论文标题
通过时间约束，在云机器人系统的动态任务计划中改进MakePan
Improving Makespan in Dynamic Task Scheduling for Cloud Robotic Systems with Time Window Constraints
论文作者
论文摘要
机器人网络云系统中的调度方法最少是有益的，因为该系统可以以最快的方式完成分配给它的所有任务。机器人网络云系统可以翻译成图形，其中节点代表具有独立计算能力的硬件，边缘代表节点之间的数据传输。任务上的时间窗口约束是订购任务的自然方法。 MakePAN是第一个接收任务的节点开始执行其第一个计划任务的最大时间，以及所有节点都完成了最后一个计划的任务。负载平衡分配和调度确保确保第一个节点完成其计划任务与所有其他节点完成其计划任务之间的时间尽可能短。我们提出了所有任务的网格，以确保满足任务的时间窗口约束。我们提出了平衡算法的所有任务的网格，用于分发和调度任务以最低的速度分配和调度任务。从理论上讲，我们证明了所提出的算法的正确性，并在说明了所获得的结果的情况下进行了模拟。
A scheduling method in a robotic network cloud system with minimal makespan is beneficial as the system can complete all the tasks assigned to it in the fastest way. Robotic network cloud systems can be translated into graphs where nodes represent hardware with independent computing power and edges represent data transmissions between nodes. Time window constraints on tasks are a natural way to order tasks. The makespan is the maximum amount of time between when the first node to receive a task starts executing its first scheduled task and when all nodes have completed their last scheduled task. Load balancing allocation and scheduling ensures that the time between when the first node completes its scheduled tasks and when all other nodes complete their scheduled tasks is as short as possible. We propose a grid of all tasks to ensure that the time window constraints for tasks are met. We propose grid of all tasks balancing algorithm for distributing and scheduling tasks with minimum makespan. We theoretically prove the correctness of the proposed algorithm and present simulations illustrating the obtained results.
