On Wireless Link Connectivity for Resilient Multi-Hop Networks

Abstract

Wireless multi-hop networks are rapidly becoming an integral part of next generation mobile communications. These networks are highly scalable, self-organizing, dynamic, and may share spectrum with others while operating in resource-constrained environments. As a result, these networks are highly susceptible to link failure. In particular, wireless multi-hop sensor networks are required to maintain a high level of resiliency in order to deliver sensor data with minimum latency. One way to achieve such resiliency is by maximizing the probability of maintaining a high level of topological connectivity. In this paper, we develop a graph-theoretic model that maintains a high level of connectivity in the presence of internal and external interference. Given a pool of available channels, we utilize spectrum sensing to determine the state of each channel, achieve channel state consensus across the network using distributed average consensus approach and use graph coloring for channel allocation in order to minimize interference experienced from adjacent nodes as well as external interference sources. These models, corroborated by simulation, are then utilized to quantify the improvement in network resiliency as measured by link connectivity.