Contention resolution on a restrained channel

TL;DR

This paper investigates how strict power limitations affect the stability and efficiency of deterministic broadcasting protocols on multiple-access channels, demonstrating that adaptive protocols can maintain stability with minimal energy, unlike fixed-pattern acknowledgment protocols.

Contribution

It introduces energy-efficient deterministic algorithms for stable broadcasting under power constraints, highlighting the impact of protocol adaptiveness on system stability and throughput.

Findings

Adaptive and full-sensing protocols achieve stability with minimal power.

Fixed-pattern acknowledgment protocols require reduced injection rates for stability.

Simulations show the effectiveness of proposed algorithms compared to backoff methods.

Abstract

We examine deterministic broadcasting on multiple-access channels for a scenario when packets are injected continuously by an adversary to the buffers of the devices at rate $\rho$ packages per round. The aim is to maintain system stability, that is, bounded queues. In contrast to previous work we assume that there is a strict limit of available power, defined as the total number of stations allowed to transmit or listen to the channel at a given time, that can never be exceeded. We study how this constraint influences the quality of services with particular focus on stability. We show that in the regime of deterministic algorithms, the significance of energy restriction depends strongly on communication capabilities of broadcasting protocols. For the adaptive and full-sensing protocols, wherein stations may substantially adopt their behavior to the injection pattern, one can construct efficient algorithms using very small amounts of power without sacrificing throughput or stability of the system. In particular, we construct constant-energy adaptive and full sensing protocols stable for $\rho=1$ and any $\rho<1$, respectively, even for worst case (adversarial) injection patterns. Surprisingly, for the case of acknowledgment based algorithms that cannot adopt to the situation on the channel (i.e., their transmitting pattern is fixed in advance), limiting power leads to reducing the throughput. That is, for this class of protocols in order to preserve stability we need to reduce injection rate significantly. We support our theoretical analysis by simulation results of algorithms constructed in the paper. We depict how they work for systems of moderate, realistic sizes. We also provide a comprehensive simulation to compare our algorithms with backoff algorithms, which are common in real-world implementations, in terms of queue sizes and energy consumption.