Abstract
For a number of services with similar functionality reputation has been regarded as one of the most important methods to identify good ones from bad ones. However, a composite service, which is composed of multiple component services, obtains only one score (or feedback) after every invocation. In order to compute the reputation of each component service, it is necessary for the composite service to distribute this score to its component services. How to achieve a fair distribution is a challenging issue, as each component service may perform differently in contributing to the success or failure of the composite service. Although several efforts have been made for this problem, they do not consider the context of composition, which makes the distribution unfair. Therefore, in this paper, we propose a fair score distribution framework which combines the context of component services and their runtime performance. We distinguish two aspects contexts of a component service: structure-related importance and community-related replaceability, and adopt graph theory and dominating relationship technique to compute them, respectively. Experimental results show that our approach can achieve a more reasonable and fair score distribution than other existing methods.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Papazoglou MP, Georgakopoulos D (2003) Service-oriented computing. Commun ACM 46(10): 25–65
Haesen R, Snoeck M, Lemahieu W, Poelmans S (2008) On the definition of service granularity and its architectural impact. In: Proceedings of international conference on advanced information systems engineering (CAiSE’08), pp 375–389
Web Services Business Process Execution Language Version 2.0, OASIS Standard, 11, April, (2007). http://docs.oasis-open.org/wsbpel/2.0/wsbpel-v2.0.html. Accessed 5 March 2011
Zaki M, Bouguettaya A (2009) RATEWeb: reputation assessment for trust establishment among web services. VLDB J 18: 885–911
Li Z, Wang S (2005) The foundation of E-commerce: social reputation system-a comparison between American and China. In: Proceedings of international conference on electronic commerce (CEC’05), ACM Press, New York, pp 230–232
Chiu DKW, Leung H-F, Lam K-M (2009) On the making of service recommendations: an action theory based on utility, reputation, and risk attitude. Exp Syst Appl 36: 3293–3301
Li X, Liu L (2004) PeerTrust: supporting reputation-based trust for peer-to-peer electronic communities. IEEE Trans Knowl Eng 16(7): 843–857
Maximilien EM, Singh MP (2002) Conceptual model of web services reputation. SIGMOD Rec 31(4): 36–41
Binder BW, Drago ML, Ghezzi C (2009) REMAN:a pro-active reputation management infrastructure for composite web service. In: IEEE international conference on software engineering (ICSE’2009), May 16–24, pp 623–626
Binder BW, Drago ML, Ghezzi C (2008) Transparent reputation management for composite web service. In: IEEE international conference on web services (ICWS’2008), September 23–26, pp 621–628
Conner W, Lyengar A, Mikalsen T (2009) A trust management framework for service-oriented environments. In: International conference on world wide-web (WWW’2009), April 20–24, pp 891–900
Nepal S, Malik Z, Bouguettaya A (2009) Reputation propagation in composite services. In: IEEE international conference on web services (ICWS’2009), September, pp 295–302
Li L, Wang Y (2008) A trust vector approach to service-oriented application. In: IEEE international conference on web services (ICWS’2008), September 23–26, pp 621–628
Liu A, Li Q, Huang L, Wen S, Tang C (2010) Reputation-driven recommendation of services with uncertain QoS. In: Proceedings of IEEE Asia-Pacific services computing conference (APSCC’2010), Hang Zhou, Dec., pp 6–10
Dellarocs C (2003) The digitalization of word-of-mouth: promise and challenges of online feedback mechanism. Manag Sci 49(10): 1407–1424
Sing MP, Huhns MN (2005) Service-oriented computing. Wiley Online Library, New York
Sabater J, Sierra C (2003) Reputation and social network analysis in multi-agent systems. In: Proceedings of the first international joint conference on autonomous agents and multiagent systems, Bologna, Italy, pp 475–482
Huynh TD, Jennings NR, Shadbolt NR (2006) Certified reputation: how an agent can trust a stranger. In: Proceedings of the fifth international joint conference on automomous agents and multiagent systems, Japan, pp 1217–1224
Kamvar SD, Scholosser MT, Garcia-Molina H (2003) The EigenTrsut algorithm for reputation management in P2P networks. In: International conference on world wide web (WWW’03), May 20–24
Zhou R, Hwang K (2007) PowerTrust: a robust and scalable reputation system for trusted peer-to-peer computing. IEEE Trans Parallel Distrib Syst 18(4): 472–560
Buchigger S, Boudec J-YL (2004) A robust reputation system for P2P and mobile ad-hoc networks. In: Proceeding of second workshop economics of P2P systems
Brinklov M, Sharp R (2007) Incremental trust in grid computing. In: Proceedings of the seventh IEEE international symposium on cluster computing and the grid, pp 135–144
Azzedin F, Maheswaran M, Mitra A (2006) Trust brokering and its use for resource matchmaking in public-resource grids. J Grid Comput 4(3): 247–263
Kreps DM, Wilson R (1982) Reputation and imperfect information. J Econ Theory 27(2): 253–279
Holmstrom B (1999) Managerial incentive problems: a dynamic perspective. Rev Econ Stud 66(1): 169–182
Huberman BA, Wu F (2004) The dynamics of reputation. J Stat Mech Theory Exp 2004:P04006
Zeng L, Benatallsh B, Ngu AHH, Dumas M, Kalagnanam J, Chang H (2004) QoS-aware middleware for web services composition. IEEE Trans Softw Eng 30(5): 311–327
Berbner R, Spahn M, Repp N, Heckmann Q, Steinmetz R (2006) Heuristics for QoS-aware web service composition. In: IEEE international conference on web services (ICWS), pp 72–82
Stein S, Payne TR, Jennings NR (2009) Flexible provisioning of web service workflows. ACM Trans Internet Technol 9(1), Article 2, p 45
Cambridge Dictionary Online. http://dictionary.cambridge.org/
Wen S, Li Q, Yue L, Liu A, Tang C (2010) Towards fair reputation propagation from a composite service to its component services. In: IEEE international conference on E-business engineering (ICEBE’2010), Nov. 10–12
Liu A, Li Q, Huang L, Xiao M, Liu H (2008) QoS-aware scheduling of web service. In: Proceedings of international conference on web-based information management (WAIM’08), pp 171–178
Opsahl T, Agneessens F, Skvoretz J (2010) Node centrality in weighted networks: generalizing degree and shortest paths. Soc Netw 32: 245–251
Alonso G, Casati F, Kuno H, Machiraju V (2004) Web services: concepts, architectures and applications. Springer, Berlin
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Wen, S., Li, Q., Yue, L. et al. CRP: context-based reputation propagation in services composition. SOCA 6, 231–248 (2012). https://doi.org/10.1007/s11761-012-0105-3
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11761-012-0105-3