CAREER: Coverage, Capacity, and Connectivity of Wireless Sensor Networks

无线传感器网络在环境监测和战场监视等各种应用中发挥着重要作用。无线传感器网络的基本功能是监控其部署的区域，并将传感器数据传输到特定的指定节点。因此，覆盖、容量和连通性是无线传感器网络运行和性能的三个最基本的属性。深入了解这些特性及其相互关系对于无线传感器网络的网络规划、算法设计和性能具有重要意义。本项目旨在建立强大的理论基础和设计实用协议，以提供无线传感器网络的高性能覆盖、容量和连接。无线传感器网络具有与其他无线网络不同的许多独特特征，包括传感器节点的异构传感、通信和移动能力、有限的基础设施和电源，以及数据主要从传感器流向数据接收器而不是在对等节点之间流动的流量模式。本研究将无线通讯、随机建模、几何及组合优化等概念与技术整合，以建构分析模型及开发实际解决方案。预期结果包括：(i)不同网络场景下覆盖范围、容量和连通性的基本限制；（ii）实现稳健覆盖、连接和数据传输的高效算法；（iii）通过实际实验验证分析结果和评估算法性能的试验台。该项目还包括一个强大的教育组成部分，通过研究学生的积极参与促进教学，培训和学习。

Wireless sensor networks play an important role in a wide variety of applications such as environment monitoring and battlefield surveillance. The basic function of a wireless sensor network is to monitor its deployed region and transport sensor data to certain designated nodes. Therefore, coverage, capacity, and connectivity are three most fundamental properties for the operation and performance of a wireless sensor network. A deep understanding of these properties and their interrelationship is of great importance for the network planning, algorithm design, and performance of wireless sensor networks.This project aims to establish a strong theoretical foundation and design practical protocols to provide high performance coverage, capacity, and connectivity in wireless sensor networks. Wireless sensor networks have many unique characteristics differing from other wireless networks, including heterogeneous sensing, communication, and mobility capabilities of sensor nodes, limited infrastructure and power supply, and traffic pattern where data mainly flow from sensors to data sinks rather than between peer nodes. This research integrates the concepts and techniques in wireless communications, stochastic modeling, geometry, and combinatorial optimizations to construct analytical models and develop practical solutions.The expected outcomes include: (i) fundamental limits of the coverage, capacity, and connectivity under various network scenarios; (ii) efficient algorithms for robust coverage, connectivity, and data transportation; (iii) a test-bed to validate the analytical results and evaluate the performance of algorithms via real experiments. This project also includes a strong educational component that promotes teaching, training, and learning through the active involvement of research students.