Multi-Node Collaborative Resource Allocation Method for Concurrent Tasks

Mingjun Zhu, Yuanling Huang, Xiaoting Ji, Yanpeng Luo, Haibing Cheng, Tongxin Zhang
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Abstract

Current unmanned aerial vehicle (UAV) and their mission system have been gradually developed in the direction of swarming together. However, the existing swarm coordination method usually realizes the parallel execution of multiple tasks through the assignment missions for various nodes, so the number of concurrent missions supported by the system is minimal, which is challenging to meet the requirements of electromagnetic monitoring tasks in the natural electromagnetic environment. Therefore, this paper introduces the idea of time-division multiplexing and proposes a time resource allocation algorithm for concurrent tasks oriented to multi-node synchronous cooperation. Based on the fixed-priority scheduling strategy, the algorithm can reasonably schedule sensor resources of each UAV node according to priority constraints, which improves the concurrent task processing capability of the UAV swarm. Through the fast schedulability test based on blocking interval, the task's parameters can be adjusted quickly to ensure the mission's correct execution and improve the UAV swarm's dynamic adaptability. Finally, simulation verifies the proposed algorithm's effectiveness and feasibility.
并行任务的多节点协同资源分配方法
当前的无人机及其任务系统正逐步向蜂群协同方向发展。然而,现有的群体协调方法通常通过对各个节点的分配任务来实现多个任务的并行执行,因此系统支持的并发任务数量很少,难以满足自然电磁环境下电磁监测任务的要求。为此,本文引入了时分复用的思想,提出了一种面向多节点同步协作的并发任务时间资源分配算法。该算法基于固定优先级调度策略,根据优先级约束合理调度各无人机节点的传感器资源,提高了无人机群的并发任务处理能力。通过基于阻塞间隔的快速可调度性测试,可以快速调整任务参数,保证任务的正确执行,提高无人机群的动态适应性。最后通过仿真验证了算法的有效性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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