Dr. Maria Gorlatova and Dr. Aya Wallwater received the IEEE Communications Society Young Author Best Paper Award
Dr. Maria Gorlatova and Dr. Aya Wallwater received the IEEE Communications Society Young Author Best Paper Award for the following paper:
M. Gorlatova, A. Wallwater, and G. Zussman, "Networking Low-Power Energy Harvesting Devices: Measurements and Algorithms", IEEE Transactions on Mobile Computing, Vol. 13, No. 9, pp. 1853-1865, Sept. 2013.
This award recognizes "Author(s) of an original paper in a subject related to the Society’s technical scope and appearing in one of the Society’s solely owned or jointly owned transactions or journals in the previous 3 calendar years and who, upon the date of submission of the paper, is(are) less than 30 years of age." The award ceremony will take place at IEEE ICC'16 (May 2016).
The research described in the paper was motivated by advances in ultra-low-power communications and energy harvesting techniques. These advances will soon enable the operation of energy harvesting wireless nodes (e.g., powered by energy harvested from indoor light) that can serve as one of the building blocks for the Internet of Things. Although a lot of data is available regarding outdoor solar and wind energy, at the time of the paper publication, there was almost no information about the availability and characteristics of energy whose source is indoor ambient light.
Therefore, the paper summarized the results of a first-of-its-kind measurement campaign of indoor light energy harvesting levels and provided a through analysis of the results. Specifically, the paper presents the results of a 16-months-long light measurement study and provides key insights into algorithm and system design (e.g., determining the sizes of a node’s energy harvester and battery). In addition, it introduces the design considerations of energy-harvesting-aware algorithms. In that area, it was the first to introduce the notion of time fairness to support the operation in a dynamic harvesting environment, and was the first to incorporate the nonlinearity of capacitor-based energy harvesting nodes into such algorithms.