This project, addressing heterogeneous and dynamic sensor technologies, facilitates experimental research, demonstrating and distributing scalable middleware services that support hybrid sensor technologies, including traditional scalar sensors such as the Berkeley motes, as well as newer sensors such as the OGI panoptes video-based sensors. The work focuses on the following tasks: Adaptive Network Protocols, Global Power Management, and Programmable Architectures. Dynamically inferring and exploiting the heterogeneity of network components, the 1st task investigates mechanisms to support a range of sensor networking technologies by designing adaptive protocols for network resource management and data recovery. The 2nd investigates techniques to help designers understand global power management in heterogeneous sensor networking applications. The 3rd task investigates middleware to support the programmability of hybrid signaling within video-based sensor networks. To validate and demonstrate the approach, three sample applications will be built. Time-Elapsed Imaging for Coastal Monitoring (used to sense light), Security Monitoring (used to sense movement in a room), and Health-Care Monitoring (used to validate video and vice versa with scalars). The difference between a custom-built application and a middleware version for various parameters will be measured in each case, as well as how much energy can be saved by having hybrid sensors working cooperatively (rather than autonomously) to manage power. This project explores the fundamental challenges in enabling such applications. Addressing the diversity in sensors should be critical in addressing the sensor networking applications of the future. These systems comprise the integration and interaction of diverse classes of sensor nodes, motivating approaches that require greater synergy among nodes than those previously explored in the traditional sensor networks. Augmenting the infrastructure through separate funds with a variety of additional sensing devices, will enable the creation of an extensive and flexible testbed to study scalable middleware services that support hybrid technologies. Hybrid sensor technologies can enrich the potential of sensor applications.
Broader Impact: The artifacts of this research will be useful to the broader community; the experiences with real applications can inform further research. Moreover, the experimental research will further enable scientists in the Environmental Science and Biomedical Engineering Departments. This work enhances the curriculum enabling students to partake in experimental sensor networks research for their course work.
