Context-Aware Optimal Assignment of a Chain-like Processing Task onto Chain-like Resources in M-Health

H. Mei, I.A. Widya

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

    Abstract

    This paper focuses on the optimal assignment of a chain-structured medical task onto a chain of networked devices, a need identified in context-aware mobile healthcare applications. We propose a graph-based method to compute the assignment which has the minimal end-to-end process and transfer delay. In essence, the method transforms the assignment problem to a shortest path problem in a graph representing all possible assignments. Compared to earlier work, our method relaxes a so-called contiguity constraint, which is a necessity in the earlier case but unnecessarily constraining in the healthcare applications. The proposed method reduces the time and space complexity in case it is adapted to include the contiguity constraint.
    Original languageUndefined
    Title of host publicationInternational Conference on Computational Science (3)
    PublisherSpringer
    Pages424-431
    Number of pages8
    ISBN (Print)978-3-540-72587-9
    DOIs
    Publication statusPublished - 14 Jul 2007
    Event10th International Conference on Computational Science, ICCS 2010 - University of Amsterdam, Amsterdam, Netherlands
    Duration: 31 May 20102 Jun 2010
    Conference number: 10
    https://www.iccs-meeting.org/iccs2010/

    Publication series

    Name
    PublisherSpringer Verlag
    Number67310A

    Conference

    Conference10th International Conference on Computational Science, ICCS 2010
    Abbreviated titleICCS 2010
    CountryNetherlands
    CityAmsterdam
    Period31/05/102/06/10
    Internet address

    Keywords

    • EWI-11642
    • METIS-245895
    • Graph-based - task assignment - contiguity constraint - M-health
    • IR-62083

    Cite this

    Mei, H., & Widya, I. A. (2007). Context-Aware Optimal Assignment of a Chain-like Processing Task onto Chain-like Resources in M-Health. In International Conference on Computational Science (3) (pp. 424-431). [10.1007/978-3-540-72588-6_69] Springer. https://doi.org/10.1007/978-3-540-72588-6_69