CAREER: Survivable, Maintainable, and Adaptable Sensor Networks

University Of Arkansas, Fayetteville AR

Investigators

Abstract

This Faculty Early Career Development Program (CAREER) award will contribute to the advancement of national prosperity and increased national security by studying efficient operations of complex wireless sensor networks. Wireless sensor networks (WSNs) are increasingly used to collect and process data over space and time in a variety of domains. Wireless sensor networks appear in ecosystems and geological phenomena, as well in monitoring adversarial use of biological, chemical, or nuclear weapons. In all of these applications, the WSN must provide effective coverage over an extended period of time even as individual sensors fail and require maintenance. Acquiring and/or installing sensors may be costly, raising the question of how to ensure satisfactory performance of the WSN indefinitely. This award supports research to establish methodology required for the design and maintenance of the WSN over time as it evolves to meet changing conditions. The award will additionally support the creation of a new interdisciplinary honors curriculum within the PI's home institution. This program will prepare engineering students to tackle multi-disciplinary problems by broadening their awareness of emerging solutions to modern societal problems. This research will contribute to the complex problem of designing, maintaining, and adapting ad hoc WSNs over time. This problem entails numerous sources of computational complexity stemming from modeling randomly evolving networks and decisions made over time. Overcoming these challenges will require advancing mathematical and computational methods from network optimization, complex system reliability, Monte Carlo simulation, stochastic processes, and stochastic optimization. The research will initially develop stochastic network maintenance models and computationally tractable reliability estimation procedures for the purpose of describing WSN reliability under a given maintenance policy. Optimization methodology will be derived to incorporate emerging reliability representation/estimation techniques in order to determine efficient fixed-schedule and condition-based maintenance policies that are efficient with respect to cost and reliability criteria. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.