Queueing in the Mist: Buffering and Scheduling with Limited Knowledge

TL;DR

This paper investigates queue management with limited knowledge of packet properties, establishing lower bounds, designing algorithms, and validating their performance through analysis and simulations in complex networking scenarios.

Contribution

It introduces a new framework for managing queues with incomplete information, including lower bounds, algorithm design, and practical implementation strategies.

Findings

Lower bounds on competitive ratios for limited knowledge scenarios

A new algorithmic framework for queue management with unknown packet info

Simulation results validating the effectiveness of the proposed algorithms

Abstract

Scheduling and managing queues with bounded buffers are among the most fundamental problems in computer networking. Traditionally, it is often assumed that all the properties of each packet are known immediately upon arrival. However, as traffic becomes increasingly heterogeneous and complex, such assumptions are in many cases invalid. In particular, in various scenarios information about packet characteristics becomes available only after the packet has undergone some initial processing. In this work, we study the problem of managing queues with limited knowledge. We start by showing lower bounds on the competitive ratio of any algorithm in such settings. Next, we use the insight obtained from these bounds to identify several algorithmic concepts appropriate for the problem, and use these guidelines to design a concrete algorithmic framework. We analyze the performance of our proposed algorithm, and further show how it can be implemented in various settings, which differ by the type and nature of the unknown information. We further validate our results and algorithmic approach by a simulation study that provides further insights as to our algorithmic design principles in face of limited knowledge.