Integrated resource management for lambda-grids: The Distributed Virtual Computer (DVC)

The Distributed Virtual Computer (DVC) is the key unifying element of the OptIPuter software architecture. It provides a simple, clean abstraction for applications or higher-level middleware, allowing them to use lambda-grids with the same convenience as a VPN. The DVC is successful because it employs integrated network and end-resource selection, achieving high quality results so that there is little incentive for end-users to expose and manage lower-level interfaces. We describe the development of the DVC abstraction, key results, and experience with multiple applications and testbeds.

[1]  R. V. van Nieuwpoort,et al.  The Grid 2: Blueprint for a New Computing Infrastructure , 2003 .

[2]  Andrew A. Chien,et al.  Collaborative data visualization for Earth Sciences with the OptIPuter , 2006, Future Gener. Comput. Syst..

[3]  Ian T. Foster,et al.  The Anatomy of the Grid: Enabling Scalable Virtual Organizations , 2001, Int. J. High Perform. Comput. Appl..

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

[5]  Robert L. Grossman,et al.  Teleimmersion and Visualization with the OptIPuter , 2002 .

[6]  Nut Taesombut Coordinated resource management for guaranteed high performance and efficient utilization in Lambda-Grids , 2007 .

[7]  Scott Campbell,et al.  USER-MANAGED END-TO-END LIGHTPATH PROVISIONING OVER CA*NET 4 , 2003 .

[8]  Andrew A. Chien,et al.  The Composite Endpoint Protocol (CEP): scalable endpoints for terabit flows , 2005, CCGrid 2005. IEEE International Symposium on Cluster Computing and the Grid, 2005..

[9]  Andrew A. Chien,et al.  GTP: group transport protocol for lambda-Grids , 2004, IEEE International Symposium on Cluster Computing and the Grid, 2004. CCGrid 2004..

[10]  Andrew A. Chien,et al.  Distributed virtual computers (DVC): simplifying the development of high performance Grid applications , 2004, IEEE International Symposium on Cluster Computing and the Grid, 2004. CCGrid 2004..

[11]  William Gropp,et al.  Beowulf Cluster Computing with Linux , 2003 .

[12]  Kazunori Nozaki,et al.  Real-time multi-scale brain data acquisition, assembly, and analysis using an end-to-end OptIPuter , 2006, Future Gener. Comput. Syst..

[13]  Andrew A. Chien,et al.  The OptIPuter , 2003, CACM.

[14]  Andrew A. Chien,et al.  Efficient resource description and high quality selection for virtual grids , 2005, CCGrid 2005. IEEE International Symposium on Cluster Computing and the Grid, 2005..

[15]  Yuan Cao,et al.  Multi-domain Lambda Grid data portal for collaborative Grid applications , 2006, Future Gener. Comput. Syst..

[16]  Robert L. Grossman,et al.  UDT: UDP-based data transfer for high-speed wide area networks , 2007, Comput. Networks.

[17]  Miron Livny,et al.  Condor: a distributed job scheduler , 2001 .

[18]  Andrew A. Chien,et al.  Evaluating network information models on resource efficiency and application performance in lambda-grids , 2007, Proceedings of the 2007 ACM/IEEE Conference on Supercomputing (SC '07).

[19]  Ann Zimmerman,et al.  The Biomedical Informatics Research Network , 2008 .

[20]  Andrew A. Chien,et al.  Realistic Modeling and Svnthesis of Resources for Computational Grids , 2004, Proceedings of the ACM/IEEE SC2004 Conference.