Energy and Utility Optimization in Wireless Networks with Random Access

TL;DR

This paper explores the tradeoff between energy consumption and data transmission utility in wireless ad-hoc networks, proposing a bi-criterion optimization framework for random access MAC that balances these competing objectives.

Contribution

It introduces a novel bi-criterion optimization model for energy and utility in wireless networks, with a layered decomposition approach for practical implementation.

Findings

Optimal tradeoff between energy and utility identified.

Decomposition method enables distributed optimization.

Enhanced MAC performance with balanced energy and throughput.

Abstract

Energy consumption is a main issue of concern in wireless networks. Energy minimization increases the time that networks' nodes work properly without recharging or substituting batteries. Another criterion for network performance is data transmission rate which is usually quantified by a network utility function. There exists an inherent tradeoff between these criteria and enhancing one of them can deteriorate the other one. In this paper, we consider both Network Utility Maximization (NUM) and energy minimization in a bi-criterion optimization problem. The problem is formulated for Random Access (RA) Medium Access Control (MAC) for ad-hoc networks. First, we optimize performance of the MAC and define utility as a monotonically increasing function of link throughputs. We investigate the optimal tradeoff between energy and utility in this part. In the second part, we define utility as a function of end to end rates and optimize MAC and transport layers simultaneously. We calculate optimal persistence probabilities and end-to-end rates. Finally, by means of duality theorem, we decompose the problem into smaller subproblems, which are solved at node and network layers separately. This decomposition avoids need for a central unit while sustaining benefits of layering.