On throughput capacity for a class of buffer-limited MANETs

TL;DR

This paper introduces a novel analytical framework to precisely determine the throughput capacity of buffer-limited MANETs with two-hop relays, addressing the gap left by previous studies that focused mainly on scaling laws and infinite buffer assumptions.

Contribution

The paper develops a comprehensive theoretical framework using Markov and Queuing Theory to derive exact throughput capacity considering buffer limitations in MANETs with two-hop relays.

Findings

Throughput capacity is primarily influenced by relay-buffer blocking probability.

The framework accurately predicts capacity under different scheduling schemes.

Buffer constraints significantly impact network throughput and scalability.

Abstract

Available throughput performance studies for mobile ad hoc networks (MANETs) suffer from two major limitations: they mainly focus on the scaling law study of throughput, while the exact throughput of such networks remains largely unknown; they usually consider the infinite buffer scenarios, which are not applicable to the practical networks with limited buffer. As a step to address these limitations, this paper develops a general framework for the exact throughput capacity study of a class of buffer-limited MANETs with the two-hop relay. We first provide analysis to reveal how the throughput capacity of such a MANET is determined by its relay-buffer blocking probability (RBP). Based on the Embedded Markov Chain Theory and Queuing Theory, a novel theoretical framework is then developed to enable the RBP and closed-form expression for exact throughput capacity to be derived. We further conduct case studies under two typical transmission scheduling schemes to illustrate the applicability of our framework and to explore the corresponding capacity optimization as well as capacity scaling law. Finally, extensive simulation and numerical results are provided to validate the efficiency of our framework and to show the impacts brought by the buffer constraint.