To address the issue of inefficient processing of computational task requests in heterogeneous Computing Power Network, a novel optimal pathfinding algorithm based on adap-tive task division is proposed. By modeling computing network resources and computational tasks as a Directed Acyclic Graph (DAG), a latency prediction model is established. This model, with latency as weights, facilitates adaptive task division within the DAG, and employs a reinforcement learning algorithm for optimal pathfinding. This approach matches computing nodes on the optimal path, enabling edge-to-edge computing and collabo-rative transmission, effectively reducing task processing latency. Simulation experiments demonstrate a significant reduction in the average system latency, with a maximum acceleration ratio of 5.8, showcasing improved performance in complex environments.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Task Scheduling Algorithm for Heterogeneous Computing Power Network


    Beteiligte:
    He, Guodong (Autor:in) / Li, Xiaohui (Autor:in) / Lv, Siting (Autor:in) / Zhou, Yuanyuan (Autor:in) / Ni, ZhiGang (Autor:in) / Chen, Xingbo (Autor:in)


    Erscheinungsdatum :

    24.06.2024


    Format / Umfang :

    1702400 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Solution Space Reduction in Task Scheduling for Heterogeneous Computing Systems

    Lam, Yuet M. | British Library Online Contents | 2013


    Research of task scheduling in network parallel computing environment

    Hu, K. / Zhang, Y. / Hu, J.-p. | British Library Online Contents | 2001


    A Task Scheduling Algorithm for Large Graph Processing in Cloud Computing

    Li, J. / Huang, Q. / Liu, Y. et al. | British Library Online Contents | 2012


    Hybrid genetic algorithm for independent tasks scheduling in heterogeneous computing systems

    Yiwen, Z. / Jiangang, Y. | British Library Online Contents | 2004