Delay-Constrained Utility Maximization in Multihop Random Access Networks

TL;DR

This paper addresses delay issues in multi-hop random access networks by formulating and solving delay-constrained utility maximization problems, balancing rate, energy, and delay through distributed algorithms.

Contribution

It introduces a novel delay-constrained utility maximization framework and proposes distributed solutions for optimizing delay, rate, and energy in multi-hop networks.

Findings

Optimal delay, rate, and energy tradeoffs are achieved for various delay constraints.

Distributed algorithms converge efficiently with manageable complexity.

Performance comparisons show effectiveness of proposed solutions.

Abstract

Multi-hop random access networks have received much attention due to their distributed nature which facilitates deploying many new applications over the sensor and computer networks. Recently, utility maximization framework is applied in order to optimize performance of such networks however delay is not limited and proposed algorithms result in very large transmission delays. In this paper, we will analyze delay in random access multi-hop networks and solve the delay-constrained utility maximization problem. We define the network utility as a combination of rate utility and energy cost functions and solve the following two problems: 'optimal medium access control with link delay constraint' and, 'optimal congestion and contention control with end-to-end delay constraint'. The optimal tradeoff between delay, rate, and energy is achieved for different values of delay constraint and the scaling factors between rate and energy. Different distributed solutions will be proposed for each problem and their performance will be compared in terms of convergence and complexity.