Chordal Graph Based Channel Assignment for Multicast and Unicast Traffic in Wireless Mesh Networks

Abstract

With the increasing popularity of multicast and real-time streaming service applications, efficient channel assignment algorithms that handle both multicast and unicast traffic in wireless mesh networks are needed. One of the most effective approaches to enhance the capacity of wireless networks is to use systems with multiple channels and multiple radio interfaces. However, most of the past works focus on vertex coloring of a general contention graph, which is NP-Complete, and use the greedy algorithm to achieve a suboptimal result. In this paper, we combine unicast and multicast with a transmission set, and propose a framework named Chordal Graph Based Channel Assignment (CGCA) that performs channel assignment for multicast and unicast traffic in multi-channel multi-radio wireless mesh networks. The proposed framework based on chordal graph coloring minimizes the interference of the network and prevents unicast traffic from starvation. Simulation results show that our framework provides high throughput and low end-to-end delay for both multicast and unicast traffic. Furthermore, our framework significantly outperforms other well-known schemes that have a similar objective in various scenarios.