Scholar
  72. 72.
    The European DataGrid Project, http://eu-datagrid.web.cern.ch/eu-datagrid (2008).
  73. 73.
    N. Karonis, B. Toonen, I. Foster,MPICH-G2: a Grid-enabled implementation of the message passing interface, Journal of Parallel and Distributed Computing 63 (5) (2003) 551–563.MATHCrossRefGoogle Scholar
  74. 74.
    M. Ripeanu, A. Iamnitchi, I. Foster, Cactus application: Performance predictions in grid environments, Lecture Notes in Computer Science (2001) 807–816.Google Scholar
  75. 75.
    J. Frey, T. Tannenbaum, M. Livny, I. Foster, S. Tuecke, Condor-G: A computation management agent for multi-institutional grids, Cluster Computing 5 (3) (2002) 237–246.CrossRefGoogle Scholar
  76. 76.
    A. YarKhan, J. Dongarra, K. Seymour, GridSolve: The evolution of a network enabled solver, International Federation for Information Processing-Publications-IFIP 239 (2007) 215.Google Scholar
  77. 77.
    J. Yu, R. Buyya, A taxonomy of workflow management systems for grid computing, Journal of Grid Computing 3 (3) (2005) 171–200.CrossRefGoogle Scholar
  78. 78.
    E. Deelman, J. Blythe, Y. Gil, C. Kesselman, G.Mehta, S. Patil, M. H. Su, K. Vahi, M. Livny, Pegasus: Mapping scientific workflow onto the grid, in: Across Grids Conference 2004, Nicosia, Cyprus, (2004), pp. 11–20.Google Scholar
  79. 79.
    I. Taylor, M. Shields, I. Wang, A. Harrison, Visual grid workflow in triana, Journal of Grid Computing 3 (3) (2005) 153–169.CrossRefGoogle Scholar
  80. 80.
    G. von Laszewski, Java CoG kit workflow concepts for scientific experiments, Technical Report, Argonne National Laboratory, Argonne, IL, USA, (2005).Google Scholar
  81. 81.
    T. Oinn, M. Greenwood, M. Addis, M. Alpdemir, J. Ferris, K. Glover, C. Goble, A. Goderis, D. Hull, D. Marvin, et al., Taverna: lessons in creating a workflow environment for the life sciences, Concurrency and Computation 18 (10) (2006) 1067.CrossRefGoogle Scholar
  82. 82.
    C. Goble, D. De Roure, myExperiment: social networking for workflow-using e-scientists, in: Proceedings of the 2nd workshop on Workflows in support of large-scale science, ACM Press New York, NY, USA, (2007), pp. 1–2.Google Scholar
  83. 83.
    Gridbus workflow homepage, http://www.gridbus.org/workflow/ (2008).
  84. 84.
    PBS Pro, http://www.pbsgridworks.com/ (2008).
  85. 85.
    B. Nitzberg, J. M. Schopf, J. P. Jones, PBS Pro: Grid computing and scheduling attributes, in: R. Selva (eds.) Grid Resource Management: State of the Art and Future Trends, Kluwer Academic Publishers, Norwell, MA, USA, (2004), pp. 183–190.Google Scholar
  86. 86.
    86. I. Foster, C. Kesselman, Globus: A metacomputing infrastructure toolkit, Supercomputer Applications 11 (2) (1997) 115–128.Google Scholar
  87. 87.
    J. MacLaren, HARC: The highly-available resource co-allocator, in: Proceedings of the International Conference on Grid Computing, High-PerformAnce and Distributed Applications (GADA’07), Vilamoura, Algarve, Portugal, (2007), pp. 1385–1402.Google Scholar
  88. 88.
    J. Gray, L. Lamport, Consensus on transaction commit, ACM Transactions on Database Systems (TODS) 31 (1) (2006) 133–160.CrossRefGoogle Scholar
  89. 89.
  90. 90.
    J. MacLaren, Co-allocation of compute and network resources using HARC, in: Proceedings of Lighting the Blue Touchpaper for UK e-Science: Closing Conference of the ESLEA Project, Edinburgh, UK, 2007, p. 16.Google Scholar
  91. 91.
    A. Takefusa, M. Hayashi, N. Nagatsu, H. Nakada, T. Kudoh, T. Miyamoto, T. Otani, H. Tanaka, M. Suzuki, Y. Sameshima, W. Imajuku, M. Jinno, Y. Takigawa, S. Okamoto, Y. Tanaka, S. Sekiguchi, G-lambda: Coordination of a grid scheduler and lambda path service over GMPLS, Future Generation Computer Systems 22 (8) (2006) 868–875.CrossRefGoogle Scholar
  92. 92.
    G-lambda, http://www.g-lambda.net (2008).
  93. 93.
    I. Foster, Globus toolkit version 4: Software for service-oriented systems, in: IFIP International Conference on Network and Parallel Computing (NPC’06)), Tokyo, Japan, (2006), pp. 2–13.Google Scholar
  94. 94.
    E. Mannie, RFC 3945: Generalized Multi-Protocol Label Switching (MPLS) Architecture, http://www.ietf.org/rfc/rfc3945.txt (Oct. 2004).
  95. 95.
    J. Geddes, S. Lloyd, A. Simpson, M. Rossor, N. Fox, D. Hill, J. Hajnal, S. Lawrie, A. Mclntosh, E. Johnstone, et al., NeuroGrid: Using grid technology to advance neuroscience, in: Computer-Based Medical Systems, 2005. Proceedings. 18th IEEE Symposium on, (2005), pp. 570–572.Google Scholar
  96. 96.
    Medigrid project homepage, http://www.medigrid.de/ (2008).
  97. 97.
    X. Chu, A. Lonie, P. Harris, S. R. Thomas, R. Buyya, A service-oriented grid environment for integration of distributed kidney models and resources, Concurrency and Computation: Practice and Experience 20 (9) (2008) 1095–1111.CrossRefGoogle Scholar
  98. 98.
    S. Amendolia,M. Brady, R.McClatchey, M. Mulet-Parada, M. Odeh, T. Solomonides, MammoGrid: Large-scale distributed mammogram analysis, The New Navigators: From Professionals to Patients (2003).Google Scholar
  99. 99.
    J. Jacob, R. Williams, J. Babu, S. Djorgovski, M. Graham, D. Katz, A. Mahabal, C. Miller, R. Nichol, D. Berk, et al., Grist: Grid data mining for astronomy, Astronomical Data Analysis Software and Systems (ADASS) XIV (2004).Google Scholar
  100. 100.
    Astrogrid-d project homepage, http://www.gac-grid.de/ (2008).
  101. 101.
    Australian virtual laboratory, http://aus-vo.org/ (2008).
  102. 102.
    Project grifin homepage, http://www.grifin.eu/ (2008).
  103. 103.
    D. Castelli, DILIGENT project homepage http://www.diligentproject.org/ (2008).
  104. 104.
    R. Buyya, C. Yeo, S. Venugopal, Market-oriented cloud computing: vision, hype, and reality for delivering IT services as computing utilities, in: Proceedings of 10th IEEE International Conference on High Performance Computing and Communications, (2008).Google Scholar
  105. 105.
    X. Chu, K. Nadiminti, C. Jin, S. Venugopal, R. Buyya, Aneka: Next-generation enterprise grid platform for e-Science and e-Business applications, in: e-Science and Grid Computing, IEEE International Conference on, (2007), pp. 151–159.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Uroš Čibej
    • 1
  • Anthony Sulistio
    • 2
  • Rajkumar Buyya
    • 2
  1. 1.Faculty of Computer and Information ScienceUniversity of Ljubljana1000 LjubljanaSlovenia
  2. 2.Grid Computing and Distributed Systems LaboratoryThe University of MelbourneAustralia

Personalised recommendations