A survey of autonomic computing methods in digital service ecosystems

Dhaminda B. Abeywickrama (Corresponding Author), Eila Ovaska

    Research output: Contribution to journalArticleScientificpeer-review

    9 Citations (Scopus)

    Abstract

    Service engineering of digital service ecosystems can be associated with several challenges, such as change and evolution of requirements; gathering of quality requirements and assessment; and uncertainty caused by dynamic nature and unknown deployment environment, composition and users. Therefore, the complexity and dynamics in which these digital services are deployed call for solutions to make them autonomic. Until now there has been no upto-date review of the scientific literature on the application of the autonomic computing initiative in the digital service ecosystems domain. This article presents a review and comparison of autonomic computing methods in digital service ecosystems from the perspective of service engineering, i.e., requirements engineering and architecting of services. The review is based on systematic queries in four leading scientific databases and Google Scholar, and it is organized in four thematic research areas. A comparison framework has been defined which can be used as a guide for comparing the different methods selected. The goal is to discover which methods are suitable for the service engineering of digital service ecosystems with autonomic computing capabilities, highlight what the shortcomings of the methods are, and identify which research activities need to be conducted in order to overcome these shortcomings. The comparison reveals that none of the existing methods entirely fulfills the requirements that are defined in the comparison framework.
    Original languageEnglish
    Pages (from-to)1-31
    JournalService Oriented Computing and Applications
    Volume11
    Issue number1
    DOIs
    Publication statusPublished - 2017
    MoE publication typeA1 Journal article-refereed

    Fingerprint

    Ecosystems
    Requirements engineering
    Ecosystem services
    Chemical analysis
    Service engineering

    Keywords

    • autonomous systems
    • digital ecosystems
    • service engineering
    • self- features
    • quality attributes

    Cite this

    Abeywickrama, Dhaminda B. ; Ovaska, Eila. / A survey of autonomic computing methods in digital service ecosystems. In: Service Oriented Computing and Applications. 2017 ; Vol. 11, No. 1. pp. 1-31.
    @article{62a82b48d3cf4e88a0802254eec124f8,
    title = "A survey of autonomic computing methods in digital service ecosystems",
    abstract = "Service engineering of digital service ecosystems can be associated with several challenges, such as change and evolution of requirements; gathering of quality requirements and assessment; and uncertainty caused by dynamic nature and unknown deployment environment, composition and users. Therefore, the complexity and dynamics in which these digital services are deployed call for solutions to make them autonomic. Until now there has been no upto-date review of the scientific literature on the application of the autonomic computing initiative in the digital service ecosystems domain. This article presents a review and comparison of autonomic computing methods in digital service ecosystems from the perspective of service engineering, i.e., requirements engineering and architecting of services. The review is based on systematic queries in four leading scientific databases and Google Scholar, and it is organized in four thematic research areas. A comparison framework has been defined which can be used as a guide for comparing the different methods selected. The goal is to discover which methods are suitable for the service engineering of digital service ecosystems with autonomic computing capabilities, highlight what the shortcomings of the methods are, and identify which research activities need to be conducted in order to overcome these shortcomings. The comparison reveals that none of the existing methods entirely fulfills the requirements that are defined in the comparison framework.",
    keywords = "autonomous systems, digital ecosystems, service engineering, self- features, quality attributes",
    author = "Abeywickrama, {Dhaminda B.} and Eila Ovaska",
    year = "2017",
    doi = "10.1007/s11761-016-0203-8",
    language = "English",
    volume = "11",
    pages = "1--31",
    journal = "Service Oriented Computing and Applications",
    issn = "1863-2386",
    publisher = "Springer",
    number = "1",

    }

    A survey of autonomic computing methods in digital service ecosystems. / Abeywickrama, Dhaminda B. (Corresponding Author); Ovaska, Eila.

    In: Service Oriented Computing and Applications, Vol. 11, No. 1, 2017, p. 1-31.

    Research output: Contribution to journalArticleScientificpeer-review

    TY - JOUR

    T1 - A survey of autonomic computing methods in digital service ecosystems

    AU - Abeywickrama, Dhaminda B.

    AU - Ovaska, Eila

    PY - 2017

    Y1 - 2017

    N2 - Service engineering of digital service ecosystems can be associated with several challenges, such as change and evolution of requirements; gathering of quality requirements and assessment; and uncertainty caused by dynamic nature and unknown deployment environment, composition and users. Therefore, the complexity and dynamics in which these digital services are deployed call for solutions to make them autonomic. Until now there has been no upto-date review of the scientific literature on the application of the autonomic computing initiative in the digital service ecosystems domain. This article presents a review and comparison of autonomic computing methods in digital service ecosystems from the perspective of service engineering, i.e., requirements engineering and architecting of services. The review is based on systematic queries in four leading scientific databases and Google Scholar, and it is organized in four thematic research areas. A comparison framework has been defined which can be used as a guide for comparing the different methods selected. The goal is to discover which methods are suitable for the service engineering of digital service ecosystems with autonomic computing capabilities, highlight what the shortcomings of the methods are, and identify which research activities need to be conducted in order to overcome these shortcomings. The comparison reveals that none of the existing methods entirely fulfills the requirements that are defined in the comparison framework.

    AB - Service engineering of digital service ecosystems can be associated with several challenges, such as change and evolution of requirements; gathering of quality requirements and assessment; and uncertainty caused by dynamic nature and unknown deployment environment, composition and users. Therefore, the complexity and dynamics in which these digital services are deployed call for solutions to make them autonomic. Until now there has been no upto-date review of the scientific literature on the application of the autonomic computing initiative in the digital service ecosystems domain. This article presents a review and comparison of autonomic computing methods in digital service ecosystems from the perspective of service engineering, i.e., requirements engineering and architecting of services. The review is based on systematic queries in four leading scientific databases and Google Scholar, and it is organized in four thematic research areas. A comparison framework has been defined which can be used as a guide for comparing the different methods selected. The goal is to discover which methods are suitable for the service engineering of digital service ecosystems with autonomic computing capabilities, highlight what the shortcomings of the methods are, and identify which research activities need to be conducted in order to overcome these shortcomings. The comparison reveals that none of the existing methods entirely fulfills the requirements that are defined in the comparison framework.

    KW - autonomous systems

    KW - digital ecosystems

    KW - service engineering

    KW - self- features

    KW - quality attributes

    UR - http://www.scopus.com/inward/record.url?scp=84997638332&partnerID=8YFLogxK

    U2 - 10.1007/s11761-016-0203-8

    DO - 10.1007/s11761-016-0203-8

    M3 - Article

    VL - 11

    SP - 1

    EP - 31

    JO - Service Oriented Computing and Applications

    JF - Service Oriented Computing and Applications

    SN - 1863-2386

    IS - 1

    ER -