A Performance-Based Methodology to Improve Grid Exploitation

Due to their complexity, the exploitation of Grid environments is not a trivial activity for many users, and a key factor is to enable a simplified and transparent orchestration of resources and jobs. Particularly critical is the deployment of matching procedures capable to effectively meet user's requirements with resources offer. We introduce GREEN a management tool primarily devoted to the matchmaking process, based on a performance characterization of both resources and job requirements. Leveraging on a two-level benchmarking methodology, GREEN allows users to express performance preference through an appropriate extension to Grid submission and description languages such as JSDL and Glue. Operating at intermediate level between applications and Grid middleware, GREEN reduces the gap between users' needs and available resources thus enabling a seamless exploitation of the Grid.

[1]  Andrea Clematis,et al.  A Distributed Approach for Structured Resource Discovery on Grid , 2008, 2008 International Conference on Complex, Intelligent and Software Intensive Systems.

[2]  Rajkumar Buyya,et al.  Workflow scheduling algorithms for grid computing , 2008 .

[3]  Eduardo Huedo,et al.  A framework for adaptive execution in grids , 2004, Softw. Pract. Exp..

[4]  Marios D. Dikaiakos Grid benchmarking: vision, challenges, and current status: Research Articles , 2007 .

[5]  Roger W. Hockney The science of computer benchmarking , 1995, Software, environments, tools.

[6]  Dan C. Marinescu,et al.  Resource Matching and a Matchmaking Service for an Intelligent Grid , 2004, International Conference on Computational Intelligence.

[7]  Arie Shoshani,et al.  The Grid 2: Blueprint for a New Computing Infrastructure (2nd edition), , 2003 .

[8]  Herwig Unger,et al.  Innovative Internet Community Systems, 4th InternationalWorkshop, IICS 2004, Guadalajara, Mexico, June 21-23, 2004, Revised Papers , 2006, IICS.

[9]  Alain Bui,et al.  A Random Walk Topology Management Solution for Grid , 2005, IICS.

[10]  Michael A. Frumkin,et al.  NAS Grid Benchmarks: A Tool for Grid Space Exploration , 2001, Proceedings 10th IEEE International Symposium on High Performance Distributed Computing.

[11]  Radu Prodan,et al.  Benchmarking Grid Applications for Performance and Scalability Predictions , 2010 .

[12]  Johan Tordsson,et al.  Grid resource brokering algorithms enabling advance reservations and resource selection based on performance predictions , 2008, Future Gener. Comput. Syst..

[13]  Karsten Schwan,et al.  Open Metadata Formats: Efficient XML-Based Communication for High Performance Computing , 2004, Cluster Computing.

[14]  Marios D. Dikaiakos,et al.  GridBench: A tool for the interactive performance exploration of Grid infrastructures , 2007, J. Parallel Distributed Comput..

[15]  Henri Casanova,et al.  Benchmark probes for grid assessment , 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

[16]  Ian Foster,et al.  The Grid 2 - Blueprint for a New Computing Infrastructure, Second Edition , 1998, The Grid 2, 2nd Edition.

[17]  Ian T. Foster,et al.  The anatomy of the grid: enabling scalable virtual organizations , 2001, Proceedings First IEEE/ACM International Symposium on Cluster Computing and the Grid.

[18]  Fatos Xhafa,et al.  Metaheuristics for scheduling in distributed computing environments , 2008 .

[19]  Min Cai,et al.  MAAN: A Multi-Attribute Addressable Network for Grid Information Services , 2003, Journal of Grid Computing.

[20]  Pedro A. Szekely,et al.  MAAN: A Multi-Attribute Addressable Network for Grid Information Services , 2003, Proceedings. First Latin American Web Congress.

[21]  Marios D. Dikaiakos,et al.  Grid benchmarking: vision, challenges, and current status , 2007, Concurr. Comput. Pract. Exp..