NeTS-NOSS: Algorithms and System Support for Data Integrity in Wireless Sensor Networks

无线传感器网络具有对物理现象进行现场和密集时空采样的能力，已迅速成为基础科学领域一类有价值的新型仪器。然而，像任何仪器一样，传感器网络也会受到损害，这会对关于物理现象的感测信息的完整性产生不利影响。传感器网络中完整性降低的原因有很多，包括系统的感测、处理和通信元件中的各种内部和外部不确定性。例子包括校准误差，故障，传感通道退化和障碍物，生物污垢等，该项目是全面解决的完整性问题，通过研究其原因，了解基本限制，开发算法和系统支持，并在现实生活中验证的方法。整体方法的两个关键要素是完整性损害的自主检测，以及弹性估计和聚合。这两个基础是新的统计和信号处理技术，利用学习模型的物理现象，测量过程，并导致损坏或丢失的数据的故障。此外，该项目正在研究指导补救完整性问题原因的方法，以及传感器网络的完整性驱动部署，以实现所需的弹性。该研究将导致在传感器网络的完整性故障的透彻理解，并导致在设计工具和运行时软件的工具包，以确保高完整性的操作。这些将通过陆地、地下和水生生态观测应用程序加以验证，并通过项目网站http://nesl.ee.ucla.edu/projects/integrity传播，以供更广泛使用。

Wireless sensor networks with their ability of in situ and dense spatiotemporal sampling of physical phenomena have rapidly emerged as a valuable new class of instrument for the basic sciences. Like any instrument, however, sensor networks suffer from impairments that adversely impact the integrity of the sensed information about the physical phenomena. The causes of reduced integrity in sensor networks are many, and include various internal and external uncertainties in the sensing, processing, and communication elements of the system. Examples include calibration errors, faults, sensing channel degradation and obstructions, bio-fouling etc. This project is comprehensively addressing the integrity problem by studying its causes, understanding fundamental limits, developing algorithms and system support, and validating the approach in real-life. The two key elements of the overall approach are autonomous detection of integrity compromise, and resilient estimation and aggregation. Underlying these two are novel statistical and signal-processing techniques that exploit learned models of the physical phenomenon, the measurement process, and the faults which result in corrupted or missed data. In addition, the project is investigating approaches for guiding remediation of the causes of integrity problems, and for integrity-driven deployment of sensor network to achieve desired resilience. The research would result in a thorough understanding of integrity failure in sensor networks, and result in a toolkit of design tools and run-time software for ensuring high-integrity operation. These would be validated via terrestrial, under-soil, and aquatic ecological observation application, and also disseminated for broader use via the project web site at http://nesl.ee.ucla.edu/projects/integrity.