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  • 1.
    El Yaacoub, Ahmed
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems.
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems.
    Rümmer, Philipp
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
    Poster: Fault Tolerance with Time Guarantees in Mobile Systems for Extreme Environments2024Conference paper (Refereed)
  • 2.
    He, Yuan
    et al.
    Tsinghua University, China.
    Wang, Weiguo
    Tsinghua University, China.
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Politecnico di Milano, Italy; Uppsala University, Sweden.
    Li, Shuai
    Tsinghua University, China.
    Sun, Yimiao
    Tsinghua University, China.
    Li, Jinming
    Tsinghua University, China.
    Jing, Hua
    Meituan, China.
    Wang, Ting
    Meituan, China.
    Wang, Yulei
    Meituan, China.
    Acoustic Localization System for Precise Drone Landing2024In: IEEE Transactions on Mobile Computing, Vol. 23, no 5, p. 4126-4144Article in journal (Refereed)
    Abstract [en]

    We present MicNest: an acoustic localization system enabling precise drone landing. In MicNest, multiple microphones are deployed on a landing platform in carefully devised configurations. The drone carries a speaker transmitting purposefully-designed acoustic pulses. The drone may be localized as long as the pulses are correctly detected. Doing so is challenging: i) because of limited transmission power, propagation attenuation, background noise, and propeller interference, the Signal-to-Noise Ratio (SNR) of received pulses is intrinsically low; ii) the pulses experience non-linear Doppler distortion due to the physical drone dynamics; iii) as location information is used during landing, the processing latency must be reduced to effectively feed the flight control loop. To tackle these issues, we design a novel pulse detector, Matched Filter Tree (MFT), whose idea is to convert pulse detection to a tree search problem. We further present three practical methods to accelerate tree search jointly. Our experiments show that MicNest can localize a drone 120 m away with 0.53% relative localization error at 20 Hz location update frequency. For navigating drone landing, MicNest can achieve a success rate of 94 %. The average landing error (distance between landing point and target point) is only 4.3 cm.

  • 3. Sun, Yimiao
    et al.
    Wang, Weiguo
    Mottola, Luca
    Politecnico di Milano, Italy;RI.SE Sweden.
    Wang, Ruijin
    He, Yuan
    AIM: Acoustic Inertial Measurement for Indoor Drone Localization and Tracking2023In: SenSys '22: Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems, Association for Computing Machinery (ACM), 2023, p. 476-488Conference paper (Refereed)
    Abstract [en]

    We present Acoustic Inertial Measurement (AIM), a one-of-a-kind technique for indoor drone localization and tracking. Indoor drone localization and tracking are arguably a crucial, yet unsolved challenge: in GPS-denied environments, existing approaches enjoy limited applicability, especially in Non-Line of Sight (NLoS), require extensive environment instrumentation, or demand considerable hardware/software changes on drones. In contrast, AIM exploits the acoustic characteristics of the drones to estimate their location and derive their motion, even in NLoS settings. We tame location estimation errors using a dedicated Kalman filter and the Interquartile Range rule (IQR). We implement AIM using an off-the-shelf microphone array and evaluate its performance with a commercial drone under varied settings. Results indicate that the mean localization error of AIM is 46% lower than commercial UWB-based systems in complex indoor scenarios, where state-of-the-art infrared systems would not even work because of NLoS settings. We further demonstrate that AIM can be extended to support indoor spaces with arbitrary ranges and layouts without loss of accuracy by deploying distributed microphone arrays.

    Download full text (pdf)
    fulltext
  • 4.
    Mahima, K. T. Y.
    et al.
    University of Colombo, Sri Lanka.
    Weerasekara, M.
    University of Colombo, Sri Lanka.
    Zoysa, K. D.
    University of Colombo, Sri Lanka.
    Keppitiyagama, C.
    University of Colombo, Sri Lanka.
    Flierl, Markus
    KTH Royal Institute of Technology, Sweden.
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Uppsala University, Sweden.
    Voigt, Thiemo
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Uppsala University, Sweden.
    MM4Drone: A Multi-spectral Image and mmWave Radar Approach for Identifying Mosquito Breeding Grounds via Aerial Drones2023In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Springer Science and Business Media Deutschland GmbH , 2023, Vol. 488, p. 412-426Conference paper (Refereed)
    Abstract [en]

    Mosquitoes spread disases such as Dengue and Zika that affect a significant portion of the world population. One approach to hamper the spread of the disases is to identify the mosquitoes’ breeding places. Recent studies use drones to detect breeding sites, due to their low cost and flexibility. In this paper, we investigate the applicability of drone-based multi-spectral imagery and mmWave radios to discover breeding habitats. Our approach is based on the detection of water bodies. We introduce our Faster R-CNN-MSWD, an extended version of the Faster R-CNN object detection network, which can be used to identify water retention areas in both urban and rural settings using multi-spectral images. We also show promising results for estimating extreme shallow water depth using drone-based multi-spectral images. Further, we present an approach to detect water with mmWave radios from drones. Finally, we emphasize the importance of fusing the data of the two sensors and outline future research directions. 

  • 5.
    Song, Weining
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems.
    Kaxiras, Stefanos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems.
    Yao, Yuan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
    Silent Stores in the Battery-less Internet of Things: A Good Idea?2023Conference paper (Refereed)
  • 6.
    El Yaacoub, Ahmed
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems.
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems.
    Rümmer, Philipp
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
    Timing Analysis of Embedded Software Updates2023Conference paper (Refereed)
  • 7.
    Shen, Qianyao
    et al.
    KTH Royal Institute of Technology, Sweden.
    Mahima, KTY
    University of Colombo, Sri Lanka.
    de Zoysa, Kasun
    University of Colombo, Sri Lanka.
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Uppsala University, Sweden.
    Voigt, Thiemo
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Uppsala University, Sweden .
    Flierl, Markus
    KTH Royal Institute of Technology, Sweden.
    CNN-Based Estimation of Water Depth from Multispectral Drone Imagery for Mosquito Control2023In: 2023 IEEE International Conference on Image Processing (ICIP), Institute of Electrical and Electronics Engineers (IEEE), 2023, p. 3250-3254Conference paper (Refereed)
    Abstract [en]

    We present a machine learning approach that uses a custom Convolutional Neural Network (CNN) for estimating the depth of water pools from multispectral drone imagery. Using drones to obtain this information offers a cheaper, timely, and more accurate solution compared to alternative methods, such as manual inspection. This information, in turn, represents an asset to identify potential breeding sites of mosquito larvae, which grow only in shallow water pools. As a significant part of the world’s population is affected by mosquito-borne viral infections, including Dengue and Zika, identifying mosquito breeding sites is key to control their spread. Experiments with 5-band drone imagery show that our CNN-based approach is able to measure shallow water depths accurately up to a root mean square error of less than 0.5 cm, outperforming state-of-the-art Random Forest methods and empirical approaches.

  • 8.
    El Yaacoub, Ahmed
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. Politecnico di Milano, Italy.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Rümmer, Philipp
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems. University of Regensburg, Germany.
    Scheduling Dynamic Software Updates in Mobile Robots2023In: ACM Transactions on Embedded Computing Systems, ISSN 1539-9087, E-ISSN 1558-3465, Vol. 22, no 6, p. 1-27Article in journal (Refereed)
    Abstract [en]

    We present NeRTA (Next Release Time Analysis), a technique to enable dynamic software updates for low-level control software of mobile robots. Dynamic software updates enable software correction and evolution during system operation. In mobile robotics, they are crucial to resolve software defects without interrupting system operation or to enable on-the-fly extensions. Low-level control software for mobile robots, however, is time sensitive and runs on resource-constrained hardware with no operating system support. To minimize the impact of the update process, NeRTA safely schedules updates during times when the computing unit would otherwise be idle. It does so by utilizing information from the existing scheduling algorithm without impacting its operation. As such, NeRTA works orthogonal to the existing scheduler, retaining the existing platform-specific optimizations and fine-tuning, and may simply operate as a plug-in component. To enable larger dynamic updates, we further conceive an additional mechanism called bounded reactive control and apply mixed-criticality concepts. The former cautiously reduces the overall control frequency, whereas the latter excludes less critical tasks from NeRTA processing. Their use increases the available idle times. We combine real-world experiments on embedded hardware with simulations to evaluate NeRTA. Our experimental evaluation shows that the difference between NeRTA’s estimated idle times and the measured idle times is less than 15% in more than three-quarters of the samples. The combined effect of bounded reactive control and mixed-criticality concepts results in a 150+% increase in available idle times. We also show that the processing overhead of NeRTA and of the additional mechanisms is essentially negligible.

    Download full text (pdf)
    fulltext
  • 9.
    Wang, Weiguo
    et al.
    Tsinghua Univ, Beijing, Peoples R China..
    He, Yuan
    Tsinghua Univ, Beijing, Peoples R China.;Tsinghua Univ, Sch Software, Beijing, Peoples R China.;Tsinghua Univ, BNRist, Beijing, Peoples R China..
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. Politecn Milan, Milan, Italy.;RI SE, Gothenburg, Sweden..
    Li, Shuai
    Tsinghua Univ, Beijing, Peoples R China..
    Sun, Yimiao
    Tsinghua Univ, Beijing, Peoples R China..
    Li, Jinming
    Tsinghua Univ, Beijing, Peoples R China..
    Jing, Hua
    Meituan, Beijing, Peoples R China..
    Wang, Ting
    Meituan, Beijing, Peoples R China..
    Wang, Yulei
    Meituan, Beijing, Peoples R China..
    Acoustic localization of drones in precise landing: The research and practice with micnest2023In: GetMobile: Mobile Computing and Communications, ISSN 2375-0529, E-ISSN 2375-0537, Vol. 27, no 3, p. 27-32Article in journal (Other academic)
    Abstract [en]

    Delivery drones have the potential to revolutionize transportation and distribution of goods. With their autonomous navigation capabilities, they offer an efficient solution to bypass the challenges posed by complex urban traffic and enable instant package delivery. Many industrial firms are actively exploring the commercial feasibility of instant drone deliveries. Meituan, one of the largest companies in this area, devised a systematic approach to instant delivery using drones. The process begins with loading the package onto the drone, which then takes off, ascends to cruising altitude, and sets a direct course towards the designated destination. Typically, this destination is a Meituan-operated self-collection station located near the customer.

  • 10.
    Singhal, Chetna
    et al.
    Indian Institute of Technology, India.
    Voigt, Thiemo
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Uppsala University, Sweden.
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Uppsala University, Sweden; Politecnico di Milano, Italy.
    Application-aware Energy Attack Mitigation in the Battery-less Internet of Things2023In: MobiWac 2023: Proceedings of the International ACM Symposium on Mobility Management and Wireless Access, Association for Computing Machinery, Inc , 2023, p. 35-43Conference paper (Refereed)
    Abstract [en]

    We study how to mitigate the effects of energy attacks in the battery-less Internet of Things∼(IoT). Battery-less IoT devices live and die with ambient energy, as they use energy harvesting to power their operation. They are employed in a multitude of applications, including safety-critical ones such as biomedical implants. Due to scarce energy intakes and limited energy buffers, their executions become intermittent, alternating periods of active operation with periods of recharging their energy buffers. Experimental evidence exists that shows how controlling ambient energy allows an attacker to steer a device execution in unintended ways: energy provisioning effectively becomes an attack vector. We design, implement, and evaluate a mitigation system for energy attacks. By taking into account the specific application requirements and the output of an attack detection module, we tune task execution rates and optimize energy management. This ensures continued application execution in the event of an energy attack. When a device is under attack, our solution ensures the execution of 23.3% additional application cycles compared to the baselines we consider and increases task schedulability by at least 21%, while enabling a 34% higher peripheral availability. 

  • 11.
    Singhal, Chetna
    et al.
    Indian Inst Technol IIT, Kharagpur, W Bengal, India..
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. RI.SE Sweden.
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. RI.SE Sweden;Politecnico di Milano, Italy.
    Application-aware Energy Attack Mitigation in the Battery-less Internet of Things2023In: MobiWac '23: Proceedings of the Int'l ACM Symposium on Mobility Management and Wireless Access, Association for Computing Machinery (ACM), 2023, p. 35-43Conference paper (Refereed)
    Abstract [en]

    We study how to mitigate the effects of energy attacks in the batteryless Internet of Things (IoT). Battery-less IoT devices live and die with ambient energy, as they use energy harvesting to power their operation. They are employed in a multitude of applications, including safety-critical ones such as biomedical implants. Due to scarce energy intakes and limited energy buffers, their executions become intermittent, alternating periods of active operation with periods of recharging their energy buffers. Experimental evidence exists that shows how controlling ambient energy allows an attacker to steer a device execution in unintended ways: energy provisioning effectively becomes an attack vector. We design, implement, and evaluate a mitigation system for energy attacks. By taking into account the specific application requirements and the output of an attack detection module, we tune task execution rates and optimize energy management. This ensures continued application execution in the event of an energy attack. When a device is under attack, our solution ensures the execution of 23.3% additional application cycles compared to the baselines we consider and increases task schedulability by at least 21%, while enabling a 34% higher peripheral availability.

  • 12.
    Shen, Qianyao
    et al.
    KTH Royal Inst Technol, Elect Engn & Comp Sci, Stockholm, Sweden..
    Mahima, K. T. Y.
    Univ Colombo, Sch Comp, Colombo, Sri Lanka..
    De Zoysa, Kasun
    Univ Colombo, Sch Comp, Colombo, Sri Lanka..
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. RISE Res Inst Sweden, Stockholm, Sweden.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. RISE Res Inst Sweden, Stockholm, Sweden.
    Flierl, Markus
    KTH Royal Inst Technol, Elect Engn & Comp Sci, Stockholm, Sweden..
    CNN-Based Estimation of Water Depth from Multispectral Drone Imagery for Mosquito Control2023In: 2023 IEEE International Conference on Image Processing (ICIP), Institute of Electrical and Electronics Engineers (IEEE), 2023, p. 3250-3254Conference paper (Refereed)
    Abstract [en]

    We present a machine learning approach that uses a custom Convolutional Neural Network (CNN) for estimating the depth of water pools from multispectral drone imagery. Using drones to obtain this information offers a cheaper, timely, and more accurate solution compared to alternative methods, such as manual inspection. This information, in turn, represents an asset to identify potential breeding sites of mosquito larvae, which grow only in shallow water pools. As a significant part of the world's population is affected by mosquito-borne viral infections, including Dengue and Zika, identifying mosquito breeding sites is key to control their spread. Experiments with 5-band drone imagery show that our CNN-based approach is able to measure shallow water depths accurately up to a root mean square error of less than 0.5 cm, outperforming state-of-the-art Random Forest methods and empirical approaches.

  • 13. He, Yuan
    et al.
    Wang, Weiguo
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering. olitecnico di Milano, Italy;RISE Research Institutes of Sweden .
    Li, Shuai
    Sun, Yimiao
    Li, Jinming
    Jing, Hua
    Wang, Ting
    Wang, Yulei
    Acoustic Localization System for Precise Drone Landing2023In: IEEE Transactions on Mobile Computing, ISSN 1536-1233, E-ISSN 1558-0660Article in journal (Refereed)
    The full text will be freely available from 2025-06-22 15:27
  • 14.
    El Yaacoub, Ahmed
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems. Politecnico di Milano, Italy.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
    Rümmer, Philipp
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
    NeRTA: Enabling Dynamic Software Updates in Mobile Robotics2022Conference paper (Refereed)
    Abstract [en]

    We present NeRTA (Next Release Time Analysis), a technique to schedule dynamic software updates of the low-level control loops of mobile robots. Dynamic software updates enable software correction and evolution during system operation. In mobile robotics, they are crucial to resolve software defects without interrupting system operation or to enable on-the-fly extensions. Low-level control loops of mobile robots, however, are time sensitive and run on resource-constrained hardware with no operating system support. To minimize the impact of the update process, NeRTA safely schedules updates during times when the computing unit would otherwise be idle. It does so by utilizing information from the existing scheduling algorithm without impacting its operation. As such, NeRTA works orthogonal to the existing scheduler, retaining the existing platform-specific optimizations and fine-tuning, and may simply operate as a plug-in component. Our experimental evaluation shows that NeRTA estimates are within 15% of the actual idle times in more than three-quarters of the cases. We also show that the processing overhead of NeRTA is essentially negligible.

  • 15.
    Bambusi, Fulvio
    et al.
    Politecn Milan, Milan, Italy..
    Cerizzi, Francesco
    Politecn Milan, Milan, Italy..
    Lee, Yamin
    Politecn Milan, Milan, Italy..
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Politecn Milan, Milan, Italy.;RISE, Gothenburg, Sweden..
    The Case for Approximate Intermittent Computing2022In: 2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (ISPN 2022), Institute of Electrical and Electronics Engineers (IEEE), 2022, p. 463-476Conference paper (Refereed)
    Abstract [en]

    We present the concept of approximate intermittent computing and concretely demonstrate its application. Intermittent computations stem from the erratic energy patterns caused by energy harvesting: computations unpredictably terminate whenever energy is insufficient and the application state is lost. Existing solutions maintain equivalence to continuous executions by creating persistent state on non-volatile memory, enabling stateful computations to cross power failures. The performance penalty is massive: system throughput reduces while energy consumption increases. In contrast, approximate intermittent computations trade the accuracy of the results for sparing the entire overhead to maintain equivalence to a continuous execution. This is possible as we use approximation to limit the extent of stateful computations to the single power cycle, enabling the system to completely shift the energy budget for managing persistent state to useful computations towards an immediate approximate result. To this end, we effectively reverse the regular formulation of approximate computing problems. First, we apply approximate intermittent computing to human activity recognition. We design an anytime variation of support vector machines able to improve the accuracy of the classification as energy is available. We build a hw/sw prototype using kinetic energy and show a 7x improvement in system throughput compared to state-of-the-art system support for intermittent computing, while retaining 83% accuracy in a setting where the best attainable accuracy is 88%. Next, we apply approximate intermittent computing in a sharply different scenario, that is, embedded image processing, using loop perforation. Using a different hw/sw prototype we build and diverse energy traces, we show a 5x improvement in system throughput compared to state-of-the-art system support for intermittent computing, while providing an equivalent output in 84% of the cases.

  • 16.
    Mahima, K.T.Y
    et al.
    University of Colombo, Sri Lanka.
    Weerasekara, Malith
    University of Colombo, Sri Lanka.
    De Zoysa, Kasun
    University of Colombo, Sri Lanka.
    Keppitiyagama, Chamath
    University of Colombo, Sri Lanka.
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. RISE.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. RISE.
    Flierl, Markus
    KTH, Sweden.
    Fighting Dengue Fever with Aerial Drones2022In: EWSN '22: Proceedings of the 2022 International Conference on Embedded Wireless Systems and Networks / [ed] Alois Ferscha, Mun Choon Chan, Salil Kanhere & Ranga Rao Venkatesha Prasad, Association for Computing Machinery (ACM), 2022, p. 206-207Conference paper (Refereed)
    Abstract [en]

    Dengue and Zika are two arboviral viruses that affect a significant portion of the world population. Each year, almost 400 million dengue infections happen. Due to severe dengue fever, around half a million people each year are in need of hospitalization and about 36.000 people die.

    Dengue spreads rapidly in densely populated urban areas. The principle vector species of both dengue and zika viruses are the Aedes aegypti and Aedes albopictus mosquitoes. They breed in very slow-flowing or standing water pools. It is important to reduce and control such potential breeding grounds to contain the spread of these diseases.

    We describe our system design and presents initial results. We employ mmWave radios to detect water retention areas as potential mosquito habitats. Next, we use multi-spectral images to analyze the water area, measure the depth of the water, and understand the larvae density. After that, we fuse the results for the final classification of the water area.

    Download full text (pdf)
    fulltext
  • 17.
    Lundberg, Axel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems.
    Järvström, William
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems.
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. RISE Computer Science.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. RISE Computer Science.
    Westman, Erik
    Vattenfall.
    Poster: Exploring Energy Harvesting Possibilities in Embankment Dams2022In: EWSN '22: Proceedings of the 2022 International Conference on Embedded Wireless Systems and Networks, 2022, p. 200-201Conference paper (Refereed)
  • 18.
    El Yaacoub, Ahmed
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication.
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
    Rümmer, Philipp
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
    Poster Abstract: Scheduling Dynamic Software Updates in Safety-critical Embedded Systems: the Case of Aerial Drones2022In: 2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS), Institute of Electrical and Electronics Engineers (IEEE), 2022, p. 284-285Conference paper (Refereed)
    Abstract [en]

    Dynamic software updates enable software evolution and bug fixes to embedded systems without disrupting their run-time operation. Scheduling dynamic updates for safety-critical embedded systems, such as aerial drones, must be done with great care. Otherwise, the system's control loop will be delayed leading to a partial or even complete loss of control, ultimately impacting the dependable operation. We propose an update scheduling algorithm called NeRTA, which schedules updates during the short times when the processor would have been idle. NeRTA consequently avoids the loss of control that would occur if an update delayed the execution of the control loop. The algorithm computes conservative estimations of idle times to determine if an update is possible, but is also sufficiently accurate that the estimated idle time is typically within 15% of the actual idle time.

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  • 19. Afanasov, Mikhail
    et al.
    Anwar Bhatti, Naveed
    Dolui, Koustabh
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering. Politecnico di Milano, Italy;RI.SE Sweden.
    Embedded Sensing through Energy Harvesting at the Mithræum of Circus Maximus2022In: Il Mitreo del Circo Massimo: Studio Preliminare di un Monumento Inedito tra Archeologia, Conservazione e Fruizione, EUT Edizioni Università di Trieste , 2022, p. 271-299Chapter in book (Other academic)
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  • 20. Wang, Weiguo
    et al.
    Mottola, Luca
    Politecnico di Milano, Italy;RI.SE Sweden.
    He, Yuan
    Li, Jinming
    Sun, Yimiao
    Li, Shuai
    Jing, Hua
    Wang, Yulei
    MicNest: Long-Range Instant Acoustic Localization of Drones in Precise Landing2022In: SenSys '22: Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems, Association for Computing Machinery (ACM), 2022, p. 504-517Conference paper (Refereed)
    Abstract [en]

    We present MicNest: an acoustic localization system enabling precise landing of aerial drones. Drone landing is a crucial step in a drone's operation, especially as high-bandwidth wireless networks, such as 5G, enable beyond-line-of-sight operation in a shared airspace and applications such as instant asset delivery with drones gain traction. In MicNest, multiple microphones are deployed on a landing platform in carefully devised configurations. The drone carries a speaker transmitting purposefully-designed acoustic pulses. The drone may be localized as long as the pulses are correctly detected. Doing so is challenging: i) because of limited transmission power, propagation attenuation, background noise, and propeller interference, the Signal-to-Noise Ratio (SNR) of received pulses is intrinsically low; ii) the pulses experience non-linear Doppler distortion due to the physical drone dynamics while airborne; iii) as location information is to be used during landing, the processing latency must be reduced to effectively feed the flight control loop. To tackle these issues, we design a novel pulse detector, Matched Filter Tree (MFT), whose idea is to convert pulse detection to a tree search problem. We further present three practical methods to accelerate tree search jointly. Our real-world experiments show that MicNest is able to localize a drone 120 m away with 0.53% relative localization error at 20 Hz location update frequency.

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  • 21. Hokke, N H
    et al.
    Sharma, S
    Prasad, R V
    Mottola, Luca
    Politecnico di Milano, Italy.
    Narayana, S
    Rao, V
    Kouvelas, N
    RF Information Harvesting for Medium Access in Event-driven Batteryless Sensing2022In: 2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), IEEE, 2022, p. 377-389Conference paper (Refereed)
    Abstract [en]

    We present radio-frequency (RF) information harvesting, a channel sensing technique that takes advantage of the energy in the wireless medium to detect channel activity at essentially no energy cost. RF information harvesting is essential for event-driven wireless sensing applications using battery-less devices that harvest tiny amounts of energy from impromptu events, such as operating a switch, and then transmit the event notification to a one-hop gateway. As multiple such devices may concurrently detect events, coordinating access to the channel is key. RF information harvesting allows devices to break the symmetry between concurrently-transmitting devices based on the harvested energy from the ongoing transmissions. To demonstrate the benefits of RF information harvesting, we integrate it in a tailor-made ultra lowpower hardware MAC protocol we call Radio Frequency-Distance Packet Queuing (RF-DiPaQ). We build a hardware/software prototype of RF-DiPaQ and use an established Markov framework to study its performance at scale. Comparing RF-DiPaQ against staple contention-based MAC protocols, we show that it outperforms pure Aloha and 1-CSMA by factors of 3.55 and 1.21 respectively in throughput, while it saturates at more than double the offered load compared to 1-CSMA. As traffic increases, the energy saving of RF-DiPaQ against CSMA protocols increases, consuming 36% less energy than np-CSMA at typical offered loads.

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  • 22.
    Mahima, K.T.Y
    et al.
    University of Colombo, Sri Lanka.
    Weerasekara, Malith
    University of Colombo, Sri Lanka.
    De Zoysa, Kasun
    University of Colombo, Sri Lanka.
    Keppitiyagama, Chamath
    University of Colombo, Sri Lanka.
    Flierl, Markus
    KTH, Sweden.
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. RISE.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. RISE.
    MM4Drone: A Multi-Spectral Image and mmWave Radar Approach for Identifying Mosquito Breeding Grounds via Aerial Drones2022In: Pervasive Computing Technologies for Healthcare: 16th EAI International Conference, PervasiveHealth 2022, Thessaloniki, Greece, December 12-14, 2022, Proceedings / [ed] Athanasios Tsanas; Andreas Triantafyllidis, Cham: Springer, 2022, p. 412-426Conference paper (Refereed)
    Abstract [en]

    Mosquitoes spread disases such as Dengue and Zika that affect a significant portion of the world population. One approach to hamper the spread of the disases is to identify the mosquitoes’ breeding places. Recent studies use drones to detect breeding sites, due to their low cost and flexibility. In this paper, we investigate the applicability of drone-based multi-spectral imagery and mmWave radios to discover breeding habitats. Our approach is based on the detection of water bodies. We introduce our Faster R-CNN-MSWD, an extended version of the Faster R-CNN object detection network, which can be used to identify water retention areas in both urban and rural settings using multi-spectral images. We also show promising results for estimating extreme shallow water depth using drone-based multi-spectral images. Further, we present an approach to detect water with mmWave radios from drones. Finally, we emphasize the importance of fusing the data of the two sensors and outline future research directions.

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  • 23.
    Zimmerling, Marco
    et al.
    Center for Advancing Electronics Dresden, Germany .
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Politecnico di Milano, Italy.
    Santini, Silvia
    Universitá della Svizzera Italiana, Switzerland.
    Synchronous Transmissions in Low-Power Wireless: A Survey of Communication Protocols and Network Services2021In: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 53, no 6, article id 121Article in journal (Refereed)
    Abstract [en]

    Low-power wireless communication is a central building block of cyber-physical systems and the Internet of Things. Conventional low-power wireless protocols make avoiding packet collisions a cornerstone design choice. The concept of synchronous transmissions challenges this view. As collisions are not necessarily destructive, under specific circumstances, commodity low-power wireless radios are often able to receive useful information even in the presence of superimposed signals from different transmitters. We survey the growing number of protocols that exploit synchronous transmissions for higher robustness and efficiency as well as unprecedented functionality and versatility compared to conventional designs. The illustration of protocols based on synchronous transmissions is cast in a conceptional framework we establish, with the goal of highlighting differences and similarities among the proposed solutions. We conclude this article with a discussion on open questions and challenges in this research field

  • 24.
    Maioli, Andrea
    et al.
    RISE Research Institutes of Sweden. Politecnico di Milano, Italy.
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Politecnico di Milano, Italy.
    Hamad Alizai, Muhammad
    LUMS, Pakistan.
    Haroon Siddiqui, Junaid
    LUMS, Pakistan.
    Discovering the Hidden Anomalies of Intermittent Computing2021In: Proceedings of the 18th ACM International Conference on Embedded Wireless Systems and Networks (EWSN), Delft (The Netherlands), February 2021., 2021Conference paper (Other academic)
    Abstract [en]

    Energy harvesting battery-less embedded devices compute intermittently, as energy is available. Intermittent executions may differ from continuous ones due to repeated executions of non-idempotent code. This anomaly is normally recognized as a “bug” and solutions exist to retain equivalence between intermittent and continuous executions. We argue that our current understanding of these “bugs” is limited. We address this issue by devising techniques to comprehensively identify where and how intermittent and continuous executions possibly differ and by implementing them in SCEPTIC: a code analysis tool for intermittent programs. Thereby, we find execution anomalies and their manifested impact on program behavior in ways previously not considered. This analysis is enabled by SCEPTIC design, implementation, and performance. SCEPTIC runs up to ten orders of magnitude faster than the baselines we consider, enabling many types of analyses that would be otherwise impractical.

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  • 25.
    Maioli, Andrea
    et al.
    Politecnico di Milano, Italy.
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Politecnico di Milano, Italy; Uppsala University, Sweden.
    ALFRED: Virtual Memory for Intermittent Computing2021In: Proceedings of the 19th ACM International Conference on Embedded Networked Sensor Systems (SENSYS), Coimbra (Portugal), November 2021., 2021Conference paper (Other academic)
    Abstract [en]

    We present ALFRED: a virtual memory abstraction that resolves the dichotomy between volatile and non-volatile memory in intermittent computing. Mixed-volatile microcontrollers allow programmers to allocate part of the application state onto non-volatile memory. Programmers are therefore to manually explore the tradeoff between simpler management of persistent state against energy overhead and possibility of intermittence anomalies due to nonvolatile memory operations. This approach is laborious and yields sub-optimal performance. We take a different stand with ALFRED: we provide programmers with a virtual memory abstraction detached from the specific volatile nature of memory and automatically determine an efficient mapping from virtual to volatile or non-volatile memory. Unlike existing works, ALFRED does not require programmers to learn a newlanguage syntax and the mapping is entirely resolved at compile-time, reducing the run-time energy overhead.We implement ALFRED through a series of machine-level code transformations. Compared to existing systems, we demonstrate that ALFRED reduces energy consumption by up to two orders of magnitude given a fixed workload. This enables workloads to finish sooner, as the use of available energy shifts from ensuring forward progress to useful application processing.

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  • 26. Maioli, Andrea
    et al.
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Networked Embedded Systems. Politecnico di Milano, Italy;RI.SE Computer Science, Sweden.
    Virtual Memory for Intermittent Computing2021In: Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems, Association for Computing Machinery (ACM), 2021, p. 261-273Conference paper (Refereed)
  • 27.
    Zimmerling, Marco
    et al.
    TU Dresden, Dresden, Germany.
    Mottola, Luca
    Politecnico di Milano, Italy; RISE, Kista, Sweden.
    Santini, Silvia
    Universitá della Svizzera italiana (USI), Lugano, Switzerland.
    Synchronous Transmissions in Low-Power Wireless: A Survey of Communication Protocols and Network Services2020In: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 53, no 6, article id 121Article in journal (Refereed)
    Abstract [en]

    Low-power wireless communication is a central building block of cyber-physical systems and the Internet of Things. Conventional low-power wireless protocols make avoiding packet collisions a cornerstone design choice. The concept of synchronous transmissions challenges this view. As collisions are not necessarily destructive, under specific circumstances, commodity low-power wireless radios are often able to receive useful information even in the presence of superimposed signals from different transmitters. We survey the growing number of protocols that exploit synchronous transmissions for higher robustness and efficiency as well as unprecedented functionality and versatility compared to conventional designs. The illustration of protocols based on synchronous transmissions is cast in a conceptional framework we establish, with the goal of highlighting differences and similarities among the proposed solutions. We conclude this article with a discussion on open questions and challenges in this research field.

  • 28. Ahmed, Saad
    et al.
    Bhatti, Naveed Anwar
    Alizai, Muhammad Hamad
    Siddiqui, Junaid Haroon
    Mottola, Luca
    Politecnico di Milano, Italy; RISE, Sweden.
    Fast and Energy-efficient State Checkpointing for Intermittent Computing2020In: ACM Transactions on Embedded Computing Systems, ISSN 1539-9087, E-ISSN 1558-3465, Vol. 19, no 6, article id 45Article in journal (Refereed)
    Abstract [en]

    Intermittently powered embedded devices ensure forward progress of programs through state checkpointing in non-volatile memory. Checkpointing is, however, expensive in energy and adds to the execution times. To minimize this overhead, we present DICE, a system that renders differential checkpointing profitable on these devices. DICE is unique because it is a software-only technique and efficient because it only operates in volatile main memory to evaluate the differential. DICE may be integrated with reactive (Hibernus) or proactive (MementOS, HarvOS) checkpointing systems, and arbitrary code can be enabled with DICE using automatic code-instrumentation requiring no additional programmer effort. By reducing the cost of checkpoints, DICE cuts the peak energy demand of these devices, allowing operation with energy buffers that are one-eighth of the size originally required, thus leading to benefits such as smaller device footprints and faster recharging to operational voltage level. The impact on final performance is striking: with DICE, Hibernus requires one order of magnitude fewer checkpoints and one order of magnitude shorter time to complete a workload in real-world settings.

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  • 29. Ahmed, Saad
    et al.
    Nawaz, Muhammad
    Bakar, Abu
    Bhatti, Naveed Anwar
    Alizai, Muhammad Hamad
    Siddiqui, Junaid Haroon
    Mottola, Luca
    Politecnico di Milano, Italy; RI.Se SICS, Sweden.
    Demystifying Energy Consumption Dynamics in Transiently powered Computers2020In: ACM Transactions on Embedded Computing Systems, ISSN 1539-9087, E-ISSN 1558-3465, Vol. 19, no 6, article id 47Article in journal (Refereed)
    Abstract [en]

    Transiently powered computers (TPCs) form the foundation of the battery-less Internet of Things, using energy harvesting and small capacitors to power their operation. This kind of power supply is characterized by extreme variations in supply voltage, as capacitors charge when harvesting energy and discharge when computing. We experimentally find that these variations cause marked fluctuations in clock speed and power consumption. Such a deceptively minor observation is overlooked in existing literature. Systems are thus designed and parameterized in overly conservative ways, missing on a number of optimizations.

    We rather demonstrate that it is possible to accurately model and concretely capitalize on these fluctuations. We derive an energy model as a function of supply voltage and prove its use in two settings. First, we develop EPIC, a compile-time energy analysis tool. We use it to substitute for the constant power assumption in existing analysis techniques, giving programmers accurate information on worst-case energy consumption of programs. When using EPIC with existing TPC system support, run-time energy efficiency drastically improves, eventually leading up to a 350% speedup in the time to complete a fixed workload. Further, when using EPIC with existing debugging tools, it avoids unnecessary program changes that hurt energy efficiency. Next, we extend the MSPsim emulator and explore its use in parameterizing a different TPC system support. The improvements in energy efficiency yield up to more than 1000% time speedup to complete a fixed workload.

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  • 30. Afanasov, Mikhail
    et al.
    Bhatti, Naveed Anwar
    Campagna, Dennis
    Caslini, Giacomo
    Centonze, Fabio Massimo
    Dolui, Koustabh
    Maioli, Andrea
    Barone, Erica
    Alizai, Muhammad Hamad
    Siddiqui, Junaid Haroon
    Mottola, Luca
    Politecnico di Milano, Italy; RI.SE Sweden.
    Battery-less zero-maintenance embedded sensing at the mithræum of circus maximus2020In: SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems, 2020, p. 368-381Conference paper (Refereed)
    Abstract [en]

    We present the design and evaluation of a 3.5-year embedded sensing deployment at the Mithræum of Circus Maximus, a UNESCO-protected underground archaeological site in Rome (Italy). Unique to our work is the use of energy harvesting through thermal and kinetic energy sources. The extreme scarcity and erratic availability of energy, however, pose great challenges in system software, embedded hardware, and energy management. We tackle them by testing, for the first time in a multi-year deployment, existing solutions in intermittent computing, low-power hardware, and energy harvesting. Through three major design iterations, we find that these solutions operate as isolated silos and lack integration into a complete system, performing suboptimally. In contrast, we demonstrate the efficient performance of a hardware/software co-design featuring accurate energy management and capturing the coupling between energy sources and sensed quantities. Installing a battery-operated system alongside also allows us to perform a comparative study of energy harvesting in a demanding setting. Albeit the latter reduces energy availability and thus lowers the data yield to about 22% of that provided by batteries, our system provides a comparable level of insight into environmental conditions and structural health of the site. Further, unlike existing energy-harvesting deployments that are limited to a few months of operation in the best cases, our system runs with zero maintenance since almost 2 years, including 3 months of site inaccessibility due to a COVID19 lockdown.

  • 31. Ahmed, Saad
    et al.
    Ul Ain, Qurat
    Siddiqui, Junaid Haroon
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Politecnico di Milano, Italy; RI.SE Sweden.
    Alizai, Muhammad Hamad
    Intermittent Computing with Dynamic Voltage and Frequency Scaling2020In: EWSN '20: Proceedings of the 2020 International Conference on Embedded Wireless Systems and Networks / [ed] Christine Julien, Fabrice Valois, Omprakash Gnawali & Amy L. Murphy, 2020, p. 97-107Conference paper (Refereed)
    Abstract [en]

    We present D2VFS, a run-time technique to intelligently regulate supply voltage and accordingly reconfigure clock frequency of intermittently-computing devices. These devices rely on energy harvesting to power their operation and on small capacitors as energy buffer. Statically setting their clock frequency fails to achieve energy efficiency, as the setting remains oblivious of fluctuations in capacitor voltage and of their impact on a microcontroller operating range. In contrast, D2VFS captures these dynamics and places the microcontroller in the most efficient configuration by regulating the microcontroller supply voltage and changing its clock frequency. Our evaluation shows that D2VFS markedly increases energy efficiency; for example, ultimately enabling a 30-300% reduction of workload completion times.

  • 32.
    Asad, Hafiz Areeb
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
    Wouters, Erik Henricus
    Bhatti, Naveed Anwar
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. RISE.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. RISE.
    On Securing Persistent State in Intermittent Computing2020In: ENSsys '20: Proceedings of the 8th International Workshop on Energy Harvesting and Energy-Neutral Sensing Systems, 2020, p. 8-14Conference paper (Refereed)
    Abstract [en]

    We present the experimental evaluation of different security mechanisms applied to persistent state in intermittent computing. Whenever executions become intermittent because of energy scarcity, systems employ persistent state on non-volatile memories (NVMs) to ensure forward progress of applications. Persistent state spans operating system and network stack, as well as applications. While a device is off recharging energy buffers, persistent state on NVMs may be subject to security threats such as stealing sensitive information or tampering with configuration data, which may ultimately corrupt the device state and render the system unusable. Based on modern platforms of the Cortex M* series, we experimentally investigate the impact on typical intermittent computing workloads of different means to protect persistent state, including software and hardware implementations of staple encryption algorithms and the use of ARM TrustZone protection mechanisms. Our results indicate that i) software implementations bear a significant overhead in energy and time, sometimes harming forward progress, but also retaining the advantage of modularity and easier updates; ii) hardware implementations offer much lower overhead compared to their software counterparts, but require a deeper understanding of their internals to gauge their applicability in given application scenarios; and iii) TrustZone shows almost negligible overhead, yet it requires a different memory management and is only effective as long as attackers cannot directly access the NVMs.

  • 33. Narayana, Sujay
    et al.
    Prasad, R. Venkatesha
    Rao, Vijay
    Mottola, Luca
    Politecnico di Milano, Italy.
    Prabhakar, T. V.
    Hummingbird: energy efficient GPS receiver for small satellites2020In: MobiCom '20: Proceedings of the 26th Annual International Conference on Mobile Computing and Networking, 2020, p. 1-13, article id 9Conference paper (Refereed)
    Abstract [en]

    Global Positioning System is a widely adopted localization technique. With the increasing demand for small satellites, the need for a low-power GPS for satellites is also increasing. To enable many state-of-the-art applications, the exact position of the satellites is necessary. However, building low-power GPS receivers which operate in low earth orbit pose significant challenges. This is mainly due to the high speed (~7.8 km/s) of small satellites. While duty-cycling the receiver is a possible solution, the high relative Doppler shift between the GPS satellites and the small satellite contributes to the increase in Time To First Fix (TTFF), thus increasing the energy consumption. Further, if the GPS receiver is tumbling along with the small satellite on which it is mounted, longer TTFF may lead to no GPS fix due to disorientation of the receiver antenna. In this paper, we elucidate the design of a low-cost, low-power GPS receiver for small satellite applications. We also propose an energy optimization algorithm called F3to improve the TTFF which is the main contributor to the energy consumption during cold start. With simulations and in-orbit evaluation from a launched nanosatellite with our μGPS and high-end GPS simulators, we show that up to 96.16% of energy savings (consuming only ~ 1/25th energy compared to the state of the art) can be achieved using our algorithm without compromising much (~10 m) on the navigation accuracy. The TTFF achieved is at most 33 s.

  • 34. Narayana, Sujay
    et al.
    Rao, Vijay
    Prasad, R. Venkatesha
    Kanthila, A. K.
    Managundi, Kavya
    Mottola, Luca
    RISE SICS, Sweden.
    Prabhakar, T. V.
    LOCI: Privacy-aware, Device-free, Low-power Localization of Multiple Persons using IR Sensors2020In: 19th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), 2020, p. 121-132Conference paper (Refereed)
    Abstract [en]

    High accuracy and device-free indoor localization is still a holy grail to enable smart environments. With the growing privacy concerns and regulations, it is necessary to develop methods and systems that can be low-power, device-free as well as privacy-aware. While IR-based solutions fit the bill, they require many modules to be installed in the area of interest for higher accuracy, or proper planning during installation, or they may not work if the background has multiple heat-emitting objects, etc. In this paper, we propose a custom-built miniature device called LOCI that uses IR sensing. One unit of LOCI can provide three-dimensional localization at best. LOCI uses only a thermopile and a PIR sensor built within a 5×5×2 cm3 module. Since IR-based sensing is used, LOCI consumes around 80 mW. LOCI uses analog waveform from the PIR sensor with the gain of the PIR sensor dynamically controlled through software in real-time to simulate spatial diversity. LOCI proposes low-complexity techniques with sensor fusion to eliminate the noise in the background, which has not been handled in previous works even with sophisticated signal processing techniques. Since LOCI uses raw data from the thermopile, the computations are power-efficient. We present the complete design of LOCI and the proposed methodology to estimate height and location. LOCI achieves accuracies of sub-22 cm with a confidence of 0.5 and sub-35 cm with a confidence of 0.8. The best-case location accuracy is 12.5 cm. The accuracy of height estimation is within 8 cm in majority cases. LOCI can easily be extended to recognize activities.

  • 35. Maioli, Andrea
    et al.
    Mottola, Luca
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication.
    Intermittence Anomalies not Considered Harmful2020In: Proceedings of the 8th International Workshop on Energy Harvesting and Energy-Neutral Sensing Systems, 2020Conference paper (Refereed)
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  • 36. Afanasov, Mikhail
    et al.
    Mottola, Luca
    Politecnico di Milano, Italy; RI.SE Sweden.
    The FlyZone Testbed Architecture for Aerial Drone Applications2020In: GetMobile: Mobile Computing and Communications, ISSN 2375-0529, E-ISSN 2375-0537, Vol. 24, no 1Article in journal (Refereed)
    Abstract [en]

    Aerial drones represent a new breed of mobile computing. Compared to mobile phones and connected cars that only opportunistically sense or communicate, aerial drones offer direct control over their movements. They can thus implement functionality that were previously beyond reach, such as collecting high-resolution imagery, exploring near-inaccessible areas, or inspecting remote areas to gather fine-grain environmental data.

  • 37.
    Maioli, Andrea
    et al.
    Politecnico di Milano, Italy.
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Politecnico di Milano, Italy.
    Intermittence Anomalies not Considered Harmful2020In: ENSsys 2020 - Proceedings of the 8th International Workshop on Energy Harvesting and Energy-Neutral Sensing Systems16 November 2020, Pages 1-78th International Workshop on Energy Harvesting and Energy-Neutral Sensing Systems, ENSsys 2020, co-located with ACM SenSys 2020; Virtual, Online; Japan; 16 November 2020 through, Association for Computing Machinery, Inc , 2020Conference paper (Refereed)
    Abstract [en]

    We consider a new perspective on intermittence anomalies arising in intermittently-computing mixed-volatile systems. Existing forward progress techniques avoid such anomalies by enforcing a computation that corresponds to a continuous one, introducing a significant overhead. We take a different stand: By allowing the presence of specific anomalies, we make the program aware of intermittence, unlocking new design patterns. We argue about the various possibilities emerging from this and we make the concept concrete by applying it to loops. We show how intermittence anomalies allow to preserve the results of loop iterations across power failures, without requiring to save the device's volatile state after each iteration. Compared to existing checkpoint mechanisms, our technique shows on average a 35.2x lower energy consumption and a 48.4x lower execution time across several staple benchmarks. 

  • 38.
    Ahmed, Saad
    et al.
    Lahore University of Management Sciences, Pakistan.
    Nawaz, Muhammad
    Lahore University of Management Sciences, Pakistan.
    Bakar, Abu
    Lahore University of Management Sciences, Pakistan.
    Bhatti, Naveed Anwar
    Air University, Pakistan.
    Alizai, Muhammad Hamad
    Lahore University of Management Sciences, Pakistan.
    Siddiqui, Junaid Haroon
    Lahore University of Management Sciences, Pakistan.
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Politecnico di Milano, Italy.
    Demystifying Energy Consumption Dynamics in Transiently Powered Computers2020In: ACM Transactions on Embedded Computing Systems, ISSN 1539-9087, E-ISSN 1558-3465, Vol. 19, no 6, article id 47Article in journal (Refereed)
    Abstract [en]

    Transiently powered computers (TPCs) form the foundation of the battery-less Internet of Things, using energy harvesting and small capacitors to power their operation. This kind of power supply is characterized by extreme variations in supply voltage, as capacitors charge when harvesting energy and discharge when computing. We experimentally find that these variations cause marked fluctuations in clock speed and power consumption. Such a deceptively minor observation is overlooked in existing literature. Systems are thus designed and parameterized in overly conservative ways, missing on a number of optimizations.We rather demonstrate that it is possible to accurately model and concretely capitalize on these fluctuations. We derive an energy model as a function of supply voltage and prove its use in two settings. First, we develop EPIC, a compile-time energy analysis tool. We use it to substitute for the constant power assumption in existing analysis techniques, giving programmers accurate information on worst-case energy consumption of programs. When using EPIC with existing TPC system support, run-time energy efficiency drastically improves, eventually leading up to a 350% speedup in the time to complete a fixed workload. Further, when using EPIC with existing debugging tools, it avoids unnecessary program changes that hurt energy efficiency. Next, we extend the MSPsim emulator and explore its use in parameterizing a different TPC system support. The improvements in energy efficiency yield up to more than 1000% time speedup to complete a fixed workload.

  • 39.
    Ahmed, Saad
    et al.
    Lahore University of Management Science, Pakistan.
    Bhatti, Naveed
    Air University, Pakistan.
    Alizai, Hamad
    Lahore University of Management Science, Pakistan.
    Siddiqui, Junaid
    Lahore University of Management Science, Pakistan.
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Politecnico di Milano, Italy.
    Fast and Energy-Efficient State Checkpointing for Intermittent Computing2020In: ACM Transactions on Embedded Computing Systems, ISSN 1539-9087, E-ISSN 1558-3465, Vol. 19, no 6, article id 45Article in journal (Refereed)
    Abstract [en]

    Intermittently powered embedded devices ensure forward progress of programs through state checkpointing in non-volatile memory. Checkpointing is, however, expensive in energy and adds to the execution times. To minimize this overhead, we present DICE, a system that renders differential checkpointing profitable on these devices. DICE is unique because it is a software-only technique and efficient because it only operates in volatile main memory to evaluate the differential. DICE may be integrated with reactive (Hibernus) or proactive (MementOS, HarvOS) checkpointing systems, and arbitrary code can be enabled with DICE using automatic code-instrumentation requiring no additional programmer effort. By reducing the cost of checkpoints, DICE cuts the peak energy demand of these devices, allowing operation with energy buffers that are one-eighth of the size originally required, thus leading to benefits such as smaller device footprints and faster recharging to operational voltage level. The impact on final performance is striking: with DICE, Hibernus requires one order of magnitude fewer checkpoints and one order of magnitude shorter time to complete a workload in real-world settings.

  • 40.
    Narayana, S.
    et al.
    TU Delft, Netherlands.
    Rao, V.
    TU Delft, Netherlands.
    Prasad, R. V.
    TU Delft, Netherlands.
    Kanthila, A. K.
    TU Delft, Netherlands.
    Managundi, K.
    TU Delft, Netherlands.
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science.
    Prabhakar, T. V.
    IISc,India.
    LOCI: privacy-aware, device-free, low-power localization of multiple persons using IR sensors2020In: Proceedings - 2020 19th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2020, Institute of Electrical and Electronics Engineers Inc. , 2020, p. 121-132Conference paper (Refereed)
    Abstract [en]

    High accuracy and device-free indoor localization is still a holy grail to enable smart environments. With the growing privacy concerns and regulations, it is necessary to develop methods and systems that can be low-power, device-free as well as privacy-aware. While IR-based solutions fit the bill, they require many modules to be installed in the area of interest for higher accuracy, or proper planning during installation, or they may not work if the background has multiple heat-emitting objects, etc. In this paper, we propose a custom-built miniature device called LOCI that uses IR sensing. One unit of LOCI can provide three-dimensional localization at best. LOCI uses only a thermopile and a PIR sensor built within a 5x5x2 cm3 module. Since IR-based sensing is used, LOCI consumes around 80 mW. LOCI uses analog waveform from the PIR sensor with the gain of the PIR sensor dynamically controlled through software in real-time to simulate spatial diversity. LOCI proposes low-complexity techniques with sensor fusion to eliminate the noise in the background, which has not been handled in previous works even with sophisticated signal processing techniques. Since LOCI uses raw data from the thermopile, the computations are power-efficient. We present the complete design of LOCI and the proposed methodology to estimate height and location. LOCI achieves accuracies of sub-22 cm with a confidence of 0.5 and sub-35 cm with a confidence of 0.8. The best-case location accuracy is 12.5 cm. The accuracy of height estimation is within 8 cm in majority cases. LOCI can easily be extended to recognize activities. 

  • 41.
    Afanasov, Mikhail
    et al.
    Politecnico di Milano, Italy; Credit Suisse, Poland.
    Bhatti, Naveed
    Politecnico di Milano, Italy; Air University, Pakistan.
    Campagna, Dennis
    Politecnico di Milano, Italy.
    Caslini, Giacomo
    Politecnico di Milano, Italy.
    Centonze, Fabio
    Politecnico di Milano, Italy.
    Dolui, Koustabh
    Politecnico di Milano, Italy; Ku Leuven, Belgium.
    Maioli, Andrea
    Politecnico di Milano, Italy.
    Barone, Erica
    Microsoft, Italy.
    Alizai, Mohammad
    Lums, Pakistan.
    Siddiqui, Junaid
    Lums, Pakistan.
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Politecnico di Milano, Italy.
    Battery-less zero-maintenance embedded sensing at the mithræum of circus maximus2020In: SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems, Association for Computing Machinery, Inc , 2020, p. 368-381Conference paper (Refereed)
    Abstract [en]

    We present the design and evaluation of a 3.5-year embedded sensing deployment at the Mithræum of Circus Maximus, a UNESCO-protected underground archaeological site in Rome (Italy). Unique to our work is the use of energy harvesting through thermal and kinetic energy sources. The extreme scarcity and erratic availability of energy, however, pose great challenges in system software, embedded hardware, and energy management. We tackle them by testing, for the first time in a multi-year deployment, existing solutions in intermittent computing, low-power hardware, and energy harvesting. Through three major design iterations, we find that these solutions operate as isolated silos and lack integration into a complete system, performing suboptimally. In contrast, we demonstrate the efficient performance of a hardware/software co-design featuring accurate energy management and capturing the coupling between energy sources and sensed quantities. Installing a battery-operated system alongside also allows us to perform a comparative study of energy harvesting in a demanding setting. Albeit the latter reduces energy availability and thus lowers the data yield to about 22% of that provided by batteries, our system provides a comparable level of insight into environmental conditions and structural health of the site. Further, unlike existing energy-harvesting deployments that are limited to a few months of operation in the best cases, our system runs with zero maintenance since almost 2 years, including 3 months of site inaccessibility due to a COVID19 lockdown

  • 42.
    Asad, H. A.
    et al.
    Uppsala University, Sweden.
    Wouters, E. H.
    KTH Royal Institute of Technology, Sweden.
    Bhatti, N. A.
    Air University, Pakistan.
    Mottola, Luca
    RISE Research Institutes of Sweden, Digital Systems, Data Science.
    Voigt, Thiemo
    RISE Research Institutes of Sweden, Digital Systems, Data Science. Uppsala University, Sweden.
    On Securing Persistent State in Intermittent Computing2020In: ENSsys 2020 - Proceedings of the 8th International Workshop on Energy Harvesting and Energy-Neutral Sensing Systems16 November 2020, Pages 8-148th International Workshop on Energy Harvesting and Energy-Neutral Sensing Systems, ENSsys 2020, co-located with ACM SenSys 2020; Virtual, Online; Japan; 16 November 2020 throug, Association for Computing Machinery, Inc , 2020, p. 8-14Conference paper (Refereed)
    Abstract [en]

    We present the experimental evaluation of different security mechanisms applied to persistent state in intermittent computing. Whenever executions become intermittent because of energy scarcity, systems employ persistent state on non-volatile memories (NVMs) to ensure forward progress of applications. Persistent state spans operating system and network stack, as well as applications. While a device is off recharging energy buffers, persistent state on NVMs may be subject to security threats such as stealing sensitive information or tampering with configuration data, which may ultimately corrupt the device state and render the system unusable. Based on modern platforms of the Cortex M*series, we experimentally investigate the impact on typical intermittent computing workloads of different means to protect persistent state, including software and hardware implementations of staple encryption algorithms and the use of ARM TrustZone protection mechanisms. Our results indicate that i) software implementations bear a significant overhead in energy and time, sometimes harming forward progress, but also retaining the advantage of modularity and easier updates; ii) hardware implementations offer much lower overhead compared to their software counterparts, but require a deeper understanding of their internals to gauge their applicability in given application scenarios; and iii) TrustZone shows almost negligible overhead, yet it requires a different memory management and is only effective as long as attackers cannot directly access the NVMs

  • 43.
    Mottola, Luca
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. RISE Swedish Institute of Computer Science, Kista SE164 29, Sweden;Politecnico di Milano, Milano 20133, Italy.
    Picco, Gian Pietro
    University of Trento, Trento 38122, Italy.
    Oppermann, Felix
    Graz University of Technology, Ultimo, NSW 2007, Australia.
    Eriksson, Joakim
    RISE Swedish Institute of Computer Science, Kista SE164 29, Sweden SICS.
    Finne, Niclas
    RISE Swedish Institute of Computer Science, Kista SE164 29, Sweden SICS.
    Fuchs, Harald
    SAP, Walldorf, 69190, Germany.
    Gaglione, Andrea
    University of Trento, Trento 38122, Italy.
    Karnouskos, Stamatis
    SAP, Walldorf, 69190, Germany.
    Montero, Patricio
    Acciona Infraestructuras S.A. Alcobendas, Madrid 28108, Spain.
    Oertel, Nina
    SAP, Walldorf, 69190, Germany.
    Römer, Kay
    Graz University of Technology, Ultimo, NSW 2007, Australia.
    Spiess, Patrik
    SAP, Walldorf, 69190, Germany.
    Tranquillini, Stefano
    University of Trento, Trento 38122, Italy.
    Voigt, Thiemo
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. RISE Swedish Institute of Computer Science, Kista, SE-164 29, Sweden.
    makeSense: Simplifying the Integration of Wireless Sensor Networks into Business Processes2019In: IEEE Transactions on Software Engineering, ISSN 0098-5589, E-ISSN 1939-3520, Vol. 45, no 6, p. 576-596Article in journal (Refereed)
    Abstract [en]

    A wide gap exists between the state of the art in developing Wireless Sensor Network (WSN) software and current practices concerning the design, execution, and maintenance of business processes. WSN software is most often developed based on low-level OS abstractions, whereas business process development leverages high-level languages and tools. This state of affairs places WSNs at the fringe of industry. The makeSense system addresses this problem by simplifying the integration of WSNs into business processes. Developers use BPMN models extended with WSN-specific constructs to specify the application behavior across both traditional business process execution environments and the WSN itself, which is to be equipped with application-specific software. We compile these models into a high-level intermediate language—also directly usable by WSN developers—and then into OS-specific deployment-ready binaries. Key to this process is the notion of meta-abstraction, which we define to capture fundamental patterns of interaction with and within the WSN. The concrete realization of meta-abstractions is application-specific; developers tailor the system configuration by selecting concrete abstractions out of the existing codebase or by providing their own. Our evaluation of makeSense shows that i) users perceive our approach as a significant advance over the state of the art, providing evidence of the increased developer productivity when using makeSense; ii) in large-scale simulations, our prototype exhibits an acceptable system overhead and good scaling properties, demonstrating the general applicability of makeSense; and, iii) our prototype—including the complete tool-chain and underlying system support—sustains a real-world deployment where estimates by domain specialists indicate the potential for drastic reductions in the total cost of ownership compared to wired and conventional WSN-based solutions.

  • 44. Ahmed, Saad
    et al.
    Bhatti, Naveed Anwar
    Alizai, Muhammad Hamad
    Siddiqui, Junaid
    Mottola, Luca
    Politecnico di Milano, Italy; RI.SE SICS Swedish.
    Efficient Intermittent Computing with Differential Checkpointing2019In: LCTES 2019 Proceedings of the 20th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems, 2019, p. 70-81Conference paper (Refereed)
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    fulltext
  • 45. Maioli, Andrea
    et al.
    Mottola, Luca
    Politecnico di Milano, Italy; RI.SE SICS, Sweden.
    Alizai, Muhammad Hamad
    Siddiqui, Junaid Haroon
    On Intermittence Bugs in the Battery-less Internet of Things2019In: LCTES 2019 Proceedings of the 20th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems, 2019, p. 203-207Conference paper (Refereed)
    Download full text (pdf)
    fulltext
  • 46. Branco, Adriano
    et al.
    Mottola, Luca
    RI.Se SICS Sweden.
    Alizai, Hamad
    Haroon Siddiqui, Junaid
    Intermittent Intermittent Asynchronous Peripheral Operations2019In: SenSys ´19 Proceedings of the 17th ACM International Conference on Embedded Networked Sensor Systems (SENSYS), 2019Conference paper (Refereed)
    Download full text (pdf)
    fulltext
  • 47. Ahmed, Saad
    et al.
    Bhakar, Abu
    Bhatti, Naveed Anwar
    Alizai, Muhammad Hamad
    Siddiqui, Junaid Haroon
    Mottola, Luca
    Politecnico di Milano, Italy; RI.SE SICS Sweden.
    The Betrayal of Constant Power × Time: Finding the Missing Joules of Transiently-powered Computers2019In: Proceedings of the 20th ACMSIGPLAN/SIGBED Conference on Languages, Compilers, and Toolsfor Embedded Systems (LCTES ’19), 2019Conference paper (Refereed)
    Download full text (pdf)
    fulltext
  • 48. Afanasov, Mikhail
    et al.
    Djordjevic, Alessandro
    Liu, Feng
    Mottola, Luca
    Politecnico di Milano, Italy; RI.Se SICS Sweden.
    FlyZone: A Testbed for Experimenting with Aerial Drone Applications2019In: MobiSys '19 Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services, 2019, p. 67-78Conference paper (Refereed)
    Download full text (pdf)
    fulltext
  • 49.
    Afanasov, M.
    et al.
    Politecnico di Milano, Italy; Credit Suisse, Poland.
    Djordjevic, A.
    Politecnico di Milano, Italy.
    Lui, F.
    Politecnico di Milano, Italy.
    Mottola, Luca
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS. Politecnico di Milano, Italy.
    Flyzone: A testbed for experimenting with aerial drone applications2019In: MobiSys 2019 - Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services, Association for Computing Machinery, Inc , 2019, p. 67-78Conference paper (Refereed)
    Abstract [en]

    FlyZone is a testbed architecture to experiment with aerial drone applications. Unlike most existing drone testbeds that focus on low-level mechanical control, FlyZone offers a high-level API and features geared towards experimenting with application-level functionality. These include the emulation of environment influences, such as wind, and the automatic monitoring of developer-provided safety constraints, for example, to mimic obstacles. We conceive novel solutions to achieve this functionality, including a hardware/software architecture that maximizes decoupling from the main application and a custom visual localization technique expressly designed for testbed operation. We deploy two instances of FlyZone and study performance and effectiveness. We demonstrate that we realistically emulate the environment influence with a positioning error bound by the size of the smallest drone we test, that our localization technique provides a root mean square error of 9.2cm, and that detection of violations to safety constraints happens with a 50ms worst-case latency. We also report on how FlyZone supported developing three real-world drone applications, and discuss a user study demonstrating the benefits of FlyZone compared to drone simulators. 

  • 50.
    Maioli, A.
    et al.
    Politecnico di Milano, Italy.
    Alizai, M. H.
    LUMS, Pakistan.
    Mottola, Luca
    RISE - Research Institutes of Sweden, ICT, SICS. Politecnico di Milano, Italy.
    Siddiqui, J. H.
    LUMS, Pakistan.
    On intermittence bugs in the battery-less internet of things (WIP paper)2019In: Proceedings of the ACM SIGPLAN Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES), Association for Computing Machinery , 2019, p. 203-207Conference paper (Refereed)
    Abstract [en]

    The resource-constrained devices of the battery-less Internet of Things are powered off energy harvesting and compute intermittently, as energy is available. Forward progress of programs is ensured by creating persistent state. Mixed-volatile platforms are thus an asset, as they map slices of the address space onto non-volatile memory. However, these platforms also possibly introduce intermittence bugs, where intermittent and continuous executions differ. Our ongoing work on intermittence bugs includes (i) an analysis that demonstrates their presence in settings that current literature overlooks; (ii) the design of efficient testing techniques to check their presence in arbitrary code, which would be otherwise prohibitive given the sheer number of different executions to check; (iii) the implementation of an offline tool called ScEpTIC that implements these techniques. ScEpTIC finds the same bugs as a brute-force approach, but is six orders of magnitude faster. © 2019 Copyright held by the owner/author(s).

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