From the viewpoint of researchers, developers, and even consumers, reliability analysis is recognized as an indispensable step before sensor network systems can be widely deployed for mission-critical applications. However, there is a big gap between traditional network reliability analysis theories and realistic sensor network system environments. The primary objective of this research is to close such gap through new metrics, analytical models, and approaches for the reliability analysis of large-scale sensor networks. Specifically, the research has three major components: 1) concepts, metrics, and models for describing the reliability behavior of sensor networks, 2) new algorithms and methodologies for efficient reliability evaluation of sensor networks, and 3) applications/case studies for demonstrating the practical significance of the proposed theoretical approaches. The new reliability theories and methodologies developed through this project are fundamental contributions to the body of knowledge on the network system reliability as well as to the design of reliable sensor systems. Additionally, a software tool and a prototype sensor system for railway monitoring will be built to validate the proposed research, and render the theoretical research operational and applicable. This project has broader impacts through graduate and undergraduate education, and through an integrated outreach and group mentoring program that will promote recruitment and retention of female students in engineering disciplines.