This letter studies a delay-optimal multi-destination computation offloading system, where the subtasks are transmitted to multiple Edge Computing Servers (ECSs) sequentially due to the limited communication resource, and different subtasks are computed in parallel at different ECSs. Consider the communication and computation capabilities, we jointly optimize the task assignment and the offloading scheduling for minimizing the total delay, which is the maximum completion time among all ECSs with their corresponding subtasks. We first consider a simplified case with equal task assignment, and then obtain the optimal offloading order according to the Lowest-Computation-First (LCF) rule. Under flexible task assignment, we derive the optimal offloading scheduling policy according to the Highest-Communication-First (HCF) offloading order with closed-form task assignment. Simulation results demonstrate the jointly optimized offloading scheduling policy reduces the delay by up to 62.4% compared with the non-scheduling offloading method.

中文翻译：

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多目的地计算卸载的延迟最优闭式调度

这封信研究了一个延迟最优的多目的地计算卸载系统，其中子任务由于通信资源有限而被顺序传输到多个边缘计算服务器（ECS），不同的子任务在不同的 ECS 上并行计算。考虑通信和计算能力，我们联合优化任务分配和卸载调度，以最小化总延迟，即所有 ECS 及其相应子任务之间的最大完成时间。我们首先考虑具有相等任务分配的简化情况，然后根据最低计算优先（LCF）规则获得最佳卸载顺序。在灵活的任务分配下，我们根据具有封闭形式任务分配的最高通信优先（HCF）卸载顺序推导出最优卸载调度策略。仿真结果表明联合优化的卸载调度策略与非调度卸载方法相比减少了62.4%的延迟。