• DocumentCode
    1611496
  • Title

    Heuristic Based Time-Aware Service Selection Approach

  • Author

    Guidara, Ikbel ; Guermouche, Nawal ; Chaari, Tarak ; Tazi, Said ; Jmaiel, Mohamed

  • Author_Institution
    LAAS, Toulouse, France
  • fYear
    2015
  • Firstpage
    65
  • Lastpage
    72
  • Abstract
    QoS-based service selection is one of the important requirements in Service Oriented Computing (SOC). A challenging task towards this purpose is the selection of the best combination of services that fulfils user´s requirements while meeting quality of service (QoS) constraints. This challenge becomes more complex when dealing with time-dependent QoS values and temporal properties. Indeed, during the selection, mutual dependencies between the different temporal constraints may arise so that the selection of each service may influence or be influenced by the selection of other services. On other side, to find the best solution, all potential combinations must be compared. However, the number of these combinations may be very high, which can present a barrier for enabling effective service selection. In this paper, we present a heuristic based time-aware service selection approach to efficiently select a close-to-optimal combination of services. First, pruning techniques are adopted to reduce the search space. Second, a novel heuristic approach is proposed based on service clustering, constraints decomposition and local selection while considering both QoS and temporal constraints. Finally, experiments which confirm the feasibility and effectiveness of the proposed approach in terms of its timeliness and optimality, are conducted.
  • Keywords
    feature selection; pattern clustering; quality of service; search problems; service-oriented architecture; QoS-based service selection; SOC; close-to-optimal combination; constraint decomposition; heuristic based time-aware service selection; pruning technique; quality of service; search space reduction; service clustering; service oriented computing; Business; Clustering algorithms; Constraint optimization; Partitioning algorithms; Quality of service; Silicon; System-on-chip; Clustering; Constraints decomposition; Heuristic; Pruning; Service selection; Time-dependent QoS;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Services (ICWS), 2015 IEEE International Conference on
  • Conference_Location
    New York, NY
  • Print_ISBN
    978-1-4673-7271-8
  • Type

    conf

  • DOI
    10.1109/ICWS.2015.19
  • Filename
    7195553