2017
[7]
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%.
[6]
A. Elsts, X. Fafoutis, J. Pope, G. Oikonomou, R. Piechocki, I. Craddock, "Scheduling high-rate unpredictable traffic in IEEE 802.15.4 TSCH networks", in Proc. IEEE DCOSS 2017, 2017 (accepted, to appear)
The upcoming Internet of Things (IoT) applications include real-time human activity monitoring with wearable sensors. Compared to the traditional environmental sensing with low-power wireless nodes, these new applications generate a constant stream of a much higher rate. Nevertheless, the wearable devices remain battery powered and therefore restricted to low-power wireless standards such as IEEE 802.15.4 or Bluetooth Low Energy (BLE). Our work tackles the problem of building a reliable autonomous schedule for forwarding this kind of dynamic data in IEEE 802.15.4 TSCH networks. Due to the a priori unpredictability of these data source locations, the quality of the wireless links, and the routing topology of the forwarding network, it is wasteful to reserve the number of slots required for the worst-case scenario; under conditions of high expected datarate, it is downright impossible. The solution we propose is a hybrid approach where dedicated TSCH cells and shared TSCH slots coexist in the same schedule. We show that under realistic assumptions of wireless link diversity, adding shared slots to a TSCH schedule increases the overall packet delivery rate and the fairness of the system.
[5]
S. Duquennoy, A. Elsts, B. Nahas, G. Oikonomou, "TSCH and 6TiSCH for Contiki: challenges, design and evaluation", in Proc. IEEE DCOSS 2017, 2017 (accepted, to appear)
Synchronized communication has recently emerged as a prime option for low-power critical applications. Solutions such as Glossy or Time Slotted Channel Hopping (TSCH) have demonstrated end-to-end reliability upwards of 99.99%. In this context, the IETF Working Group 6TiSCH is currently standardizing the mechanisms to use TSCH in low-power IPv6 scenarios. This paper identifies a number of challenges when it comes to implementing the 6TiSCH stack. It shows how these challenges can be addressed with practical solutions for locking, queuing, scheduling and other aspects. With this implementation as an enabler, we present an experimental validation and comparison with state-of-the-art MAC protocols. We conduct fine-grained energy profiling, showing the impact of link-layer security on packet transmission. We evaluate distributed time synchronization in a 340-node testbed, and demonstrate that tight synchronization (hundreds of microseconds) can be achieved at very low cost (0.3% duty cycle, 0.008% channel utilization). We finally compare TSCH against traditional MAC layers: low-power listening (LPL) and CSMA, in terms of reliability, latency and energy. We show that with proper scheduling, TSCH achieves by far the highest reliability, and outperforms LPL in both energy and latency.
[4]
A. Elsts, G. Oikonomou, X. Fafoutis, R. Piechocki, "Internet of things for smart homes: lessons learned from the SPHERE case study", in Proc. Global Internet of Things Summit, 2017 (accepted, to appear)
Building large-scale low-power Internet of Things (IoT) systems remains a challenge, as these systems have to meet the requirements of reliability, robustness, and energy- efficiency while running on resource-restricted microcontrollers without memory protection. In this paper we present the case study of IoT in SPHERE (Sensor Platform for HEalthcare in a Residential Environment), a project with the objective to develop a multipurpose, multi-modal sensor platform for monitoring people’s health inside their homes. Atypically for academic projects, in 2017 the SPHERE software is going to be deployed in a 100-home study in volunteer homes, therefore it has to satisfy many real-world requirements. We discuss the requirements for IoT networking in this project, the IoT architecture (built on top of Contiki OS), software engineering challenges and lessons learned, as well as some of the general aspects that still make embedded low-power IoT software development difficult.
[3]
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.
[2]
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.
[1]
P. Cooper, K. Maraslis, T. Tryfonas, G. Oikonomou, "An intelligent hot-desking model harnessing the power of occupancy sensing", Journal of Facilities, Emerald Group Publishing Limited, 2017 (in press)
In this paper a model is developed to harness the power of occupancy sensing in an Intelligent Hot-Desking system utilizing experimental data from a commercial office in central London. To achieve that, the model uses that data as an input in order to undertake the task of allocating the office desks to the employees in a way that will maximise their productivity based on the type of project that each employee is working on each time. In this way, and by taking into account other parameters that are involved as well, the synergy that this situation can create, can increase productivity significantly compared to the situation where employees have their desks fixed under any circumstances and also allow for expenses cut since the desks can now be less than the employees. Not only is this approach able to optimize desk utilization based on quality occupancy data, but also speculates how and by how much overall productivity increases, while proving that its benefits outweigh the costs of adopting such a system. Furthermore, this paper explores the barriers towards Intelligent Hot-Desking, including how an increase in occupancy data collection in the private sector could have key advantages for the business as an organization and the city as a whole. Ultimately, it provides a valuable and feasible use case for the use of occupancy data in smart buildings, a dataset that is perceived to be valuable yet underexplored.
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