IJBTT

Resource Overbooking: Using Aggregation Profiling in large scale Resource Discovery

	International Journal of Engineering Trends and Technology (IJETT)
	© 2011 by IJETT Journal
	Volume-1 Issue-1
	Year of Publication : 2011
	Authors :Dr.M.Helda Mercy, C.Anand, T.S. Suganya

Citation

Dr.M.Helda Mercy, C.Anand, T.S. Suganya "Resource Overbooking: Using Aggregation Profiling in large scale Resource Discovery". International Journal of Engineering Trends and Technology (IJETT),V1(1):52-54 May to June 2011. ISSN:2231-5381. www.ijettjournal.org. Published by Seventh Sense Research Group.

Abstract

Resource discovery is an important process for finding suitable nodes that satisfy application requirements in large loosely coupled distributed systems. Besides inter node heterogeneity, many of these systems also show a high degree of intra node dynamism, so that selecting nodes based only on their recently observed resource capacities can lead to poor deployment decisions resulting in application failures or migration overheads. However, most existing resource discovery mechanisms rely mainly on recent observations to achieve scalability in large systems. In this paper, we propose the notion of a resource bundle — a representative resource usage distribution for a group of nodes with similar resource usage patterns — that employs two complementary techniques to overcome the limitations of existing techniques: resource usage histograms to provide statistical guarantees for resource capacities and clustering - based resource aggregation to achieve scalabil ity. Using trace - driven simulations and data analysis of a month - long Planet Lab trace, we show that resource bundles are able to provide high accuracy for statistical resource discovery, while achieving high scalability. We also show that resource bundles are ideally suited for identifying group - level characteristics (e.g., hot spots, total group capacity).

References

[1] D. Anderson, “BOINC: A System for Public - Resource Computing and Storage,” Proc. IEEE/ACM Int’l Workshop Grid Computing (GRID), 2004.
[2] V. Lo, D. Zappala, D. Zhou, Y. Liu, and S. Zhao, “Cluster Computing on the Fly: P2P Sche duling of Idle Cycles in the Internet,” Proc. IEEE Fourth Int’l Conf. Peer - to - Peer Systems, 2004.
[3] Grid2: Blueprint for a New Computing Infrastructure,I. Foster and C. Kesselman, eds. M. Kauffman, 2004.
[4] Y. Chawathe, S. Ratnasamy, L. Breslau, N. Lanh am, and S.Shenker, “Making Gnutella Like P2P Systems Scalable,” Proc. ACM SIGCOMM, Aug. 2003.
[5] B. Cohen, “Incentives Build Robustness in Bittorrent,” Proc. First Workshop the Economics of P2P Systems, June 2003.
[6] S. Guha, N. Daswani, and R. Jain, “An Experimental Study of the Skype Peer - to - Peer Voip System,” Proc. Int’l Workshop Peer - to - Peer Systems (IPTPS), 2006.
[7] B. Chun, D. Culler, T. Roscoe, A. Bavier, L. Peterson, M. Wawrzoniak, and M. Bowman, “PlanetLab: An Overlay Testbed for Broad - Coverage Services,” ACM SIGCOMM Computer Comm. Rev., vol. 33, no. 3, pp. 3 - 12, July 2003.
[8] A. Iamnitchi and I. Foster, “On Fully Decentralized Resource Discovery in Grid Environments,” Proc. IEEE/ACM Int’l Workshop Grid Computing (GRID), 2001.
[9] P. Yalagandula and M. Dahlin, “A Scalable Distributed Information Management System,” Proc. ACM SIGCOMM, 2004.
[10] B. Chun, J.M. Hellerstein, R. Huebsch, P. Maniatis, and T. Roscoe, “Design Considerations for Information Planes,” Proc. Workshop Real, Large Distributed Systems (WORLDS ’04), Dec. 2004.
[11] J.M. Schopf, “A Practical Methodology for Defining Histograms for Predictions and Scheduling,” NU technical report, 1999.
[12] S.Zhong http://www.cse.fau.edu/~zhong/software/index.htm, 2009.
[13] A. Gupta, D. Agrawal, and A.E. Abbadi, “Distributed Resource Discovery in Large Scale Computing Systems,” Proc. Int’l Symp. Applications and the Internet (SAINT), 2005.
[14] R.V. Renesse, K.P. Birman, and W. Vogels, “Astrolabe: A Robust and Scalable Technology for Distributed System Monitoring, Management, and Data Mining,” ACM Trans. Computer Systems, vol. 21, no. 2, pp. 164 - 206, 2003.
[15] J. Cappos and J.H. Hartman, “San Ferm? ?n: Aggregating Large Data Sets Using a Binomial Swap Forest,” Proc. USENIX Symp. Networked Systems Design and mplementation (NSDI), 2008.
[16] J. Mickens and B. Noble, “Exploiting Availability Prediction in Distri buted Systems,” Proc. USENIX Symp. Networked Systems Design and Implementation (NSDI ’06), May 2006.