Self-Sustainable Data-Driven Systems In the Field
Data-driven intelligence is an essential foundation for physical systems in
transportation safety and efficiency, area surveillance and security, as well
as environmental sustainability. This project develops new computer system
infrastructure and algorithms for self-sustainable data-driven systems in the
field. Research outcomes of the project include (a) a low-maintenance,
environmentally-friendly hardware platform with solar energy harvesting and
super capacitor-based energy storage, (b) virtualization software
infrastructure for low-power nodes to enable inter-operability among
distributed field nodes and from/to the data center, and (c) new image and
data processing approaches for resource-adaptive fidelity adjustment and
function partitioning. The synergy between the self-sustainable hardware,
system software support, wireless communications management, and application
data processing manifests through global coordination for quality-of-service,
energy efficiency, and data privacy.
This picture illustrates our deployment on a seven-story building rooftop
that includes a camera, a block of
solar panels, and a system box. The system box contains a
Nexus 7 tablet computer (without its internal rechargeable battery)
sustained by eight Maxwell 3000 Farad supercapacitors (wrapped in
black tapes), and a custom-built controller board (at the top of the box).
The energy buffering capacity of the supercapacitors is about 1.4 times
that in the original Nexus 7 battery.
In broader impacts, this project enables data-driven intelligence in the
field for important physical system domains. Integration of the technologies
involved is accomplished through real-world system deployment and
experimentation, including an intelligent campus traffic and parking
management system and collaborative work with industry collaborators. The
results of this project will further enhance the technological
competitiveness for US industries in key areas such as intelligent
transportation. The education component includes cross-disciplinary
curriculum enhancements and the development of a new instructional platform
for realistic experiments with cyber-physical systems. Within the scope of
this project, the PIs perform mentoring and outreach activities to
recruit/retain women and minorities in science and engineering.
Kai Shen at Computer Science;
Gaurav Sharma, and
Tolga Soyata at Electrical and Computer Engineering.
Kofi Sarpong Adu-Manu, Cristiano Tapparello, Wendi Heinzelman, Ferdinand Apietu Katsriku, Jamal-Deen Abdulai,
"Water Quality Monitoring Using Wireless Sensor Networks: Current Trends and Future Research Directions".
To appear in ACM Transactions on Sensor Networks, 2017.
A. Page, M. K. Aktas, T. Soyata, W. Zareba and J. Couderc,
"The 'QT Clock' to Improve Detection of QT Prolongation in Long QT Syndrome Patients".
In Heart Rhythm, 2016.
Tolga Soyata, Lucian Copeland, and Wendi Heinzelman,
"RF Energy Harvesting for Embedded Systems: A Survey of Tradeoffs and Methodology".
In IEEE Circuits and Systems Magazine, 2016.
O. Kocabas, T. Soyata, and M. K. Aktas,
"Research Directions in Cloud-Based Decision Support Systems for Health Monitoring Using Internet-of-Things Driven Data Acquisition".
In International Journal of Services Computing, vol. 4, no. 4, 2016.
A. Page, S. Hijazi, D. Askan, B. Kantarci, and T. Soyata,
"Emerging Security Mechanisms for Medical Cyber Physical Systems".
In IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2016.
G. Honan, A. Page, O. Kocabas, T. Soyata, and B. Kantarci,
"Internet-of-Everything Oriented Implementation of Secure Digital Health (DHealth) Systems".
In Proceedings of the 2016 IEEE Symposium on Computers and Communications, 2016.
Malitha Wijesundara, Cristiano Tapparello, Amalinda Gamage, Yadhavan Gokulan, Logan Gittelson, Thomas Howard, and Wendi Heinzelman,
"Design of a Kinetic Energy Harvester for Elephant Mounted Wireless Sensor Nodes of JumboNet".
In IEEE GLOBECOM, 2016.
Meng Zhu and Kai Shen,
"Energy Discounted Computing on Multicore Smartphones".
In Proc. of the USENIX Annual Technical Conference (USENIX ATC'16),
Denver, CO, June 2016.
Zhuan Chen and Kai Shen,
"OrderMergeDedup: Efficient, Failure-Consistent Deduplication on Flash".
In Proc. of the 14th USENIX Conference on File and Storage Technologies (FAST'16),
Santa Clara, CA, February 2016.
Maryam Pouryazdan, Burak Kantarci, Tolga Soyata, and Houbing Song,
"Anchor-Assisted and Vote-Based Trustworthiness Assurance in Smart City Crowdsensing".
In IEEE Access, vol. 4, pp. 529-541, January 2016.
M. Hassanalieragh, T. Soyata, A. Nadeau, and G. Sharma,
"UR-SolarCap: An Open Source Intelligent Auto-Wakeup Solar Energy Harvesting System for Supercapacitor Based Energy Buffering".
In IEEE Access, vol. 4, pp. 542-557, January 2016.
A. Page, T. Soyata, M. K. Aktas, and J. P. Couderc,
"An Open Source ECG Clock Generator for Visualization of Long Term Cardiac Monitoring Data".
In IEEE Access, vol. 3, pp. 2704-2714, December 2015.
N. Powers and T. Soyata,
"AXaaS (Acceleration as a Service): Can the Telecom Service Provider Rent a Cloudlet?"
In Proc. of the 4th IEEE International Conference on Cloud Networking (CLOUDNET),
Niagara Falls, Canada, October 2015.
A. Nadeau, M. Hassanalieragh, G. Sharma, T. Soyata,
"Energy awareness for supercapacitors using Kalman filter state-of-charge tracking".
In Journal of Power Sources, vol. 296, pp. 383-391, 2015.
Alex Page, Tolga Soyata, JeanPhilippe Couderc, Mehmet Aktas, Burak Kantarci, and Silvana Andreescu,
"Visualization of Health Monitoring Data acquired from Distributed Sensors for Multiple Patients".
In Proceedings of the IEEE Global Communications Conference (GLOBECOM),
San Diego, CA, 2015.
N. Powers, A. Alling, K. Osolinsky, T. Soyata, M. Zhu, H. Wang, H. Ba, W. Heinzelman, J. Shi, and M. Kwon,
"The Cloudlet Accelerator: Bringing Mobile-Cloud Face Recognition to RealTime".
In Proceedings of the IEEE Global Communications Conference (GLOBECOM), 2015.
A. S. Elliethy and G. Sharma,
"Improved specular regions localization and optical-flow based motion estimation via joint processing".
In Proc. IEEE Intl. Conf. Image Proc., Quebec City, Canada, 2015.
P. Glasser, O. Kocabas, B. Kantarci, T. Soyata, and J. Matthews,
"Energy efficient VM migration revisited: SLA assurance and minimum service disruption with available hosts".
In Proceedings of the 12th International Conference on High-Capacity Optical Networks and Emerging/Enabling Technologies, 2015.
Sharanyan Srikanthan, Sandhya Dwarkadas, and Kai Shen,
"Data Sharing or Resource Contention: Toward Performance Transparency on Multicore Systems".
In Proc. of the USENIX Annual Technical Conference (USENIX ATC'15),
Santa Clara, CA, July 2015.
M. Hassanalieragh, A. Page, T. Soyata, G. Sharma, M. Aktas, G. Mateos, B. Kantarci, and S. Andreescu,
"Health monitoring and management using internet-of-things (IOT) sensing with cloud-based processing: Opportunities and challenges".
In Proc. of the 12th IEEE International Conference on Services Computing (SCC 2015),
New York, NY, pp. 285-292, June 2015.
Qi Zhu, Meng Zhu, Bo Wu, Xipeng Shen, Kai Shen, and Zhiying Wang,
"Software Engagement with Sleeping CPUs".
In Proc. of the 15th Workshop on Hot Topics in Operating Systems (HotOS XV),
Kartause Ittingen, Switzerland, May 2015.
Conference talk slides in PDF.
H. Ayatollahi, C. Tapparello, and W. Heinzelman,
"Transmitter-Receiver Energy Efficiency: A Trade-off in MIMO Wireless Sensor Networks".
In Proc. of IEEE Wireless Communications and Networking Conference (WCNC),
New Orleans, LA, March 2015.
C. Tapparello, H. Ayatollahi and W. Heinzelman,
"Energy Harvesting Framework for Network Simulator 3 (ns-3)".
In Proc. of the 2nd International Workshop on Energy Neutral Sensing Systems (ENSsys),
Memphis, TN, November 2014.
Moeen Hassanalieragh, Tolga Soyata, Andrew Nadeau, and Gaurav Sharma,
"Solar-Supercapacitor Harvesting System Design for Energy-Aware Applications".
In Proc. of the 27th IEEE International System-on-Chip Conference (SOCC'14),
Las Vegas, NV, September 2014.
Andrew Nadeau, Gaurav Sharma, and Tolga Soyata,
"State-of-charge Estimation for Supercapacitors: A Kalman Filtering Formulation".
In Proc. of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP),
Florence, Italy, May 2014.
Konstantinos Menychtas, Kai Shen, and Michael L. Scott,
"Disengaged Scheduling for Fair, Protected Access to Computational Accelerators".
In Proc. of the 19th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'14),
Pages 301--316, Salt Lake City, UT, March 2014.
Haoliang Wang, Wei Liu, Tolga Soyata,
"Accessing Big Data in the Cloud Using Mobile Device".
In Handbook of Research on Cloud Infrastructures for Big Data Analytics, IGI Global,
Kai Shen, Stan Park, and Meng Zhu,
"Journaling of Journal Is (Almost) Free".
In Proc. of the 12th USENIX Conference on File and Storage Technologies (FAST'14),
Pages 287-293, Santa Clara, CA, February 2014.
Conference talk slides in Powerpoint.
Ovunc Kocabas, Tolga Soyata, Jean-Philippe Couderc, Mehmet Aktas, Jean Xia, and Michael Huang,
"Assessment of Cloud-based Health Monitoring using Homomorphic Encryption".
In Proc. of the 31st IEEE International Conference on Computer Design (ICCD'13),
Asheville, NC, October 2013.
Kai Shen, Arrvindh Shriraman, Sandhya Dwarkadas, Xiao Zhang, and Zhuan Chen,
"Power Containers: An OS Facility for Fine-Grained Power and Energy Management on Multicore Servers".
In Proc. of the 18th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'13),
Houston, TX, March 2013.
Conference talk slides in Powerpoint.
Amal Fahad, Tolga Soyata, Tai Wang, Gaurav Sharma, Wendi Heinzelman, and Kai Shen,
"SOLARCAP: Super Capacitor Buffering of Solar Energy for Self-Sustainable Field Systems".
In Proc. of the 25th IEEE International System-on-Chip Conference,
Niagara Falls, NY, September 2012.
Support: This project is supported by the National Science Foundation under
Grant No. 1239423. Link to the award abstract.
Note: Any opinions, findings, and
conclusions or recommendations expressed in this material are those of the
author(s) and do not necessarily reflect the views of the National Science Foundation.