Welcome to the EnHANTs Project!
In this project we are developing Energy-Harvesting Active Networked Tags (EnHANTs). EnHANTs are 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, continuous monitoring of objects (items in a store, boxes in transit), and determining locations of disaster survivors.
Recent advances in ultra-low-power wireless communications, ultra-wideband (UWB) circuit design, and organic electronic harvesting techniques will enable the realization of EnHANTs in the near future. In order for EnHANTs to rely on harvested energy, they have to spend significantly less energy than Bluetooth, Zigbee, and IEEE 802.15.4a devices. Moreover, the harvesting components and the ultra-low-power physical layer have special characteristics whose implications on the higher layers have yet to be studied (e.g., when using ultra-low-power circuits, the energy required to receive a bit is significantly higher than the energy required to transmit a bit).
The objective of the project is to design hardware, algorithms, and software to enable the realization of EnHANTs. This interdisciplinary project includes 5 PIs in the departments of Electrical Engineering and Computer Science at Columbia University with expertise in energy-harvesting devices and techniques, ultra-low power integrated circuits, and energy efficient communications and networking protocols.
The project is supported in part by:
T. Chen, J. Ghaderi, D. Rubenstein, and G. Zussman, “Maximizing broadcast throughput under ultra-low-power constraints,” in Proc. ACM CoNEXT’16, Dec. 2016.
This year ACM CoNEXT (ACM International Conference on emerging Networking EXperiments and Technologies) received 199 submissions and the acceptance ratio was 17.6%.
The paper is motivated by wireless object tracking applications such as the ones envisioned in the EnHANTs project. Such applications will soon utilize emerging ultra-low-power device-to-device communication. However, severe energy constraints require much more careful accounting of energy usage than what prior art provides. In particular, the available energy, the differing power consumption levels for listening, receiving, and transmitting, as well as the limited control bandwidth must all be considered.
Therefore, the paper formulates the problem of maximizing the throughput among a set of heterogeneous broadcasting nodes with differing power consumption levels, each subject to a strict ultra-low-power budget. The oracle throughput (i.e., maximum throughput achieved by an oracle) is obtained and Lagrangian methods are used to design EconCast – a simple asynchronous distributed protocol in which nodes transition between sleep, listen, and transmit states, and dynamically change the transition rates.
It is shown that EconCast approaches the oracle throughput. Moreover, the performance is evaluated numerically and via extensive simulations and it is shown that EconCast outperforms prior art by 6x – 17x under realistic assumptions. Finally, EconCast is implemented using the TI eZ430-RF2500-SEH energy harvesting nodes and it is experimentally shown that in realistic environments it obtains 57% – 77% of the achievable throughput.
One conference paper and two journal papers have been recently accepted:
- ACM CoNEXT 2016: A paper authored by Tingjun Chen, Javad Ghaderi, Dan Rubenstein, and Gil Zussman, titled "Maximizing broadcast throughput under ultra-low-power constraints", was accepted to the upcoming ACM CoNEXT conference to be held in Dec. 2016 in Irvine, CA.
- IEEE JSAC 2016: A paper authored by Robert Margolies, Guy Grebla, Tingjun Chen, Dan Rubenstein, and Gil Zussman, titled “Panda: Neighbor discovery on a power harvesting budget”, was accepted to appear in the IEEE Journal on Selected Areas in Communications, Series on Green Communications and Networking, 2016
- Algorithmica 2016: A paper authored by Jelena Marasevic, Cliff Stein, and Gil Zussman, titled “Max-min fair rate allocation and routing in energy harvesting networks: Algorithmic analysis”, was accepted to appear in Algorithmica.
One demonstration has been recently accepted:
- ACM SenSys 2016 Demo: A demo abstract authored by Tingjun Chen, Gregory Chen, Saahil Jain, Robert Margolies, Guy Grebla, Dan Rubenstein, and Gil Zussman, titled “Demo abstract: Power-aware neighbor discovery for energy harvesting things”, was accepted to the demo session at the ACM SenSys conference to be held in Nov. 2016 in Stanford, CA.
Dr. Robert Margolies received the Electrical Engineering Collaborative Research Award. The award is “presented to Ph.D. candidates who make a superb contribution to a collaborative research effort”. The award recognizes his excellent contribution to the EnHANTs project and his role in leading the collaborations within the project over the past few years. Robert received his Ph.D. in Sept. 2015 under the supervision of Prof. Gil Zussman and is a recipient of the NSF Graduate Research Fellowship, Egleston Doctoral Fellowship, ACM SenSys’11 Best Student Demo Award, and the Columbia University Electrical Engineering Master’s Award of Excellence.
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.
- R. Margolies, G. Grebla, T. Chen, D. Rubenstein, and G. Zussman, "Panda: Neighbor discovery on a power harvesting budget," in Proc. IEEE INFOCOM'16 (to appear), Apr. 2016.
- M. Ashraphijuo, V. Aggarwal, X. Wang, “On the Capacity of Energy Harvesting Communication Link,” IEEE Journal on Selected Areas in Communications, vol. 33, no. 12, pp. 2671-2686, Dec. 2015.
- R. Margolies, M. Gorlatova, J. Sarik, G. Stanje, J. Zhu, P. Miller, M. Szczodrak, B. Vigraham, L. Carloni, P. Kinget, I. Kymissis, G. Zussman, "Energy Harvesting Active Networked Tags (EnHANTs): Prototyping and Experimentation," ACM Transactions on Sensor Networks, vol. 11, no. 4, pp. 62:1-62.27, Nov. 2015.