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Quasi-light Storage for Optical Data Packets
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Intelligent task scheduling for cutover in optical networks.

Xin Qin, Tongquan An, Xia Gao

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    Summary
    This summary is machine-generated.

    Intelligent scheduling methods for optical network cutover tasks reduce scheduling time from days to seconds. Advanced algorithms significantly decrease conflicts and improve efficiency compared to manual methods.

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    Area of Science:

    • Computer Science
    • Telecommunications Engineering
    • Operations Research

    Background:

    • The expansion of optical networks increases the frequency of network cutover tasks.
    • Manual scheduling of these tasks is time-consuming, often taking several days.
    • This inefficiency leads to suboptimal resource utilization in optical networks.

    Purpose of the Study:

    • To introduce systematic intelligent task scheduling methods for optical network cutover tasks.
    • To address the inefficiencies of manual scheduling and improve resource utilization.
    • To develop methods capable of generating conflict-free schedules autonomously.

    Main Methods:

    • Abstracting cutover task rules and attributes into graphical representations or mathematical expressions.
    • Employing layered topological scheduling using greedy heuristic algorithms, maximal cliques, and particle swarm optimization.
    • Utilizing conflict verification and iterative refinement to ensure conflict-free schedules and update rules.

    Main Results:

    • Achieved second-level scheduling for optical network cutover tasks without conflicts in field trials.
    • Maximal clique and particle swarm optimization methods reduced conflict rates by 20% and 30% respectively, compared to greedy algorithms.
    • Demonstrated enhanced conflict adjustment capabilities (12% and 43%) and improved scheduling efficiency (12% and 9%).

    Conclusions:

    • The proposed intelligent scheduling methods significantly outperform traditional approaches in speed and conflict resolution.
    • These methods enable autonomous generation of multi-period conflict-free schedules for optical networks.
    • Intelligent scheduling is crucial for efficient management of increasingly complex optical networks.