Analyzing DISH for Multi-Channel MAC Protocols in Wireless Networks

TL;DR

This paper introduces a theoretical framework to evaluate the probability of cooperation in multi-channel wireless networks, linking it to network performance metrics and validating through analysis and simulations.

Contribution

It provides the first analytical evaluation of cooperation probability ($p_{co}$) in multi-channel networks and explores its relationship with network performance.

Findings

$p_{co}$ can be accurately predicted by analysis.

A near-linear relationship exists between $p_{co}$ and network performance.

Different DISH contexts influence cooperation probability and network behavior.

Abstract

For long, node cooperation has been exploited as a data relaying mechanism. However, the wireless channel allows for much richer interaction between nodes. One such scenario is in a multi-channel environment, where transmitter-receiver pairs may make incorrect decisions (e.g., in selecting channels) but idle neighbors could help by sharing information to prevent undesirable consequences (e.g., data collisions). This represents a Distributed Information SHaring (DISH) mechanism for cooperation and suggests new ways of designing cooperative protocols. However, what is lacking is a theoretical understanding of this new notion of cooperation. In this paper, we view cooperation as a network resource and evaluate the availability of cooperation via a metric, $p_{co}$, the probability of obtaining cooperation. First, we analytically evaluate $p_{co}$ in the context of multi-channel multi-hop wireless networks. Second, we verify our analysis via simulations and the results show that our analysis accurately characterizes the behavior of $p_{co}$ as a function of underlying network parameters. This step also yields important insights into DISH with respect to network dynamics. Third, we investigate the correlation between $p_{co}$ and network performance in terms of collision rate, packet delay, and throughput. The results indicate a near-linear relationship, which may significantly simplify performance analysis for cooperative networks and suggests that $p_{co}$ be used as an appropriate performance indicator itself. Throughout this work, we utilize, as appropriate, three different DISH contexts --- model-based DISH, ideal DISH, and real DISH --- to explore $p_{co}$.