基于网络拓扑和偏好排序的多优先级任务多节点分配算法

A multi-priority task multi-node assignment algorithm based on network topology and preference ordering

  • 摘要:
    目的 现有协作任务分配方法较少考虑参与节点的工作模式以及节点间的通信链路能力,导致节点资源利用率和任务调度成功率较低,为此,提出一种基于网络拓扑和偏好排序的多优先级任务多节点分配算法。
    方法 首先,将多任务多节点分配问题建模为一个优化问题,目标是最大化任务执行收益并最大化任务参与节点数量。然后,提出启发式方法求解该优化问题。该方法为每个任务分配最少节点数,以确保能够成功分配尽可能多的任务,并通过扩充任务的节点集合,进一步满足任务参与节点最多的目标。
    结果 仿真结果表明,在带宽资源丰富的场景下,仅需6节点即可使任务分配成功率达到80%。
    结论 研究表明,所提算法能够在节点工作模式和节点间链路能力等约束条件下,有效获得多优先级任务多节点分配的局部最优解。

     

    Abstract:
    Objective Existing collaborative task assignment methodologies inadequately account for the work mode of participating nodes and the communication capabilities of inter-node links, resulting in diminished node resource utilization and lower task scheduling success rate. To address these issues, a multi-priority task multi-node assignment algorithm based on network topology and preference ordering is proposed.
    Methods This algorithm models the problem of assigning multiple tasks to multiple nodes as an optimization problem aimed at maximizing task execution benefits and maximizing the participating nodes number. A heuristic method is then proposed to solve this optimization problem. Initially, the heuristic method assigns the minimum number of nodes to each task to maximize the number of successfully assigned tasks. Subsequently, it expands the node set for each task to maximize the number of participating nodes.
    Results The simulation results show that a task assignment success rate of 80% can be achieved with just six nodes in scenarios with abundant bandwidth resources.
    Conclusion This indicates that the proposed multi-priority task multi-node assignment algorithm has obtained a locally optimal solution under constraints such as node work mode and inter-node link capacities.

     

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