Although the optimal solution is obtained, two significant issues for debate remain.
First, the normalization process. A normalization of the attributes is not always nec-essary for solving MADM problems, but it may be essential for some methods, like Maxmin, simple additive weighting (SAW), ELECTRE, etc., to facilitate the computational problems inherent in the presence of the distinct scales of the per-formance rating matrix [17]. The aim of normalization is to obtain a comparable scale. Obviously, normalization is necessary in the processing of fuzzy data, to rank the web services compatibily, whose performance rating needs to be located in the interval[0,1]. In the traditional LINMAP method, users constantly convert from the distinct scales of ratings to a numerically comparable scale only, where the data of decision matrix is in nonfuzzy form. For instance, we translate all the ratings into the interval[−10,10]as in case I for benefit and cost attributes.
Second, a reliable solution. From the solution process of the two cases, one could note that when the number of attributes exceeds the number of service alternatives, then it is not easy to yield a reliable solution of weight by the LIMAP. For example, in case II, three attributes are used for assessing five alternatives that is,i=5 and j=3, then the proposed model can gain a consistent solution when i>j according to suggestions in [17].
Moreover, it may setwj,δ, intending to stimulate the feasible solutions for ob-taining a non-trivial solution of the weight of QoS attributes by adjustingδ. The tar-get of consensus-based weighting is to obtain a compromise solution of weight vec-tors among items of QoS attributes in the LINMAP method. From the two distinct cases and trial and error examples, we knew that the optimal solution sometimes
tends towards converging to a single item of weight of QoS attributes, except that the value of specific attributes are distributed equally or scattered in an average way.
7.6 Conclusion
This work presents a new approach to obtaining a consensual weight of QoS at-tributes using a fuzzy linear program for QoS-aware service selection, which allows service consumers to reach consensus on the contents of services, even though they have different opinions and preferences. In addition, it can effectively alleviate the differences of QoS characteristics by minimizing the inconsistence measurement in the WS selection, find the optimal solution of weights of QoS attribute alternatives as well as the fuzzy positive ideal solution. Future work will focus on the investiga-tion of other intelligent approaches such as genetic algorithms, simulated annealing and evolutionary computation in order to seek an efficient solution by improving the search effectiveness of feasible solutions.
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Trust and Reputation
Sarah N. Lim Choi Keung and Nathan Griffiths
Abstract Trust and reputation have become standard approaches for supporting the management of interactions in distributed environments. Several alternative ap-proaches have been proposed that take a wide range of apap-proaches, including socio-cognitive, computational, and reputational mechanisms. In this chapter we introduce the various approaches to trust and reputation, and discuss how they relate to agents in a service-oriented computing context.
8.1 Introduction
In this chapter we consider service-oriented computing (SOC) from an agent per-spective. Service advertisement, discovery and selection can be seen as processes carried out by agents. The agent view of SOC holds for the various settings in which SOC is used, including peer-to-peer systems, Grid computing and e-commerce.
Trust and reputation are useful in all these settings. As we progress from simple to complex settings the issues change, and we need more complex trust and reputa-tion mechanisms.
Sarah N. Lim Choi Keung
Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK e-mail:S.N.Lim.Choi.Keung@dcs.warwick.ac.uk
Nathan Griffiths
Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK e-mail:nathan@dcs.warwick.ac.uk
N. Griffiths, K.-M. Chao (eds.),Agent-Based Service-Oriented Computing, 189 Advanced Information and Knowledge Processing,
DOI 10.1007/978-1-84996-041-0 8, cSpringer-Verlag London Limited 2010