Motivated by the events of Sept. 11, 2001, back in 2002 we proposed to use wireless technology for locating survivors of structural collapse. The proposed architecture included a network of wireless tags that would allow acquiring information from trapped survivors. While that work presented theoretical results in the area of energy efficient routing, the convergence of ultra-low-power communications and energy-harvesting technologies will soon enable realizing the vision of self-powered networked nodes.
Our activities in this area take place within the multi-PI Energy Harvesting Active Network Tags (EnHANTs) project. EnHANTs will be small, flexible, and energetically self-reliant devices that can be attached to objects that are traditionally not networked (e.g., books, furniture, walls, doors, toys, keys, clothing, and produce), thereby providing the infrastructure for various novel tracking applications. Examples of these applications include locating misplaced items and continuous monitoring of objects (items in a store, boxes in transit). As such, EnHANTs will be one of the enablers for the Internet of Things (IoT) and for Cyber Physical Systems.
In order for EnHANTs to rely on harvested energy, they have to spend significantly less energy than existing low-power wireless technologies (e.g, Bluetooth, Zigbee). Moreover, the energy harvesting components and the ultra-low-power physical layer have special characteristics whose implications on the higher layers have yet to be studied. Hence, in the EnHANTs project we seek to design hardware, algorithms, and software to overcome the challenges posed by these special characteristics.
Within this project, the WiMNet Lab focuses on the development and performance evaluation of resource allocation algorithms. The design of such algorithms requires nontraditional approaches, since energy harvesting shifts the nature of energy-aware protocols from prolonging the lifespan of a device to enabling perpetual life. Moreover, different algorithmic approaches are required for supporting different types of energy storage devices (i.e., battery and capacitor) and different harvesting environments. To support the algorithms’ development, we experimentally characterized energy availability in various environments. In particular, we conducted a long-term indoor light energy measurement campaign (the collected traces are available via CRAWDAD) and a measurement campaign to characterize kinetic energy availability. Based on the measurement results, we developed and evaluated algorithms for time fair energy allocation in networks with predictable and stochastic energy inputs, and with different types of energy storage devices.
Our other focus area is the design of EnHANT prototypes and testbed and in particular software development and software and hardware integration. The prototypes have been developed in a multi-lab interdisciplinary effort and prototype demonstrations took place in 6 conferences. A testbed composed of the prototypes received the ACM SenSys 2011 Best Student Demo Award (the video below shows that version of the testbed) and we have been using the prototypes to experimentally evaluate the performance of energy harvesting adaptive algorithms.
Overall, our measurement-based, theoretical, and experimental studies provide a fundamental understanding of the design tradeoffs in networks of rechargeable nodes. A recording of a talk in which Maria Gorlatova presents various aspects of our work is available online.
The project won the 1st place in the Vodafone Americas Foundation Wireless Innovation Competition and was discussed in several media outlets including BBC/PRI The World. For more details see the EnHANTs project website.