×

GridSim: a toolkit for the modeling and simulation of distributed resource management and scheduling for grid computing. (English) Zbl 1007.68630

Summary: Clusters, Grids, and peer-to-peer (P2P) networks have emerged as popular paradigms for next generation parallel and distributed computing. They enable aggregation of distributed resources for solving large-scale problems in science, engineering, and commerce. In Grid and P2P computing environments, the resources are usually geographically distributed in multiple administrative domains, managed and owned by different organizations with different policies, and interconnected by wide-area networks or the Internet. This introduces a number of resource management and application scheduling challenges in the domain of security, resource and policy heterogeneity, fault tolerance, continuously changing resource conditions, and politics. The resource management and scheduling systems for Grid computing need to manage resources and application execution depending on either resource consumers’ or owners’ requirements, and continuously adapt to changes in resource availability.
The management of resources and scheduling of applications in such large-scale distributed systems is a complex undertaking. In order to prove the effectiveness of resource brokers and associated scheduling algorithms, their performance needs to be evaluated under different scenarios such as varying number of resources and users with different requirements. In a Grid environment, it is hard and even impossible to perform scheduler performance evaluation in a repeatable and controllable manner as resources and users are distributed across multiple organizations with their own policies. To overcome this limitation, we have developed a Java-based discrete-event Grid simulation toolkit called GridSim. The toolkit supports modeling and simulation of heterogeneous Grid resources (both time- and space-shared), users and application models. It provides primitives for creation of application tasks, mapping of tasks to resources, and their management. To demonstrate suitability of the GridSim toolkit, we have simulated a Nimrod-G like Grid resource broker and evaluated the performance of deadline and budget constrained cost- and time-minimization scheduling algorithms.

MSC:

68U99 Computing methodologies and applications
68N15 Theory of programming languages
PDFBibTeX XMLCite
Full Text: DOI arXiv

References:

[1] (eds.). The Grid: Blueprint for a Future Computing Infrastructure. Morgan Kaufmann: San Mateo, CA, 1999.
[2] (ed.). Peer-to-Peer: Harnessing the Power of Disruptive Technologies. O’Reilly, 2001.
[3] The Grid: International efforts in global computing. Proceedings of the International Conference on Advances in Infrastructure for Electronic Business, Science, and Education on the Internet, Rome, Italy, 31 July-6 August 2000.
[4] High performance parametric modeling with Nimrod/G: Killer application for the global Grid? Proceedings International Parallel and Distributed Processing Symposium (IPDPS 2000), Cancun, Mexico, 1-5 May 2000. IEEE Computer Society Press, 2000.
[5] Nimrod/G: An architecture for a resource management and scheduling system in a global computational Grid. Proceedings 4th International Conference and Exhibition on High Performance Computing in Asia-Pacific Region (HPC ASIA 2000), Beijing, China, 14-17 May 2000. IEEE Computer Society Press, 2000.
[6] An economy driven resource management architecture for global computational power Grids. Proceedings of the 2000 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA 2000), Las Vegas, NV, 26-29 June 2000. CSREA Press, 2000.
[7] An evaluation of economy-based resource trading and scheduling on computational power Grids for parameter sweep applications. Proceedings of the 2nd International Workshop on Active Middleware Services (AMS 2000), Pittsburgh, PA, 1 August 2000. Kluwer Academic Press, 2000.
[8] Economic models for management of resources in peer-to-peer and Grid computing. SPIE International Conference on Commercial Applications for High-Performance Computing, Denver, CO, 20-24 August 2001.
[9] The World-Wide Grid. http://www.csse.monash.edu.au/?rajkumar/ecogrid/wwg/.
[10] Weissman, IEEE Distributed Systems Online 1 (2000)
[11] (ed.). High Performance Cluster Computing: Architectures and Systems, vol. 1. Prentice-Hall: Englewood Cliffs, NJ, 1999.
[12] CACI. Simscript: A Simulation Language for Building Large-scale, Complex Simulation Models. CACI Products Company: San Diego, CA. http://www.simscript.com/simscript.cfm.
[13] Bagrodia, IEEE Computer 31 (1998) · Zbl 05090807 · doi:10.1109/2.722293
[14] SimJava: A discrete event simulation package for Java with applications in computer systems modelling. Proceedings of the 1st International Conference on Web-based Modelling and Simulation, San Diego, CA. Society for Computer Simulation, 1998.
[15] The OMNeT++ discrete event simulation system. Proceedings of the European Simulation Multiconference (ESM 2001), Prague, Czech Republic, 6-9 June 2001.
[16] Aida, The International Journal of High Performance Computing Applications 14 (2000)
[17] The MicroGrid: A scientific tool for modeling computational Grids. Proceedings of IEEE Supercomputing (SC 2000), Dallas, TX, 4-10 November 2000.
[18] Simgrid: A toolkit for the simulation of application scheduling. Proceedings 1st IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGrid 2001), Brisbane, Australia, 15-18 May. IEEE Computer Society Press, 2001.
[19] Foster, International Journal of Supercomputer Applications 11 pp 115– (1997)
[20] cJVM: A single system image of a JVM on a cluster. Proceedings 29th International Conference on Parallel Processing (ICPP 99), Fukushima, Japan, September 1999. IEEE Computer Society Press, 1999.
[21] Parallel programming paradigms. High Performance Cluster Computing: Programming and Applications, vol. 2, ch. 2. Prentice-Hall: Englewood Cliffs, NJ, 1998.
[22] A deadline and budget constrained cost-time optimize algorithm for scheduling parameter sweep applications on the Grid. GridSim Toolkit Release Document, December 2001. http://www.buyya.com/gridsim.
[23] SPEC. SPEC CPU2000 Results. http://www.specbench.org/osg/cpu2000/results/cpu2000.html [30 January 2002].
[24] Buyya, Concurrency and Computation: Practice and Experience 14 pp 1507– (2002)
[25] Foundation for Intelligent Physical Agents (FIPA). Interaction and negotiation protocols. http://www.fipa.org/.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.