Opportunities for Network Coding: To Wait or Not to Wait

TL;DR

This paper investigates the decision-making process in wireless network coding, balancing transmission delays and coding opportunities, and demonstrates that queue length-based policies are optimal in stochastic environments.

Contribution

It formulates a stochastic dynamic programming model for optimal transmission and delay decisions, proving the optimality of queue length-based threshold policies.

Findings

Queue length observations suffice for optimal control.

Stationary threshold policies based on queue lengths are optimal.

Simulation confirms effectiveness in generalized settings.

Abstract

It has been well established that wireless network coding can significantly improve the efficiency of multi-hop wireless networks. However, in a stochastic environment some of the packets might not have coding pairs, which limits the number of available coding opportunities. In this context, an important decision is whether to delay packet transmission in hope that a coding pair will be available in the future or transmit a packet without coding. The paper addresses this problem by formulating a stochastic dynamic program whose objective is to minimize the long-run average cost per unit time incurred due to transmissions and delays. In particular, we identify optimal control actions that would balance between costs of transmission against the costs incurred due to the delays. Moreover, we seek to address a crucial question: what should be observed as the state of the system? We analytically show that observing queue lengths suffices if the system can be modeled as a Markov decision process. We also show that a stationary threshold type policy based on queue lengths is optimal. We further substantiate our results with simulation experiments for more generalized settings.