NeTS: Small: Collaborative Research: Advanced Algorithmic Tools for Discovery in Cognitive Radio Networks

嵌入式计算和无线技术的普及为技术提供和改进安全和服务带来了显著的新机遇。这些应用包括提高安全性和减少拥堵的即时交通管理，为灾难恢复建立特别网络，以及为军事或科学目的维护传感器网络。在所有这些情况下，无线设备必须发现彼此的存在，配置其无线无线电以最大限度地提高效率，并节省电池电量。这个项目将开发新的方法来解决这些发现和效率的根本问题。此外，该项目还将开发新的技术和工具，以评估拟议解决方案的效力。该项目还包括开发本科和研究生水平的课程，通过高中教师和学生的教育机会进行推广，扩大本科生和未被充分代表的群体参与研究，以及支持女性学生参与计算。该项目旨在开发和分析用于时空对等发现的高级算法工具，这是自组织网络的基本原语。该提案侧重于认知无线电网络，其特点是移动性高、频谱拥塞、运动导致的信道中断和能源受限的商用设备。开发既有可证明的保证又有强大的实际性能的有效的发现方案，对于建立这类网络以用于道路安全和无人驾驶车队的紧急反应等大规模应用至关重要。该项目有四个主要推动力：(1)多信道发现，其中节点配备频谱灵活的无线电信道跳跃以实现交会，使用确定性和概率技术来实现多信道发现，灵感来自于构造性Ramsey理论、循环代数几何代码、数论筛子和一种新颖的伪随机结构：同步采样器；(2)能量受限的单信道发现算法，其中移动节点通过连接加性组合、代数几何和扩展图来节省电池占空比；(3)通过应用计算和凸几何的技术来估计车辆环境中的轨迹，通过信号强度进行空间发现；以及(4)使用具有多通道车辆网络的适当扩展的NS-3仿真器通过仿真环境进行验证。在专注于车载网络的同时，这些技术可以应用于各种不同的网络，例如医疗和遥测网络。

The prevalence of embedded computing and wireless technology has given rise to remarkable new opportunities for technology to provide and improve safety and services. Such applications include on-the-fly traffic management to improve safety and reduce congestion, establishing ad-hoc networks for disaster recovery, and maintaining sensor networks for military or scientific purposes. In all these cases, wireless devices must discover each other's existence, configure their wireless radios to maximize efficiency, and conserve battery power. This project will develop new methods to address these fundamental problems of discovery and efficiency. Additionally, the project will develop and new techniques and tools for evaluating the efficacy of proposed solutions. The project also incorporates development of undergraduate- and graduate-level courses, outreach via educational opportunities for high-school teachers and students, expanding participation of undergraduates and underrepresented groups in research, and support for female students in computing.This project aims to develop and analyze advanced algorithmic tools for spatio-temporal peer discovery, a fundamental primitive for ad-hoc networks. The proposal focuses on cognitive radio networks characterized by high mobility, congested spectrum, motion-induced channel outages and energy-constrained commodity devices. The development of efficient discovery schemes with both provable guarantees and strong practical performance will be critical for the build out of such networks for large scale applications such as road safety and emergency response for driver-less fleets. The project has four principal thrusts: (1) Multi-channel discovery, where nodes equipped with spectrally agile radios channel hop to achieve rendezvous using deterministic and probabilistic techniques for achieving multi-channel discovery, drawing inspiration from constructive Ramsey theory, cyclic algebraic geometry codes, number theoretic sieves, and a novel pseudo-random construction: the synchronizing sampler; (2) Energy-constrained single channel discovery algorithms where mobile nodes duty cycle to save battery, via connections with additive combinatorics, algebraic geometry, and expander graphs; (3) Spatial discovery through signal strength by applying techniques from computational and convex geometry for estimations of trajectories within vehicular environments; and (4) Validation via a simulation environment using the ns-3 simulator with appropriate extensions for multi-channel vehicular networks. While focusing on vehicular networks, these techniques can be applied in a wide variety of different networks, such as medical and telemetry networks as well.