Binary Matchmaking for Inter-Grid Job Scheduling

Inter-Grid is a composition of small interconnected Grid domains; each has its own local broker. The main question is how to implement cross-Grid job scheduling achieving stability and load balancing, together with maintaining the local policies of interconnected Grid. Existing Inter-Grid methodologies are based on either centralised meta-scheduling or decentralised scheduling which carried out by local brokers, but without proper coordination. The question is how to perform matchmaking between a particular local job and the workers of a remote domain. Performing matchmaking remotely would result in computational overhead in case of many domains asking for match from one domain. Performing matchmaking locally requires transmission of the resource information set of the remote domain, which would result in high data traffic. This position paper introduces a coordinated scheduling technique for broker based inter-Grid architectures. Resource information set of each Grid domain is stored in a binary form. Matchmaking is carried out in the local domain using fast logical operations. Our primary results show that the proposed technique achieves 26 speedup in the matchmaking process compared to Condor negotiator, and a reduction up to 99.92 % in the resource information size compared to Condor ClassAd.

[1]  Message P Forum,et al.  MPI: A Message-Passing Interface Standard , 1994 .

[2]  Jennifer M. Schopf,et al.  A performance study of monitoring and information services for distributed systems , 2003, High Performance Distributed Computing, 2003. Proceedings. 12th IEEE International Symposium on.

[3]  Andrew S. Grimshaw,et al.  A federated model for scheduling in wide-area systems , 1996, Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing.

[4]  Hein Meling,et al.  Decentralized Service Allocation in a Broker Overlay Based Grid , 2009, CloudCom.

[5]  Antony I. T. Rowstron,et al.  Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems , 2001, Middleware.

[6]  Li Zhang,et al.  Tycoon: An implementation of a distributed, market-based resource allocation system , 2004, Multiagent Grid Syst..

[7]  Y. Charlie Hu,et al.  A Self-Organizing Flock of Condors , 2003, ACM/IEEE SC 2003 Conference (SC'03).

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

[9]  A. D. Meglio,et al.  Programming the Grid with gLite , 2006 .

[10]  Rajesh Raman,et al.  Matchmaking: distributed resource management for high throughput computing , 1998, Proceedings. The Seventh International Symposium on High Performance Distributed Computing (Cat. No.98TB100244).

[11]  Hervé Guyennet,et al.  Federation of resource traders in object-oriented distributed systems , 2000, Proceedings International Conference on Parallel Computing in Electrical Engineering. PARELEC 2000.

[12]  Hongzhang Shan,et al.  Job Superscheduler Architecture and Performance in Computational Grid Environments , 2003, ACM/IEEE SC 2003 Conference (SC'03).

[13]  Hein Meling,et al.  Slick: A Coordinated Job Allocation Technique for Inter-Grid Architectures , 2013, 2013 European Modelling Symposium.

[14]  David Abramson,et al.  Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid , 2000, Proceedings Fourth International Conference/Exhibition on High Performance Computing in the Asia-Pacific Region.

[15]  Miron Livny,et al.  Condor-a hunter of idle workstations , 1988, [1988] Proceedings. The 8th International Conference on Distributed.

[16]  Rajiv Ranjan,et al.  Coordinated Resource Provisioning in Federated Grids , 2007 .

[17]  Bernd Schuller,et al.  Chemomentum - UNICORE 6 Based Infrastructure for Complex Applications in Science and Technology , 2007, Euro-Par Workshops.

[18]  Ian T. Foster,et al.  Condor-G: A Computation Management Agent for Multi-Institutional Grids , 2004, Cluster Computing.