e-space
Manchester Metropolitan University's Research Repository

    A genetic algorithm enhanced automatic data flow management solution for facilitating data intensive applications in the cloud

    Li, SL, Huang, Z, Han, L ORCID logoORCID: https://orcid.org/0000-0003-2491-7473 and Jiang, C (2018) A genetic algorithm enhanced automatic data flow management solution for facilitating data intensive applications in the cloud. Concurrency and Computation: Practice and Experience, 30 (23). e4844. ISSN 1532-0626

    [img]
    Preview
    Accepted Version
    Available under License In Copyright.

    Download (1MB) | Preview

    Abstract

    The past few years have witnessed a rapid deployment of computing infrastructures in the cloud in support of data intensive applications. The effort of the existing works is mainly focused on data reusing mechanisms without considering data processing routes, which can significantly affect the computation costs when exchanging data among the computing node in the cloud. This paper presents a genetic algorithm enhanced Automatic Data Flow Management Solution (ADFMS) that facilitates automatic routing function and a self‐adjustable intermediate data management mechanism to achieve an efficient data processing structure of cloud computing. Experimental results show that ADFMS optimizes costs in managing intermediate data in the cloud.

    Impact and Reach

    Statistics

    Activity Overview
    6 month trend
    522Downloads
    6 month trend
    374Hits

    Additional statistics for this dataset are available via IRStats2.

    Altmetric

    Repository staff only

    Edit record Edit record