Abstract
Grid computing evolves toward an open computing environment, which is characterized by highly diversified resource providers and systems. As the control of each computing resource becomes difficult, the security of users’ job is often threatened by various risks occurred at individual resources in the network. This paper proposes two risk-aware resource brokering strategies: self-insurance and risk-performance preference specification. The former is a broker-driven method and the latter a user-driven method. Two mechanisms are analyzed through simulations. The simulation results show that both methods are effective for increasing the market size and reducing risks, but the user-driven technique is more cost-efficient.
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
Kenyon, C., Cheliotis, G.: Architecture requirements for commercializing Grid resources. In: Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing, pp. 215–224 (2002)
Kenyon, C., Cheliotis, G.: Grid resource commercialization: economic engineering and delivery scenarios. In: Grid resource management: state of the art and future trends, pp. 465–478. Kluwer Academic Publishers, Dordrecht (2004)
Foster, I., Kesselman, C., Tuecke, S.: The Anatomy of the Grid: Enabling Scalable Virtual Organizations. International Journal of High Performance Computing Applications 15, 200–222 (2001)
Minoli, D.: A Networking Approach to Grid Computing. Wiley-Interscience, Hoboken (2004)
Thanos, G., Courcoubetis, C., Stamoulis, G.: Adopting the Grid for Business Purposes: The Main Objectives and the Associated Economic Issues. In: Veit, D.J., Altmann, J. (eds.) GECON 2007. LNCS, vol. 4685, pp. 1–15. Springer, Heidelberg (2007)
Domingues, P., Sousa, B., Moura Silva, L.: Sabotage-tolerance and trust management in desktop grid computing. Future Generation Computer Systems 23, 904–912 (2007)
Plaszczak, P., Wellner, R.: Grid computing: the savvy manager’s guide. Elsevier/Morgan Kaufmann, San Francisco (2005)
Song, S., Kai, H., Yu-Kwong, K.: Risk-resilient heuristics and genetic algorithms for security-assured grid job scheduling. IEEE Transactions on Computers 55, 703–719 (2006)
Boden, T.: The Grid Enterprise — Structuring the Agile Business of the Future. BT Technology Journal 22, 107–117 (2004)
Bodin, L.D., Gordon, L.A., Loeb, M.P.: Information security and risk management. Commun. ACM 51, 64–68 (2008)
Bohme, R., Kataria, G.: Models and Measures for Correlation in Cyber-Insurance. In: Workshop on the Economics of Information Security (2006)
Gordon, L.A., Loeb, M.P., Sohail, T.: A framework for using insurance for cyber-risk management. Commun. ACM 46, 81–85 (2003)
Chen, P.-Y., Kataria, G., Krishnan, R.: Software diversity for information security. In: Workshop on the Economics of Information Security (WEIS), Harvard University, Cambridge, MA (2005)
Gordon, L.A., Loeb, M.P.: The economics of information security investment. ACM Trans. Inf. Syst. Secur. 5, 438–457 (2002)
Kesan, J., Majuca, R., Yurcik, W.: The Economic Case for Cyberinsurance. University of Illinois College of Law uiuclwps-1001 (2004)
Ogut, H., Menon, N., Raghunathan, S.: Cyber Insurance and IT Security Investment: Impact of Interdependent Risk. In: Workshop on the Economics of Information Security (2005)
Hwang, S., Kesselman, C.: A Flexible Framework for Fault Tolerance in the Grid. Journal of Grid Computing 1, 251–272 (2003)
McGough, A.S., Afzal, A., Darlington, J., Furmento, N., Mayer, A., Young, L.: Making the Grid Predictable through Reservations and Performance Modeling. The Computer Journal 48, 358–368 (2005)
Battre, D., Djemame, K., Kao, O., Voss, K.: Gaining users’ trust by publishing failure probabilities. In: Third International Conference on Security and Privacy in Communications Networks and the Workshops (SecureComm 2007), pp. 193–198 (2007)
Kleban, S.D., Clearwater, S.H.: Computation-at-risk: assessing job portfolio management risk on clusters. In: Proceedings of the 18th International Parallel and Distributed Processing Symposium, p. 254 (2004)
Yeo, C.S., Buyya, R.: Integrated Risk Analysis for a Commercial Computing Service. In: IEEE International Parallel and Distributed Processing Symposium (IPDPS 2007), pp. 1–10 (2007)
Huang, Z., Qiu, Y.: Resource trading using cognitive agents: A hybrid perspective and its simulation. Future Generation Computer Systems 23, 837–845 (2007)
Tobias, R., Hofmann, C.: Evaluation of free Java-libraries for social-scientific agent based simulation. Journal of Artificial Societies and Social Simulation 7 (2004)
Tesfatsion, L.: Agent-Based Computational Economics: A Constructive Approach to Economic Theory. In: Tesfatsion, L., Judd, K.L. (eds.) Handbook of Computational Economics, vol. 2, ch. 16, pp. 831–880. Elsevier, Amsterdam (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hwang, J., Park, J., Altmann, J. (2010). Two Risk-Aware Resource Brokering Strategies in Grid Computing: Broker-Driven vs. User-Driven Methods. In: Prasad, S.K., Vin, H.M., Sahni, S., Jaiswal, M.P., Thipakorn, B. (eds) Information Systems, Technology and Management. ICISTM 2010. Communications in Computer and Information Science, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12035-0_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-12035-0_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12034-3
Online ISBN: 978-3-642-12035-0
eBook Packages: Computer ScienceComputer Science (R0)