CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Analysis the Performance of CDS Algorithm with Constrained Price and Deadline in Grid Computing

by Deepti Gupta, Verender Singh Madra
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 9
Year of Publication: 2015
Authors: Deepti Gupta, Verender Singh Madra
10.5120/21730-4895

Deepti Gupta, Verender Singh Madra . Analysis the Performance of CDS Algorithm with Constrained Price and Deadline in Grid Computing. International Journal of Computer Applications. 122, 9 ( July 2015), 29-34. DOI=10.5120/21730-4895

@article{ 10.5120/21730-4895,
author = { Deepti Gupta, Verender Singh Madra },
title = { Analysis the Performance of CDS Algorithm with Constrained Price and Deadline in Grid Computing },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 9 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 29-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number9/21730-4895/ },
doi = { 10.5120/21730-4895 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:10:08.504521+05:30
%A Deepti Gupta
%A Verender Singh Madra
%T Analysis the Performance of CDS Algorithm with Constrained Price and Deadline in Grid Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 9
%P 29-34
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Clusters, grids and P2P networks enable aggregation of resources and creation of virtual enterprises for solving large scale problems. Resource planning in Grid computing is an advanced task owing to the heterogeneous and dynamic nature of the resources. Trade based scheduling is more attractive from point of view of business. This paper describes the design, implementation and evaluation of an economic strategy based Grid resource scheduling mechanism. It takes into account the architectural features, special requirements of computational Grids with ensuring economic efficiency. The design is concentrated on two goals. Mainly, the Grid computing environment is regarded as a distributed two-sided trade market; competition occurs on both sides of the market, users and resource providers simultaneously. Next, it needs to provide an effective scheduling environment that must have the ability to offer resources with minimal delay to jobs. In this dissertation, a framework for economic strategy based Grid scheduling is proposed. The framework entities such as users, broker and resources employ Continuous Double Scheduling Algorithm to decide the final values of prices and deadlines. We evaluated the performance of the different strategies of CDS with respect to each other and with the Offer Based Scheduling.

References
  1. Rajkumar Buyya and srikumar venugopal. A Gentle introduction of grid computing and technologies, 2005.
  2. R. Buyya and M. Murshed. GridSim: A Toolkit for the Modeling and Simulation of Distributed Resource Management and Scheduling for Grid Computing. Concurrency & Computation: Practice and Experience, Dec. 2002.
  3. Anthony Sulistio, Uros Cibej, Srikumar Venugopal, Borut Robic and Rajkumar Buyya. A Toolkit for Modelling and Simulating Data Grids: An Extension to GridSim, Concurrency and Computation: Practice and Experience (CCPE), vol. 20, Wiley Press, New York, USA, Sep. 2008.
  4. Anthony Sulistio and Rajkumar Buyya. The GridSim Toolkit, Poster for the 3th International Conference on e-Science and Grid Computing (e-Science'07), Dec. 10-13, 2007.
  5. R. Buyya. Economic-based distributed resource management and scheduling for grid computing. PhD thesis, Monash university, Melbourne, Australia,2002.
  6. H. Chen and M. Maheswaran. Distributed dynamic scheduling of composite tasks on grid computing systems. In IPDPS, 2002.
  7. Rajkumar Buyya and Anthony Sulistio. Service and Utility Oriented Data Centers and Grid Computing Environments: Challenges and Opportunities for Modeling and Simulation Communities. In Proceeding of the 41st Annual Simulation Symposium (ANSS'08), Ottawa, Canada, Apr. 13-16, 2008.
  8. Krepska, T. Kielmann, R. Sirvent and R. M. Badia. A service for reliable execution of grid applications. In Achievements in European Research on Grid Systems. Springer Verlag, 2007.
  9. M. Parashar and C. Lee. Proceeding of IEEE: specific issue on grid computing, volume 93, issue 3, IEEE Press, New York, USA, March 2005.
  10. Rajiv Ranjan, Rajkumar Buyya and Aaron Harwood. A Case for Decentralized Grid Resource Indexing.
  11. Schmidt and M. Parashar. Flexible information discovery in decentralized distributed systems. In the Twelfth International Symposium on High Performance Distributed Computing (HPDC-12), June, 2003.
  12. Iamnitchi and I. Foster. On fully decentralized resource discovery in grid environments. International Workshop on Grid Computing, Denver, CO, 2001.
  13. Iamnitchi and I. Foster. A peer-to-peer approach to resource location in grid Environments, 2004.
  14. Czajkowski K. , Foster I. , Kesselman C. , "Resource coallocation in computational grids", Proceedings of Inter Symp on High Performance Distributed Computing, California IEEE Computer Society Press, 219?228, 1999.
  15. Goswami K. and Gupta A. . . Resource Selection in Grids using Contract Net. 16th Euromicro Conference on Parallel, Distributed and Network- Based Processing (PDP), Feb. 2008.
  16. Stylianos Ziko and Helen D. Karatza. Resource Allocation Strategies in a 2-level Hierarchical Grid System", 41st Annual Simulation Symposium, 2007.
  17. Ravish Mahajan and Arobinda Gupta. Scalable Contract Net Based Resource Allocation Strategies for Grids. Ninth International Conference on Parallel and Distributed Computing, Applications and Technologies, 2008.
  18. Rajkumar Buyya and Anthony Sulistio. GridSim: Java-based Modelling and Simulation of Computational Economy-based Scheduling for Grid Computing, Poster Exhibit @ CCGrid 2001: The First IEEE/ACM International Symposium on Cluster Computing and the Grid, Brisbane, Australia, May 15-18, 2001.
  19. Rajkumar Buyya, David Abramson, Jonathan Giddy, An Economy Driven Resource Management Architecture for Global Computational Power Grids , The 2000 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA 2000), Las Vegas, USA, June 26-29, 2000.
  20. Sid Ahmed MAKHLOUF (1), Belabbas YAGOUBI, "Co-allocation in Grid Computing using Resources Offers and Advance Reservation Planning" Courrier du Savoir, 2012.
  21. Marco A. S. Netto, "Offer-based scheduling of deadline-constrained Bag-of-Tasks applications for utility computing systems", IPDPS, 2009, IEEE International Symposium on Parallel & Distributed Processing (IPDPS), pp. 1-11
  22. L. Chunlin and L. Layuan. An agent-based approach for grid computing,2003
  23. A. Iamnitchi and I. Foster. On fully decentralized resource discovery in grid environments. In International Workshop on Grid Computing, 2001.
  24. M. Maheswaran and K. Krauter. A parameter-based approach to resource discovery in grid computing systems. In Proceedings of the First International Workshop in Grid Computing, pages 181–190, 2000.
  25. Berman and R. Wolski. The apples project: A status report. In Proceedings of the 8th NEC Research Symposium,, 1997.
  26. E. Sutherland. A futures market in computer time. Commun. ACM, 11(6):449–451, 1968.
  27. Nakai. Pricing computing resources: Reading between the lines and beyond. Technical report, National Aeronautics and Space Administration, 2002.
  28. A. Takefusa, S. Matsuoka, H. Casanova, and F. Berman. A study of dead-line scheduling for client-server systems on the computational grid. In HPDC'01: Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing (HPDC-10'01), pages 406–415. IEEE Computer Society, 2001.
  29. R. Montero, E. Huedo, and I. M. Llorente. Grid Scheduling Infrastructures with the GridWay Metascheduler, 2006.
  30. S. Venugopal, K. Nadiminti, H. Gibbins, and R. Buyya. Designing a resource broker for heterogeneous grids. Software-Practice and Experience, 38(8):793–826, 2008.
  31. S. Song, K. Hwang, and M. Macwan. Fuzzy trust integration for security enforcement in grid computing. In NPC, pages 9–21, 2004.
  32. A. Galstyan, K. Czajkowski, and K. Lerman. Resource allocation in the grid using reinforcement learning. In International Conference on Autonomous Agents and Multiagent Systems, 2004.
  33. M. Bsoul, I. Phillips, and C. Hinde. A framework for economic scheduling in grid computing using tender/contract-net model. In pgnet, 2006.
  34. X. He, X. Sun, and G. V. Laszewski. A qos guided scheduling algorithm for grid scheduling, 2003
  35. F. Howell and R. McNab, SimJava: A Discrete Event Simulation Package For Java With Applications In Computer Systems Modelling, First International Conference on Web-based Modelling and Simulation, San Diego, CA, Society for Computer Simulation, January 1998.
Index Terms

Computer Science
Information Sciences

Keywords

Offer based Scheduling Grid Computing Continuous double scheduling

Powered by PhDFocusTM