The popularity of the cloud computing paradigm is opening new opportunities for collaborative computing. In this paper we tackle a fundamental problem in open-ended cloud-based distributed computing platforms, i.e., the quest for potential collaborators. We assume that cloud participants are willing to share their computational resources for shared distributed computing problems, but they are not willing to disclose the details of their resources. Lacking such information, we advocate to rely on reputation scores obtained by evaluating the interactions among participants. More specifically, we propose a methodology to assess, at design time, the impact of different (reputation-based) collaborator selection strategies on the system performance. The evaluation is performed through statistical analysis on a volunteer cloud simulator.

Reputation-Based Cooperation in the Clouds / J. Zhou, N. Gal-Oz, J. Zhang, E. Gudes (Eds.); A. Celestini; A. Lluch Lafuente; P. Mayer; S. Sebastio; F. Tiezzi. - STAMPA. - (2014), pp. 213-220. [10.1007/978-3-662-43813-8_15]

Reputation-Based Cooperation in the Clouds

F. Tiezzi
2014

Abstract

The popularity of the cloud computing paradigm is opening new opportunities for collaborative computing. In this paper we tackle a fundamental problem in open-ended cloud-based distributed computing platforms, i.e., the quest for potential collaborators. We assume that cloud participants are willing to share their computational resources for shared distributed computing problems, but they are not willing to disclose the details of their resources. Lacking such information, we advocate to rely on reputation scores obtained by evaluating the interactions among participants. More specifically, we propose a methodology to assess, at design time, the impact of different (reputation-based) collaborator selection strategies on the system performance. The evaluation is performed through statistical analysis on a volunteer cloud simulator.
2014
9783662438121
Trust Management VIII, 8th IFIP WG 11.11 International Conference, IFIPTM 2014, Singapore, July 7-10, 2014. Proceedings
213
220
J. Zhou, N. Gal-Oz, J. Zhang, E. Gudes (Eds.); A. Celestini; A. Lluch Lafuente; P. Mayer; S. Sebastio; F. Tiezzi
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1243574
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