2017
[7]
P. Woznowski, A. Burrows, T. Diethe, X. Fafoutis, J. Hall, S. Hannuna, M. Camplani, N. Twomey, M. Kozlowski, B. Tan, N. Zhu, A. Elsts, A. Vafeas, A. Paiement, L. Tao, M. Mirmehdi, T. Burghardt, D. Damen, P. Flach, R. Piechocki, I. Craddock, G. Oikonomou, "SPHERE: A sensor platform for healthcare in a residential environment", in Designing, Developing, and Facilitating Smart Cities, Springer, pp. 315-333, 2017
It can be tempting to think about smart homes like one thinks about smart cities. On the surface, smart homes and smart cities comprise coherent systems enabled by similar sensing and interactive technologies. It can also be argued that both are broadly underpinned by shared goals of sustainable development, inclusive user engagement and improved service delivery. However, the home possesses unique characteristics that must be considered in order to develop effective smart home systems that are adopted in the real world.
[6]
X. Fafoutis, A. Elsts, A. Vafeas, G. Oikonomou, R. Piechocki, "Demo: SPES-2 – A Sensing Platform for Maintenance-Free Residential Monitoring", in Proc. EWSN 2017, 2017 (accepted, to appear)
SPES-2 is a sensing board for room-level monitoring in a home environment. It constitutes a vital modality of the SPHERE architecture: a multi-modal sensing platform for healthcare in a residential environment. SPES-2 uses an optimised implementation of the IEEE 802.15.4-2015 TSCH (Time-Slotted Channel Hopping) standard to operate efficiently and reliably in unknown environments for more than one year without battery replacement, providing continuous information about the ambient characteristics of the room (such as temperature, humidity and light levels), as well as presence information captured through a motion sensor.
2016
[5]
A. Elsts, S. Duquennoy, X. Fafoutis, G. Oikonomou, R. Piechocki, I. Craddock, "Microsecond-Accuracy Time Synchronization Using the IEEE 802.15.4 TSCH Protocol", in Proc. International Workshop on Practical Issues in Building Sensor Network Applications (IEEE SenseApp 2016), 2016
Time-Slotted Channel Hopping from the IEEE 802.15.4-2015 standard requires that network nodes are tightly time-synchronized. Existing implementations of TSCH on embedded hardware are characterized by tens-of-microseconds large synchronization errors; higher synchronization accuracy would enable reduction of idle listening time on receivers, in this way decreasing the energy required to run TSCH. For some applications, it would also allow to replace dedicated time synchronization mechanisms with TSCH. We show that time synchronization errors in the existing TSCH implementations on embedded hardware are caused primarily by imprecise clock drift estimations, rather than by real unpredictable drift variance. By estimating clock drift more precisely and by applying adaptive time compensation on each node in the network, we achieve microsecond accuracy time synchronization on point-to-point links and a <2 microsecond end-to-end error in a 7-node line topology. Our solution is implemented in the Contiki operating system and tested on Texas Instruments CC2650-based nodes, equipped with common off-the-shelf hardware clock sources (20 ppm drift). Our implementation uses only standard TSCH control messages and is able to keep radio duty cycle below 1\%.
[4]
G. Papadopoulos, A. Mavromatis, X. Fafoutis, N. Montavont, R. Piechocki, T. Tryfonas, G. Oikonomou, "Guard Time Optimisation and Adaptation for Energy Efficient Multi-hop TSCH Networks", in Proc. IEEE World Forum on Internet of Things (WF-IoT), 2016
In the IEEE 802.15.4-2015 standard, Time Slotted Channel Hopping (TSCH) aims to guarantee high-level network reliability by keeping nodes time-synchronised. In order to ensure successful communication between a sender and a receiver, the latter starts listening shortly before the expected time of a MAC layer frame’s arrival. The offset between the time a node starts listening and the estimated time of frame arrival is called guard time and it aims to reduce the probability of missed frames due to clock drift. In this paper, we investigate the impact of the guard time on network performance. We identify that, when using the 6tisch minimal schedule, the most significant cause of energy consumption is idle listening during guard time. Therefore, we first perform mathematical modelling on a TSCH link to identify the guard time that maximises the energy-efficiency of the TSCH network in single hop topology. We then continue in multi-hop network, where we empirically adapt the guard time locally at each node depending its distance, in terms of hops, from the sink. Our performance evaluation results, conducted using the Contiki OS, demonstrate that the proposed decentralised guard time adaptation can reduce the energy consumption by up to 40\%, without compromising network reliability.
[3]
G. Papadopoulos, A. Mavromatis, X. Fafoutis, R. Piechocki, T. Tryfonas, G. Oikonomou, "Guard Time Optimisation for Energy Efficiency in IEEE 802.15.4-2015 TSCH Links", in 2nd EAI International Conference on Interoperability in IoT, 2016
Time Slotted Channel Hopping (TSCH) is among the Medium Access Control (MAC) schemes defined in the IEEE 802.15.4-2015 standard. TSCH aims to guarantee high-level network reliability by keeping nodes time-synchronised. In order to ensure successful communication between a sender and a receiver, the latter starts listening shortly before the expected time of a MAC layer frame’s arrival. The offset between the time a node starts listening and the estimated time of frame arrival is called guard time and it aims to reduce the probability of missed frames due to clock drift. In this paper, we investigate the impact of the guard time length on network performance. We identify that, when using the 6TiSCH minimal schedule, the most significant cause of energy consumption is idle listening during guard time. Therefore, we perform empirical optimisations on the guard time to maximise the energy-efficiency of a TSCH link. Our experiments, conducted using the Contiki OS, show that optimal guard time configuration can reduce energy consumption by up to 40\%, without compromising network reliability.
[2]
G. Margelis, X. Fafoutis, R. Piechocki, G. Oikonomou, T. Tryfonas, P. Thomas, "Practical Limits of the Secret Key-Capacity for IoT Physical Layer Security", in Proc. IEEE World Forum on Internet of Things (WF-IoT), 2016
The confidentiality of communications in the Internet of Things (IoT) is critical, with cryptography being currently the most widely employed method to achieve it. Establishing cryptographically secure communication links between two transceivers requires the pre-agreement on some key, unknown to an external attacker. In recent years there has been growing interest for techniques that generate a shared random key through observation of the channel and its effects on the exchanged messages. The maximum length of that key is characterised by the Mutual Information (MI) between the observations of the two radios. In this work we examine the practical limits of the MI of off-the-shelf transceivers communicating through the IEEE 802.15.4 specification in an indoor office environment, and calculate the secret-key capacity, that is, the maximum length of an extracted secret-key in the presence of an eavesdropper. Furthermore, we study how using groups of observations can affect the MI and both analytically and experimentally prove that grouping observations leads to better results and an increased key-capacity.
[1]
X. Fafoutis, L. Marchegiani, G. Papadopoulos, R. Piechocki, T. Tryfonas, G. Oikonomou, "Privacy Leakage of Physical Activity Levels in Wireless Embedded Wearable Systems", Signal Processing Letters, IEEE, 24(2), pp. 136-140, 2016
With the ubiquity of sensing technologies in our personal spaces, the protection of our privacy and the confidentiality of sensitive data becomes a major concern. In this paper, we focus on wearable embedded systems that communicate data periodically over the wireless medium. In this context, we demonstrate that private information about the physical activity levels of the wearer can leak to an eavesdropper through the physical layer. Indeed, we show that the physical activity levels strongly correlate with changes in the wireless channel that can be captured by measuring the signal strength of the eavesdropped frames. We practically validate this correlation in several scenarios in a real residential environment, using data collected by our prototype wearable accelerometer-based sensor. Lastly, we propose a privacy enhancement algorithm that
mitigates the leakage of this private information.
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