论文标题
安排或不安排：当无安排可以击败数据中心网络中最著名的流程度安排算法
To schedule or not to schedule: when no-scheduling can beat the best-known flow scheduling algorithm in datacenter networks
论文作者
论文摘要
最小化数据中心网络（DCN）中的平均流量完成时间（AFCT）的常规智慧，即流量大小高度可变，建议安排每个单独的流量。但是，我们表明，考虑调度延迟（包括调度程序的计算和通信延迟），为大多数流提供而无需任何计划，并且仅以先到先得的（FCFS）方式仅以第一个遇到的（FCFS）方式可显着提高其性能，即使将其与剩余的处理时间（SRPT）相比，即使是最剩余的处理时间（SRPT） - 已知为Optimum algorith deles deles deples Zero时，也可以提高其性能。为此，我们只需要根据Flow的尺寸（包括小于阈值，H和二等级别的流量，包括其他）的两类粗糙的流量，包括小于阈值，包括其他流量），然后在服务2级之前始终提供一级流动。为了表明这一点，我们采用SRPT调度算法以及全球流动知识，制定调度延迟对其性能的影响，并证明，对于任何流量尺寸分布和网络负载（<1），与SRPT相比，始终有一个阈值H，保证一级流量可在FCF下获得较低的AFCT。我们计算出的结果和广泛的流级模拟表明，平均而言，超过90％的流量可能是一级，因此不需要任何计划。
Conventional wisdom for minimizing the average flow completion time (AFCT) in the datacenter network (DCN), where flow sizes are highly variable, would suggest scheduling every individual flow. However, we show that considering scheduling delay (including scheduler's computational and communication delays), serving most of the flows without any scheduling and only in first-come-first-served (FCFS) manner significantly improves their performance even when it is compared to the shortest remaining processing time (SRPT)-known as optimum algorithm when scheduling delay is zero. To do so, we only require to have two coarse classes of flows categorized based on flows' sizes (1st-class including flows smaller than a threshold, H, and 2nd-class including others) and serve 1st-class flows always before serving 2nd-class ones. To show that, we take SRPT scheduling algorithm accompanied by the global knowledge of flows, formulate impact of scheduling delay on its performance, and prove that for any flow size distribution and network load (<1), there is always a threshold, H, which guarantees 1st-class flows achieve lower AFCT under FCFS compared to SRPT. Our numerically calculated results and extensive flow-level simulations show that on average, more than 90% of flows could be in 1st-class and consequently do not require any scheduling.
