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In this work, we first propose a parallel batch switching algorithm calledSmall-Batch Queue-Proportional Sampling (SB-QPS). Compared to other batchswitching algorithms, SB-QPS significantly reduces the batch size withoutsacrificing the throughput performance and hence has much lower delay whentraffic load is light to moderate. It also achieves the lowest possible timecomplexity of $O(1)$ per matching computation per port, via parallelization. Wethen propose another algorithm called Sliding-Window QPS (SW-QPS). SW-QPSretains and enhances all benefits of SB-QPS, and reduces the batching delay tozero via a novel switching framework called sliding-window switching. Inaddition, SW-QPS computes matchings of much higher qualities, as measured bythe resulting throughput and delay performances, than QPS-1, thestate-of-the-art regular switching algorithm that builds upon the sameunderlying bipartite matching algorithm.

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