The Internet of Things (IoT) is a massive interconnected ecosystem of wireless connected devices ranging from traditional computing devices to mundane objects. The low-cost nature and limited resources of most IoT devices coupled with the sheer scale of the system introduce fundamentally new design constraints. In particular, a significant fraction of IoT devices will be deployed at hard-to-reach places which makes it challenging to replace their batteries frequently. One appealing solution to this is to allow IoT devices to harvest their own energy from ambient sources, such as the radio frequency (RF) signals of existing wireless networks. To this end, the overarching goal of this research is to develop a foundational framework that will unravel the performance and operational limits of a large-scale energy harvesting IoT system. In particular, the developed framework will provide a unified approach to the modeling, analysis, and optimization of an energy harvesting IoT under realistic operational constraints obtained from the proposed test-bed of prototype IoT devices. This research is complemented by an elaborate educational plan that includes development of new courses and mentoring of graduate and undergraduate students on research at the intersection of wireless networking, energy harvesting, and IoT. Elaborate outreach events leveraging hands-on IoT experiments targeting under-represented minorities at local schools are also planned.
This transformative research will lay the foundations of an energy harvesting IoT by developing the first comprehensive framework for analyzing and optimizing IoT performance under energy harvesting constraints. This framework integrates novel ideas from wireless networking, stochastic geometry, game theory, learning, and device implementation, to yield the following fundamental innovations: 1) New spatial models and associated performance metrics for the joint analysis of energy harvesting and communication aspects of energy harvesting IoT systems, 2) Energy-constrained and correlation-aware edge-intelligence techniques for an energy harvesting IoT, 3) Novel, self-organizing resource management mechanisms that advance new ideas from game theory to capture the scale, dynamics, and inter-dependencies across IoT devices, 4) Real-time, online algorithms that enable each IoT device to find its optimal resource management solution in a fully self-organizing manner, and 5) Design and implementation of a novel wideband RF energy harvesting module using wake up circuits that will only activate energy harvesting on the bands where RF energy harvested is more than the energy dissipated by the corresponding components. Collectively, these innovations will lay the foundations of a new breed of energy-harvesting IoT that can cater to emerging smart city services.
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.
