Autonomous Cooperative Routing for Mission-Critical Applications

We are entering an era where three previously decoupled domains of technology are rapidly converging together: robotics and wireless communications. We have seen giant leaps and improvements in computational efficiency of vision processing and sensing circuitry coupled with continuously miniaturized form factors. As a result, a new wave of mission-critical systems has been unleashed in fields like emergency response, public safety, law enforcement, search and rescue, as well as industrial asset mapping. There is growing evidence showing that the efficacy of team-based mission-critical systems is substantially improved when situational awareness data, such as real-time video, is disseminated within the network. Field commanders or operation managers can make great use of live vision feeds to make educated decisions in the face of unfolding circumstances or events. In the likely absence of adequate cellular service, this translates into the need for a mobile ad hoc networking technology (MANET) that supports high throughput but more importantly low end-to-end latency. However, classical MANET technologies fall short in terms of scalability, bandwidth, and latency; all three metrics being quite essential for mission-critical applications. The real bottleneck has always been in how fast packets can be routed through the network. To that end, autonomous cooperative routing (ACR) has gained traction as the most viable MANET routing proposition. Compared to classical MANET routing schemes, ACR is poised to offer up to 2X better throughput, more than 4X reduction in end-to-end latency, while observing a given target of transport rate normalized to energy consumption. Nonetheless, ACR is also associated with a few practical implementation challenges. If these go unaddressed, it will deem ACR practically infeasible. In this chapter, efficient and low-complexity remedies to those issues are presented, analyzed, and validated. The validation is based on field experiments carried out using software-defined radio (SDR) platforms. This chapter sheds light on the underlying networking challenges and practical remedies for ACR to fulfill its promise.