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Permanent link (DOI): https://doi.org/10.7939/R36Q2Q

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A multi-attribute service composition model in a dynamic environment Open Access

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Other title
Subject/Keyword
dynamic service composition
non-functional attributes
customer preferences
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Srivastava, Abhishek
Supervisor and department
Sorenson, Paul G. (Computing Science)
Examining committee member and department
Stroulia, Eleni (Computing Science)
Muller, Hausi (Computer Science, University of Victoria)
Wong, Kenny (Computing Science)
Patterson, Raymond (Alberta School of Business)
Department
Department of Computing Science
Specialization

Date accepted
2011-08-28T13:34:14Z
Graduation date
2011-11
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
Dynamic service composition involves the run-time selection of service elements that are combined to form a larger more complex composite application. There are several issues in dynamic service composition that are examined in this thesis. First, the existence of a large number of service elements with similar or identical functionalities makes it difficult to select appropriate service elements dynamically. To address this issue, we utilize the non-functional attributes of the service elements. The non-functional attribute values are discriminating factors on which one service element is deemed better than other candidates for the specific composition. We first present novel selection techniques based on single attribute criteria for the three non-functional attributes: reliability, waiting-time, and reputation. More generally, however, there are usually a number of service attributes, which include non-functional and functional attributes, associated with each service element. In addition, the customers who are the ultimate stakeholders of the composition process have varied preferences for these service attributes. To incorporate simultaneously all the service attributes and the preference weights of service customers, we introduce a unifying factor called affinity that is a function of all the service attributes of the service elements and the preferences articulated by customers. The affinity factor is embedded in a new model called the Affinity Model that is used for the dynamic selection of service elements to form service compositions. The Affinity Model utilizes the affinity values calculated to select service elements following a Greedy algorithm where the service elements with the largest affinity values are selected for each functionality. The efficacy of the Affinity Model is validated by simulating the service composition process as a game called the Ambitious-Traveler. The validation procedure involves a set of human participants who volunteer to play the Ambitious-Traveler game. The game is simultaneously played in an automated manner using selection decisions made by the Affinity Model. The results show a comparable or superior performance by the Affinity Model to that of the human players in 90% of the trials. This validates the hypothesis that the Affinity Model is capable of making service selections that are comparable to or better than the intuitive judgement of humans.
Language
English
DOI
doi:10.7939/R36Q2Q
Rights
License granted by Abhishek Srivastava (sr16@ualberta.ca) on 2011-08-23T21:37:27Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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