Fair bandwidth sharing algorithms based on game theory frameworks for wireless ad-hoc networks

TLDR

The study investigates bandwidth sharing in wireless ad‑hoc networks using a game‑theoretic framework to design efficient, self‑organized MAC protocols for both topology‑blind and partially informed environments. By modeling link contention with a conflict graph and formulating fair bandwidth allocation as a utility‑based constrained maximization, the authors derive non‑cooperative and cooperative game solutions via Lagrange relaxation and duality, yielding algorithms that operate without global information and addressing implementation concerns. Simulations demonstrate that the proposed algorithms effectively achieve fair bandwidth allocation in MANETs.

Abstract

This paper examines the theoretical aspects of bandwidth sharing in wireless, possibly mobile, ad-hoc networks (MANETs) through a game theoretic framework. It presents some applications to show how such a framework can be invoked to design efficient media access control protocols in a noncooperative, self-organized, topology-blind environment as well as in environments where the competing nodes share some basic information to guide their choice of channel access policies. For this purpose, contentions between concurrent links in a MANET are represented by a conflict graph, and each maximal clique in the graph defines a contention context which in turn imposes a constraint on the share of bandwidth that the links in the clique can obtain. Using this approach the fair bandwidth allocation problem is modeled as a general utility based constrained maximization problem, called the system problem, which is shown to admit a unique solution that can only be obtained when global coordination between all links is possible. By using Lagrange relaxation and duality theory, both a non-cooperative and a cooperative game formulation of the problem are derived. The corresponding mathematical algorithms to solve the two games are also provided where there is no need for global information. Implementation issues of the algorithms are also considered. Finally, simulation results are presented to illustrate the effectiveness of the algorithms.