A Markovian Analysis of IEEE 802.11 Broadcast Transmission Networks with Buffering

TL;DR

This paper models IEEE 802.11 broadcast networks with buffering using Markov chains, analyzing stability and throughput, and proposing two models that align well with protocol principles.

Contribution

It introduces two novel Markovian models for IEEE 802.11 broadcast networks with infinite buffering, extending prior models by considering buffered packet arrivals during back-off.

Findings

Models accurately predict stability conditions

Maximum throughput conditions derived

Buffering improves network performance

Abstract

The purpose of this paper is to analyze the so-called back-off technique of the IEEE 802.11 protocol in broadcast mode with waiting queues. In contrast to existing models, packets arriving when a station (or node) is in back-off state are not discarded, but are stored in a buffer of infinite capacity. As in previous studies, the key point of our analysis hinges on the assumption that the time on the channel is viewed as a random succession of transmission slots (whose duration corresponds to the length of a packet) and mini-slots during which the back-o? of the station is decremented. These events occur independently, with given probabilities. The state of a node is represented by a two-dimensional Markov chain in discrete-time, formed by the back-off counter and the number of packets at the station. Two models are proposed both of which are shown to cope reasonably well with the physical principles of the protocol. The stabillity (ergodicity) conditions are obtained and interpreted in terms of maximum throughput. Several approximations related to these models are also discussed.