Routing in wireless meshes must detour around holes. Extant routing protocols often underperform in minimally connected networks where holes are larger and more frequent. Minimal density networks are common in practice due to deployment cost constraints, mobility dynamics, and/or adversarial jamming. Protocols that use global search to determine optimal paths incur search overhead that limits scaling. Conversely, protocols that use local search tend to find approximately optimal paths at higher densities due to the existence of geometrically direct routes but underperform as the connectivity lowers and regional (or global) information is required to address holes. Designing a routing protocol to achieve high throughput-latency performance across network densities, mobility, and interference dynamics remains challenging. This paper shows that, in a probabilistic setting, bounded exploration can be leveraged to mitigate this challenge. We show, first, that the length of shortest paths in networks with uniform random node distribution can, with high probability (whp), be bounded. Thus, whp a shortest path may be found by limiting exploration to an elliptic region whose size is a function of the network density and the Euclidean distance between the two endpoints. Second, we propose a geographic routing protocol that achieves high reliability and throughput-latency performance by forwarding packets within an ellipse whose size is bounded similarly and by an estimate of the available capacity. Our protocol, QF-Geo, selects forwarding relays within the elliptic region, prioritizing those with sufficient capacity to avoid bottlenecks. Our simulation results show that QF-Geo achieves high goodput efficiency and reliability in both static and mobile networks across both low and high densities, at large scales, with a wide range of concurrent flows, and in the presence of adversarial jamming.

翻译：无线网格中的路由必须绕过空洞。现有路由协议在最小连通网络中常表现不佳，此类网络中空洞规模更大且出现更频繁。由于部署成本约束、移动性动态变化和/或对抗性干扰，最小密度网络在实践中普遍存在。采用全局搜索确定最优路径的协议会产生限制扩展性的搜索开销。相反，采用局部搜索的协议在较高密度下因存在几何直接路径而倾向于找到近似最优路径，但随着连通性降低和需要区域（或全局）信息处理空洞时表现下降。设计一个能在网络密度、移动性和干扰动态变化中实现高吞吐量-延迟性能的路由协议仍是挑战。本文表明，在概率框架下，有界探索可用于缓解这一挑战。我们首先证明，在均匀随机节点分布的网络中，最短路径长度能以高概率有界。因此，通过将探索限制在椭圆区域（其尺寸是网络密度和两端点欧氏距离的函数），能以高概率找到最短路径。其次，我们提出一种地理路由协议，通过将数据包转发到尺寸类似有界且基于可用容量估计的椭圆区域内，实现高可靠性与吞吐量-延迟性能。我们的协议QF-Geo在椭圆区域内选择转发中继，优先考虑具有足够容量以避免瓶颈的中继。仿真结果表明，QF-Geo在静态和移动网络、低密度和高密度、大规模场景、多种并发流以及存在对抗性干扰的条件下，均能实现高有效吞吐量效率和可靠性。