Abstract
Advances in computer technology and network technology provide a chance that multiple distributed computational resources can be shared by Internet to solve large-scale computing problems. In this paper, we focus on computational resources, and present an incentive sharing approach for this kind of resources in the autonomous environment. Firstly, we describe the sharing scenario, in which the barter auction mechanism is adopted and the deed is used to keep the trace of trades between different resource control domains. Then we discuss the evaluation methodology for testing the proposed approach. Thirdly, the auction schema is described, and the calling strategy and the responding strategy of auction are introduced. The simulation is performed based on the synthetic workloads to evaluate the performance of the auction strategies, and experimental results indicate that the barter auction method can allow computational resource domains to provide better computing service to their users.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Rosenberg, A., Yurkewych, M.: Guidelines for scheduling some common computation-dags for internet-based computing. IEEE Transactions on Computers 54, 428–438 (2005)
Buyya, R., Abramson, D., Venugopal, S.: The grid economy. Proceedings of the IEEE 93, 698–714 (2005)
Feitelson, D.: Experimental analysis of the root causes of performance evaluation results: A backfilling case study. IEEE Transactions on Parallel and Distributed Systems 16, 175–182 (2005)
Cirne, W., Berman, F.: A model for moldable supercomputer jobs. In: Proceedings of 15th International conference on Parallel and Distributed Processing Symposium (IPDPS 2001), pp. 59–79. IEEE Computer Society, Los Alamitos (2001)
Waldspurger, C., Hogg, T., Huberman, B., Kephart, J., Stornetta, S.: Spawn: A distributed computational economy. IEEE Transactions on Software Engineering 18, 103–117 (1992)
Buyya, R.: Economic-based Distributed Resource Management and Scheduling for Grid Computing. PhD thesis, Monash University, Australia (2002)
Wolski, R., Plank, J., Brevik, J., Bryan, T.: Analyzing market-based resource allocation strategies for the computational grid. The International Journal of High Performance Computing Applications 15, 258–281 (2001)
Xiao, L., Zhu, Y., Ni, L.M., Xu, Z.: Gridis: an incentive-based grid scheduling. In: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium, pp. 65b – 65b. IEEE Computer Society Press, Los Alamitos (2005)
Cooper, B., Garcia-Molina, H.: Peer-to-peer data preservation through storage auctions. IEEE Transactions on Parallel and Distributed Systems 16, 246–257 (2005)
Ozturan, C.: Resource bartering in data grids. Scientific Programming 12, 155–168 (2004)
Aix affinity with linux: Technology paper (Technical report), http://www-03.ibm.com/servers/aix/products/aixos/linux/affinity_linux.pdf
Feitelson, D., Rudolph, L., Schwiegelshohn, U., Sevcik, K., Won, P.: Theory and practice in parallel job scheduling. In: Feitelson, D.G., Rudolph, L. (eds.) IPPS-WS 1997 and JSSPP 1997. LNCS, vol. 1291, pp. 1–34. Springer, Heidelberg (1997)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Weng, C., Li, M., Lu, X. (2008). An Incentive Approach for Computational Resource Sharing in the Autonomous Environment. In: Wu, S., Yang, L.T., Xu, T.L. (eds) Advances in Grid and Pervasive Computing. GPC 2008. Lecture Notes in Computer Science, vol 5036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68083-3_13
Download citation
DOI: https://doi.org/10.1007/978-3-540-68083-3_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68081-9
Online ISBN: 978-3-540-68083-3
eBook Packages: Computer ScienceComputer Science (R0)