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Analyzing the Influence of Domain Features on the Optimality of Service Composition Algorithm

  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The problem of service composition with end-to-end QoS constraints has been proven to be an NP-hard problem and various evolutionary algorithms have been successfully applied to look for approximately optimal solutions within limited computation time. Favorable heuristic rules are considered as the key of such algorithms, and historical service usage data are widely utilized to help identify the distinct features of problem domains, used as heuristic that would greatly improve the optimality. However, our experiments show that the historical usage data is not always valid on the performance improvement, and there exist underlying dependencies between domain features and optimality of service composition algorithms, and different domain feature values require the composition algorithm to have different parameter settings to ensure the higher optimality. In this paper, we consider two domain features called Priori and Similarity along with some metrics measuring their richness and confidence level. Taking the service domain-oriented artificial bee colony algorithm (S-ABCSC) as an example, we try to discover the underlying dependencies between the domain features, the algorithm parameter settings, and the optimality of the algorithm to help algorithm designers judge whether the given historical usage data delineates valuable domain features that contribute to the optimality improvement, and setting up the best values of S-ABCSC parameters. Several experiments are conducted on different historical service usage data sets, and the results have been partially shown the effectiveness of our approach.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Services Computing, SCC 2015
EditorsPaul P. Maglio, Incheon Paik, Wu Chou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages427-434
Number of pages8
ISBN (Electronic)9781467372817
DOIs
StatePublished - 17 Aug 2015
Externally publishedYes
Event12th IEEE International Conference on Services Computing, SCC 2015, co-located with the 2015 IEEE Congress on Services, SERVICES 2015 - New York, United States
Duration: 27 Jun 20152 Jul 2015

Publication series

NameProceedings - 2015 IEEE International Conference on Services Computing, SCC 2015

Conference

Conference12th IEEE International Conference on Services Computing, SCC 2015, co-located with the 2015 IEEE Congress on Services, SERVICES 2015
Country/TerritoryUnited States
CityNew York
Period27/06/152/07/15

Keywords

  • Artificial Bee Colony Algorithm
  • Domain Feature
  • Parameter Setting
  • QoS-aware Service Composition

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