Senses Lab

SEnsors NetworkS and Embedded Systems Laboratory

Center for Cyber Intelligence and Information Security

Design, evaluation and test of complete solutions for Green Wireless Sensor Networks

Energy harvesting nodesBy exploiting novel HW concepts and HW/SW cross optimizations, we are developing solutions for a new generation of sensor nodes equipped with radio triggering circuits and multi-source energy harvesting. Collectively, these new technologies have the potential to change the time horizon for WSNs autonomous operations, posing the basis for energy neutral systems.
We have designed and developed solutions for structural health monitoring, mechanisms for energy prediction and management, protocols for harvesting-aware resource allocation, and harvesting-aware schemes that enable robust and reliable security support. We have also developed GreenCastalia, an open-source energy-harvesting simulation framework that allows to simulate networks of embedded devices with heterogeneous harvesting capabilities.


Green WSNs for structural health monitoring

Mote equipped with a wind micro-turbine, deployed in a tunnel of the Rome underground B1 line.

This activity has been performed within the framework of the FP7 EC project GENESI, coordinated by Prof. Chiara Petrioli. The first version of GENESI system has been used to monitor structural health monitoring parameters during the construction of the Rome underground B1 line. As a part of this activity, we used wind-energy-harvesting Telos B motes to instrument 220 meters of underground tunnel, collecting data about the air-flow generated by passing trains for more than a month. An analysis of the energy availability in such scenario, quantified in terms of typical WSN operations, such as communication, storage and sensing, is available here.

We have also presented a power management technique for improving the efficiency of harvesting energy from air-flows. The proposed architecture consists of a two-stage energy conversion circuit: an AC-DC converter followed by a DC-DC buck-boost regulator with Maximum Power Point Tracking (MPPT) capability. By using the adaptive AC-DC converter combined with power prediction algorithms, nodes deployed in an underground tunnel of the Metro B1 line in Rome can harvest up to 22% more energy with respect to previous methods. 

Danilo Porcarelli, Dora Spenza, Davide Brunelli, Alessandro Cammarano, Chiara Petrioli and Luca Benini
Adaptive Rectifier Driven by Power Intake Predictors for Wind Energy Harvesting Sensor Networks
IEEE Journal of Emerging and Selected Topics in Power Electronics, 2014.
Alessandro Cammarano, Dora Spenza and Chiara Petrioli
Energy-harvesting WSNs for structural health monitoring of underground train tunnels
IEEE INFOCOM 2013,
Torino, Italy. April, 14-19. 2013. pp. 9-10.

Energy prediction models

Energy prediction methods can be employed to alleviate the problem of the variable behavior of ambient energy sources, which results in different amounts and rates of energy available to power-scavenging devices over time. Such models forecast the source availability and estimate the expected energy intake, allowing the system to take critical decisions about the utilization of the available energy. We contribute to this topic by developing a general framework for multi-source (i.e., solar and wind) energy-harvesting systems, which accurately predicts the energy intake within forecasting horizons that are dynamically chosen based on the application needs. The key component of our solution is Pro-Energy (PROfi le Energy prediction model), a novel energy prediction model that leverage past energy observations to provide estimations of future energy availability. Extensive performance evaluations, performed by using real-life traces of harvested energy, confirmed that Pro-Energy significantly outperforms energy predictors previously proposed in the literature, such as EWMA and WCMA.
We also presented a further enhancement of the Pro-Energy prediction algorithm, named Pro-Energy-VLT, which adapts to the source dynamics to improve the accuracy of energy predictions, while reducing memory and energy overhead.

Alessandro Cammarano, Chiara Petrioli and Dora Spenza
Online Energy Harvesting Prediction in Environmentally-Powered Wireless Sensor Networks
IEEE Sensors Journal,
2016
Alessandro Cammarano, Chiara Petrioli and Dora Spenza
Improving energy predictions in EH-WSNs with Pro-Energy-VLT
ACM Sensys 2013,
Rome, Italy, November 11-13. 2013. pp. 41:1-41:2
Alessandro Cammarano, Chiara Petrioli and Dora Spenza
Pro-Energy: a novel energy prediction model for solar and wind energy harvesting Wireless Sensor Networks
IEEE MASS 2012,
Las Vegas, Nevada. October, 8-11. 2012. pp. 75 - 83.

[ Presentation slides: pdf ]

Task allocation and selective activation

task allocation

Sensor mission assignment involves matching the sensing resources of a WSN to appropriate tasks (missions), which may come to the network dynamically. Although solutions for WSNs with battery-operated nodes have been proposed for this problem, no attention has been given to networks whose nodes have energy harvesting capabilities, which impose quite a different energy model. We have addressed such problem by providing both an analytical model and a distributed heuristic, called EN-MASSE, for energy harvesting WSNs. The objective of both our model and EN-MASSE is to maximize the profit of the network, fully exploiting the harvesting technologies, while ensuring the execution of the most critical missions within a given target WSN lifetime. By comparing mission assignment schemes in several different scenarios we have demonstrated that traditional assignment algorithms cannot harness the full potential provided by the harvesting technology, which is instead taken into account efficiently by our proposed scheme. Moreover, using our analytical model as a benchmark, we also show that the profit earned by EN-MASSE is close to the optimum. Finally, we have implemented our proposed solution in TinyOS and experimentally validated its performance.

Thomas La Porta, Chiara Petrioli, Cynthia Phillips and Dora Spenza
Sensor-mission assignment in rechargeable wireless sensor networks
ACM Transactions on Sensor Networks, 2013.
Thomas La Porta, Chiara Petrioli and Dora Spenza
Sensor-mission Assignment in Wireless Sensor Networks with Energy Harvesting
IEEE SECON 2011,
Salt Lake City, UT. June. 2011. pp. 413-421.

Green WSNs security

Energy harvesting capabilities embedded in modern sensor nodes permit to take design choices, for a variety of wireless sensor network services, which would be hardly viable in traditional battery-powered motes. Such new opportunities are expecially attractive in the context of security in WSNs, as many solutions are deemed as being too energy demanding to be practically implemented on embedded devices. Our contribution in this topic includes the development of a context-aware decentralized data Access control for GREEn WSNs, called AGREE and of techniques to make ECDSA signatures energetically low cost and implementable on resource-constrained devices. We have proposed several optimizations for dealing with resource and energy constrained embedded systems, as well as a caching mechanisms to exploit the characteristics of Green WSNs. Our implementation on MagoNode++, Telos B and Mica2 motes have confirmed that such technique are able to efficiently operate based on the energy harvested in excess.

Giuseppe Ateniese, Giuseppe Bianchi, Angelo T. Capossele, Dora Spenza and Chiara Petrioli
Low-cost Standard Signatures for Energy-Harvesting Wireless Sensor Networks
ACM Transactions on Embedded Computing Systems, 2016.
Giuseppe Bianchi, Angelo T. Capossele, Chiara Petrioli and Dora Spenza
AGREE: exploiting energy harvesting to support data-centric access control in WSNs
Elsevier Ad Hoc Networks,
Vol. 11. 2013, pp. 2625 - 2636.
Giuseppe Ateniese, Giuseppe Bianchi, Angelo T. Capossele and Chiara Petrioli
Low-cost Standard Signatures in Wireless Sensor Networks: A Case for Reviving Pre-computation Techniques?
NDSS 2013, San Diego, CA. February 24-27. 2013.

Simulations of energy-harvesting WSNs

GreenCastalia logo

The emergence of energy-scavenging techniques for powering networks of embedded devices is raising the need for dedicated simulation frameworks that can support researchers and developers in the design and performance evaluation of harvesting-aware protocols and algorithms. Our contribution to this topic is GreenCastalia, an open-source energy-harvesting simulation framework we have developed for the popular Castalia simulator. GreenCastalia supports multi-source and multi-storage energy harvesting architectures, it is highly modular and easily customizable. In addition, it allows to simulate networks of embedded devices with heterogeneous harvesting capabilities.
David Benedetti, Chiara Petrioli and Dora Spenza
GreenCastalia: An Energy-Harvesting-Enabled Framework for the Castalia Simulator
ACM ENSSys 2013,
Rome, Italy. Nov. 2013. 

Radio-triggering techniques and wake-up-enabled communication stacks for Energy-Harvesting WSNs

Emerging low-power radio triggering techniques for wireless motes are a promising approach to prolong the lifetime of WSNs. By allowing nodes to activate their main transceiver only when data need to be transmitted or received, wake-up-enabled solutions virtually eliminate the need for idle listening, thus drastically reducing the energy toll of communication.
Within the framework of the FP7 EC project GENESI, in collaboration with the EE group lead by Prof. Trifiletti, we have designed and developed a novel wake-up receiver architecture based on an innovative pass-band filter bank with high selectivity capability. The proposed concept combines both frequency-domain and time-domain addressing space to allow selective addressing of nodes. To take advantage of the functionalities of the proposed receiver, as well as of energy-harvesting capabilities modern sensor nodes are equipped with, we have designed a novel wake-up-enabled harvesting-aware communication stack that supports both interest dissemination and convergecasting primitives. This stack builds on the ability of the developed WuR to support dynamic address assignment, which is exploited to optimize system performance. Comparison against traditional WSN protocols shows that the proposed concept allows to optimize performance tradeoffs with respect to existing low-power communication stacks.
Dora Spenza, Michele Magno, Stefano Basagni, Luca Benini, Mario Paoli and Chiara Petrioli
Beyond Duty Cycling: Wake-up Radio with Selective Awakenings for Long-lived Wireless Sensing Systems
IEEE INFOCOM 2015
, Hong Kong, 26 April - 1 May, 2015.
Angelo Capossele, Valerio Cervo, Chiara Petrioli and Dora Spenza
Counteracting Denial-of-Sleep Attacks in Wake-up-based Sensing Systems
IEEE SECON 2016
, London, 27 - 30 June, 2016.
Stefano Basagni, Chiara Petrioli and Dora Spenza
CTP-WUR: The Collection Tree Protocol in Wake-up Radio WSNs for Critical Applications
IEEE ICNC 2016
, Kauai, Hawaii, Feb 2016.
Chiara Petrioli, Dora Spenza, Pasquale Tommasino and Alessandro Trifiletti
A Novel wake-up Receiver with Addressing Capability for Wireless Sensor Nodes
IEEE DCOSS 2014
, Los Angeles, CA, May 2014.
Mario Paoli, Dora Spenza, Chiara Petrioli, Michele Magno and Luca Benini
MagoNode++: A Wake-Up-Radio-Enabled Wireless Sensor Mote for Energy-Neutral Applications
ACM/IEEE IPSN 2016 (Poster Session)
, Vienna, Austria, Apr 2016.
  

SENSESLab Members

  

Selected publications

  • "Online Energy Harvesting Prediction in Environmentally-Powered Wireless Sensor Networks", IEEE Sensors Journal. 2016. Full textBibTeXOnline version Read more
  • "Low-cost Standard Signatures for Energy-Harvesting Wireless Sensor Networks", ACM Transactions on Embedded Computing Systems. 2016. Full textBibTeX Read more
  • "MagoNode++: A Wake-Up-Radio-Enabled Wireless Sensor Mote for Energy-Neutral Applications". Proceedings of ACM/IEEE IPSN 2016 (Poster Session). Vienna, Austria. Apr. 2016. Full textBibTeX Read more
  • "CTP-WUR: The Collection Tree Protocol in Wake-up Radio WSNs for Critical Applications". Proceedings of IEEE ICNC 2016. Kauai, Hawaii. Feb. 2016. Full textBibTeXOnline version Read more
  • "Adaptive Rectifier Driven by Power Intake Predictors for Wind Energy Harvesting Sensor Networks", IEEE Journal of Emerging and Selected Topics in Power Electronics, Vol. 3. 2014, pp. 471-482. Full textBibTeXOnline version Read more
  • "Sensor-mission assignment in rechargeable wireless sensor networks", ACM Transactions on Sensor Networks (TOSN), Vol. 10, June, 2014. Full textBibTeXOnline version Read more
  • "A Novel wake-up Receiver with Addressing Capability for Wireless Sensor Nodes". Proceedings of IEEE DCoSS 2014. Marina Del Rey, USA. May 26-28. 2014. pp. 18-25. Full textBibTeXOnline version Read more
  • "AGREE: exploiting energy harvesting to support data-centric access control in WSNs", Elsevier Ad Hoc Networks, Vol. 11. 2013, pp. 2625 - 2636. Full textBibTeXOnline version Read more
  • "GreenCastalia: An Energy-Harvesting-Enabled Framework for the Castalia Simulator". Proceedings of ACM ENSSys 2013. Rome, Italy : ACM. Nov 14. 2013. pp. 7:1-7:6. Full textBibTeXOnline version Read more
  • "Improving energy predictions in EH-WSNs with Pro-Energy-VLT". Proceedings of ACM SenSys 2013, Poster Session. Rome, Italy : ACM. November 11-13. 2013. pp. 41:1-41:2. Full textBibTeXOnline version Read more