Skip to main content
Log in

Influence of Network Characteristics on Application Performance in a Grid Environment

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

In grid computing, a key issue is how limited network resources can be shared by communications by various applications more effectively in order to improve application-level performance, e.g., by reducing the completion time for an individual application and/or set of applications. Communication by an application changes the condition of the network resources, which may, in turn, affect communications by other applications, and thus may degrade their performance. In this paper, we examine the characteristics of traffic generated by typical grid applications, and the effect of the round-trip time and bottleneck bandwidth on the application-level performance (i.e., completion time) of these applications. Our experiments showed that the impact of network conditions on the performance of various applications and the impact of application traffic on network conditions differed considerably depending on the application. These results suggest that effective allocation of network resources must take into account the network-related properties of individual applications.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. K. Aida and T. Osumi, A Case Study in Running a Parallel Branch and Bound Applications, in Proc. of the 2005 International Symposium on Application and the Internet (SAINT2005) (2005) pp. 164–173.

  2. D.H. Bailey, E. Barszcz, J.T. Barton, D.S. Browning, R.L. Carter, L. Dagurm, R.A. Fatoohi, P.O. Federickson, T.A. lasinski, R.S. Schreiber, H.D. Simon, V. Venkatakrishnanand S. K. Weeratunga, The NAS parallel benchmarks, International Journal of Supercomputer Applications 5(3) (1991) 66–73.

    Google Scholar 

  3. R. Buyya, High performance cluster computing: Programming and applications, Prentice Hall PTR, Vol 2.(1999).

  4. A. Elwalid, C. Jin, S. Low and I. Widjaja, MATE: MPLS adaptive traffic engineering, in Proc. of the Infocom Anchorage (2001) pp. 1300–1309.

  5. Empirix Packet Sphere. http://www.empirix.com

  6. I. Foster and C. Kesselman, The GRID Blueprint for a New Computing Infrastructure, Morgan Kaufmann Publishers (1998).

  7. I. Foster, C. Kesselman and S. Tuecke, The Anatomy of the Grid}: Enabling Scalable Virtual Organizations, International Journal of Supercomputer Applications 15(3) (2001) 200–222.

    Article  Google Scholar 

  8. T. Guven, C. Kommareddy, R. La, M. Shayman and S. Bhattacharjee, Measurement Based Optimal Multi-path Routing in Proc. of the Infocom (2004).

  9. iperf—The TCP/UDP Bandwidth Measurement Tool. http://dast.nlanr.net/Projects/Iperf

  10. R. Kawahara, An Adaptive Load Balancing Method for Multiple Paths Using Flow Statistics and Its Performance Analysis, IEICE Transactions on Communications, Vol. E87-B(7) (2004) 1993–2003.

    Google Scholar 

  11. H. Koide and Y. Oie, A New Task Scheduling Method for Distributed Programswhich Require Memory Management in Grids, in Proc. of Proposed SAINT2004 Workshop 8: High Performance Grid Computing and Networking (2004) pp. 666–673.

  12. N.S.V. Rao, Net Lets: End-To-End Qo S Mechanisms for Distributed Computing in Wide-Area Networks Using Two-Paths, in Proc. of the First International Conference on Internet Computing (2001) pp. 475–478.

  13. A. Plaat, H.E. Bal and R.F.H. Hofman, Sensitivity of parallel applications to largedifferences in bandwidth and latency in two-layerinterconnects, in Proc. of the 5th High Perfromance Computer Architecture (1999) pp. 244–253.

  14. The ACM International Collegiate Programming Contest Japan Domestics. (2001). Probrem C Jigsaw Puzzle for Computers http://www.fun.ac.jp/icpc/domestic_problems.html

  15. T. Tobita and H. Kasahara, A standard task graph set for fair evaluation ofmultiprocessor scheduling algorithms, Journal of Scheduling 5(5) (2002) 379–394.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yoshinori Kitatsuji.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kitatsuji, Y., Yamazaki, K., Koide, H. et al. Influence of Network Characteristics on Application Performance in a Grid Environment. Telecommun Syst 30, 99–121 (2005). https://doi.org/10.1007/s11235-005-4320-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-005-4320-5

Keywords

Navigation