NeTS: Small: Collaborative Research: Protocols and Analysis for Predictable Wireless Sensor Networks

下一代无线传感器网络将监控关键基础设施，收集患者的生命体征，并在紧急响应期间传播医疗和规划信息。与早期的尽力而为服务就足够的无线传感器网络相比，这样的系统需要可预测的性能和高可靠性。如果不能满足这些要求，可能会产生严重的不利影响。该项目旨在开发一种可预测的无线传感器网络的工程方法。可预测的无线传感器网络是这样一种系统，它可以在关于其工作负载和网络属性的合理假设下检查其要求是否得到满足。该项目通过为开发人员提供分析工具来表征和优化传感器网络系统的性能，从而能够开发可预测的无线传感器网络。该项目的智能优点包括：(I)用于评估无线传感器网络的特性和用于在节点故障或时间变化的情况下提供资源以获得稳健性的统计方法；(Ii)确保系统满足其可靠性和实时要求的新型传输调度技术；(Iii)在现实干扰模型下限制网络容量和消息延迟的新的可调度性分析；以及(Iv)实例化所提出的传输调度技术和可调度性分析的无线体系结构。就更广泛的影响而言，该项目将有助于提高我国开发性能关键型无线系统的能力。PI将教授开发的设计和分析技术，作为无线传感器网络课程的一部分，并通过教程与研究社区分享。

The next generation of wireless sensor networks will monitor critical infrastructure, collect vital signs from patients, and disseminate medical and planning information during emergency responses. In contrast to earlier wireless sensor networks for which best-effort services were sufficient, such systems require predictable performance and high reliability. Failure to meet these requirements may have significant adverse effects. This project aims at the development of an engineering methodology for predictable wireless sensor networks. A predictable wireless sensor network is a system for which it is possible to check that its requirements are met under reasonable assumptions regarding its workload and network properties. This project enables the development of predictable wireless sensor networks by providing developers with analytical tools to characterize and optimize the performance of sensor network systems. The intllectual merit of the project includes: (i) Statistical methods for assessing the properties of wireless sensor networks and for provisioning resources to achieve robustness in spite of node failures or temporal variations; (ii) Novel transmission scheduling techniques that ensure a system meets its reliability and real-time requirements; (iii) A new schedulability analysis that bounds network capacity and message latencies under realistic interference models; and (iv) A wireless architecture that instantiates proposed transmission scheduling techniques and the schedulability analysis. In terms of broader impacts, this project will help advance our national capability to develop performance-critical wireless systems. The PIs will teach the developed design and analytical techniques as part of wireless sensor network curriculum and share them with the research community through tutorials.