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.
