A Survey on Delay-Aware Resource Control for Wireless Systems --- Large Deviation Theory, Stochastic Lyapunov Drift and Distributed Stochastic Learning

TL;DR

This survey reviews major systematic approaches for delay-aware resource control in wireless systems, comparing their methodologies, applications, and performance through examples and simulations.

Contribution

It provides a comprehensive overview of the equivalent rate constraint, Lyapunov stability drift, and approximate MDP approaches for delay-aware control in wireless networks, highlighting their advantages and limitations.

Findings

Lyapunov drift approach offers a good balance of performance and complexity.

Stochastic learning methods enable adaptive delay-aware resource control.

Simulation results compare delay performances across different approaches.

Abstract

In this tutorial paper, a comprehensive survey is given on several major systematic approaches in dealing with delay-aware control problems, namely the equivalent rate constraint approach, the Lyapunov stability drift approach and the approximate Markov Decision Process (MDP) approach using stochastic learning. These approaches essentially embrace most of the existing literature regarding delay-aware resource control in wireless systems. They have their relative pros and cons in terms of performance, complexity and implementation issues. For each of the approaches, the problem setup, the general solution and the design methodology are discussed. Applications of these approaches to delay-aware resource allocation are illustrated with examples in single-hop wireless networks. Furthermore, recent results regarding delay-aware multi-hop routing designs in general multi-hop networks are elaborated. Finally, the delay performance of the various approaches are compared through simulations using an example of the uplink OFDMA systems.