Wireless mesh networking (WMN) for video surveillance provides a strong potential for rapid deployment in a large community, for which reliability and survivability for real-time streaming are the key performance measure. However, current routing protocols do not provide a robust solution to meet video transmission requirements such as providing load balancing for the high data rate and delay requirements. We propose an application of field-based anycast routing (FAR) protocol, which utilizes rapid routing dynamics inspired by an electrostatic potential field model governed by Poisson's equation. This routing metric takes into account geometric proximity and congestion degree in order to increase delivery ratio and decrease end-to-end delay, which determine the quality of the delivered video. In addition, FAR protects node failure with an on-the-fly rerouting process that guarantees the continuity of video streaming. Simulation results show 100% delivery ratio in congestion situations and it shows tolerance to different delay requirements compared with AODV and FDMR protocols in terms of delivering real-time and non real-time video surveillance which verifies FAR as a strong candidate for video transmission over WMN.

A wireless mesh network (WMN) is expected to be a key enabler for next generation networking due to its infrastructure-less strengths such as scalability, costefficient rapid deployment, and long distance communications. To boost the strength of WMNs, it is required to balance loads among multiple gateways as well as mesh nodes. However, there have been only few practical and easily-implementable solutions for load balancing of WMNs. In this paper, we propose a distributed autonomous load balancing routing mechanism for anycast WMNs where most traffic flows are for the Internet access through any mesh gateways. Without flooding of control messages, our protocol finds optimized paths implicitly considering geographical distance and a congestion degree based on analogy of physics theory, Poisson's equation and by use of a distributed form of a finite element method. Through simulations, we assess the performance of our protocol compared with the anycast modifications of traditional shortest-path routing and geographic routing under dynamically varying network scenarios.