Node Weighted Scheduling

TL;DR

This paper introduces a new class of online scheduling policies for input-buffered switches that are throughput optimal and can drain packets efficiently, offering lower complexity and improved delay performance over existing methods.

Contribution

It proposes a novel class of scheduling policies focusing on congested ports, achieving throughput optimality without requiring maximality at each step, and introduces an efficient algorithm with better delay.

Findings

Policies are throughput optimal for a broad class of arrival processes.

The proposed algorithms have lower complexity than traditional edge-based methods.

Simulations show improved delay performance over existing algorithms.

Abstract

This paper proposes a new class of online policies for scheduling in input-buffered crossbar switches. Our policies are throughput optimal for a large class of arrival processes which satisfy strong-law of large numbers. Given an initial configuration and no further arrivals, our policies drain all packets in the system in the minimal amount of time (providing an online alternative to the batch approach based on Birkhoff-VonNeumann decompositions). We show that it is possible for policies in our class to be throughput optimal even if they are not constrained to be maximal in every time slot. Most algorithms for switch scheduling take an edge based approach; in contrast, we focus on scheduling (a large enough set of) the most congested ports. This alternate approach allows for lower-complexity algorithms, and also requires a non-standard technique to prove throughput-optimality. One algorithm in our class, Maximum Vertex-weighted Matching (MVM) has worst-case complexity similar to Max-size Matching, and in simulations shows slightly better delay performance than Max-(edge)weighted-Matching (MWM).