Modern cloud computing applications have stringent low-latency and high-throughput requirements to meet the increasingly diverse demands from customers. In edge datacenters, the popular load balancing scheme based on packet spraying, i.e., random packet spraying (RPS), makes good use of multiple equal-cost paths to ensure high link utilization and efficient transmission. However, RPS performs poorly under the bursty traffic scenario due to packet loss or even timeout. Therefore, to reduce the tail latency caused by retransmission, we design a coding-based random packet spraying named CRPS. Specifically, the source host transmits forward error correction (FEC) encoded packets and dynamically adjusts the data redundancy based on the packet loss rate. Then the switch randomly sprays the encoded packets across all equal-cost multiple paths to implement parallel transmission. In this way, once enough encoded packets from any parallel paths arrive at the destination host, the original packets can be decoded immediately to address the adverse impact of packet loss. The NS-2 simulation results show that CRPS effectively reduces the probability of timeout and significantly improves the tail flow completion time (FCT) by up to 72% compared with the state-of-the-art multipath transmission schemes.

现代云计算应用对低延迟和高吞吐量提出了严格的要求，以满足客户日益多样化的需求。在边缘数据中心，流行的基于数据包喷射的负载均衡方案，即随机数据包喷射（RPS），很好地利用了多条等价路径，保证了链路的高利用率和高效传输。但是RPS在突发流量场景下会出现丢包甚至超时的情况，性能很差。因此，为了减少重传造成的尾延迟，我们设计了一种基于编码的随机数据包喷射CRPS。具体来说，源主机传输前向纠错（FEC）编码的数据包，并根据数据包丢失率动态调整数据冗余。然后交换机将编码后的数据包随机喷洒在所有等价多条路径上，实现并行传输。这样，一旦来自任何并行路径的足够多的编码数据包到达目的主机，就可以立即对原始数据包进行解码，以解决数据包丢失的不利影响。NS-2 仿真结果表明，与最先进的多径传输方案相比，CRPS 有效降低了超时概率，并将尾流完成时间 (FCT) 显着提高了 72%。