Sliding-Window QPS (SW-QPS): A Perfect Parallel Iterative Switching Algorithm for Input-Queued Switches

TL;DR

This paper introduces SW-QPS, a parallel switching algorithm for input-queued switches that reduces batching delay to zero, improves throughput, and maintains low complexity, outperforming existing algorithms.

Contribution

It proposes SW-QPS, a novel sliding-window switching framework that enhances batch switching algorithms with zero delay and higher matching quality.

Findings

SW-QPS achieves zero batching delay.

SW-QPS outperforms QPS-1 in throughput and delay.

SB-QPS reduces batch size without throughput loss.

Abstract

In this work, we first propose a parallel batch switching algorithm called Small-Batch Queue-Proportional Sampling (SB-QPS). Compared to other batch switching algorithms, SB-QPS significantly reduces the batch size without sacrificing the throughput performance and hence has much lower delay when traffic load is light to moderate. It also achieves the lowest possible time complexity of $O(1)$ per matching computation per port, via parallelization. We then propose another algorithm called Sliding-Window QPS (SW-QPS). SW-QPS retains and enhances all benefits of SB-QPS, and reduces the batching delay to zero via a novel switching framework called sliding-window switching. In addition, SW-QPS computes matchings of much higher qualities, as measured by the resulting throughput and delay performances, than QPS-1, the state-of-the-art regular switching algorithm that builds upon the same underlying bipartite matching algorithm.