Low-power wireless IoT networks have traditionally operated over a single physical layer (PHY) - many based on the IEEE 802.15.4 standard. However, recent low-power wireless chipsets offer both the IEEE 802.15.4 and all four PHYs of the Bluetooth 5 (BT 5) standard. This introduces the intriguing possibility that IoT solutions might not necessarily be bound by the limits of a single PHY, and could actively or proactively adapt their PHY depending on RF or networking conditions (e.g., to offer a higher throughput or a longer radio range). Several recent studies have explored such use-cases. However, these studies lack comprehensive evaluation over various metrics (such as reliability, latency, and energy) with regards to scalability and the Radio Frequency (RF) environment. In this work we evaluate the performance of IEEE 802.15.4 and the four BT 5 2.4GHz PHY options for the recently completed IETF 6TiSCH low-power wireless standard. To the best of our knowledge, this is the first work to directly compare these PHYs in identical settings. Specifically, we use a recently released 6TiSCH simulator, TSCH-Sim, to compare these PHY options in networks of up to 250 nodes over different RF environments (home, industrial, and outdoor), and highlight from these results how different PHY options might be better suited to particular application use-cases.

The emerging Internet of Things has the potential to solve major societal challenges associated with healthcare provision. Low-power wireless protocols for residential Health Internet of Things applications are characterized by high reliability requirements, the need for energy-efficient operation, and the need to operate robustly in diverse environments in the presence of external interference. We enhance and experimentally evaluate the Time-Slotted Channel Hopping protocol from the IEEE 802.15.4 standard to address these challenges. Our contributions are a new schedule and an adaptive channel selection mechanism to increase the performance of time-slotted channel hopping in this domain. Evaluation in a test house shows that the enhanced system is suitable for our e-Health application and compares favorably with state-of-the-art options. The schedule provides higher reliability compared with the minimal scheduling function from the IETF 6TiSCH Working Group and has a better energy-efficiency/reliability tradeoff than the Orchestra scheduler. Results from 29 long-term residential deployments confirm the suitability for the application and show that the system is able to adapt and avoid channels used by WiFi. In these uncontrolled environments, the system achieves 99.96% average reliability for networks that generate 7.5 packets per second on average.

We are interested in hot and cold water flow detection in domestic kitchen and bathroom taps for smart home environments. Water flow monitoring is particularly valuable for long-term behavioural monitoring systems for health-related applications, as it enables the collection of long-term data on the hydration levels of the house residents, and it is associated with several activities of daily life, such as cooking and cleaning. This paper presents a water flow sensing device that is based on sensing the vibrations on the pipe when water is flowing through them. The proposed solution is noninvasive and energy efficient, as it does not require cutting the water pipes or altering the plumbing system, and consumes less then 2 uA in continuous operation. The proposed water flow sensor has been integrated to SPHERE, a sensing platform of non-medical sensors for healthcare monitoring and behavioural analytics in a home environment, and deployed to more than 15 residential properties.

Networks deployed in real-world conditions have to cope with dynamic, unpredictable environmental temperature changes. These changes affect the clock rate on network nodes, and can cause faster clock de-synchronization compared to situations where devices are operating under stable temperature conditions. Wireless network protocols, such as time-slotted channel hopping (TSCH) from the IEEE 802.15.4-2015 standard, are affected by this problem, since they require tight clock synchronization among all nodes for the network to remain operational. This paper proposes a method for autonomously compensating temperature-dependent clock rate changes. After a calibration stage, nodes continuously perform temperature measurements to compensate for clock drifts at runtime. The method is implemented on low-power Internet of Things (IoT) nodes and evaluated through experiments in a temperature chamber, indoor and outdoor environments, as well as with numerical simulations. The results show that applying the method reduces the maximum synchronization error more than ten times. In this way, the method allows reduction in the total energy spent for time synchronization, which is practically relevant concern for low data rate, low energy budget TSCH networks, especially those exposed to environments with changing temperature.

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.

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.

MOTIVATION: Due to their universal applicability, global stochastic optimization methods are popular for designing improvements of biochemical networks. The drawbacks of global stochastic optimization methods are: (i) no guarantee of finding global optima, (ii) no clear optimization run termination criteria and (iii) no criteria to detect stagnation of an optimization run. The impact of these drawbacks can be partly compensated by manual work that becomes inefficient when the solution space is large due to combinatorial explosion of adjustable parameters or for other reasons. RESULTS: SpaceScanner uses parallel optimization runs for automatic termination of optimization tasks in case of consensus and consecutively applies a pre-defined set of global stochastic optimization methods in case of stagnation in the currently used method. Automatic scan of adjustable parameter combination subsets for best objective function values is possible with a summary file of ranked solutions. AVAILABILITY AND IMPLEMENTATION: https://github.com/atiselsts/spacescanner . CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The IEEE 802.15.4-2015 standard defines a number of Medium Access Control (MAC) layer protocols for low-power wireless communications in the IoT. Originally defined in the IEEE 802.15.4e amendment, TSCH (Time Slotted Channel Hopping) is among the proposed mechanisms. TSCH is a scheme aiming to guarantee network reliability by keeping nodes time-synchronised at the MAC layer. 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 poster, we investigate the effect of the guard time duration on energy consumption. We identify that, when using the 6tisch minimal schedule, the most significant cause of energy consumption is idle listening during guard time. Therefore, the energy-efficiency of TSCH can be significantly improved by guard time optimisation. Our performance evaluation results, conducted using the Contiki operating system, show that an efficient configuration of guard time may reduce energy consumption by up to 30%, without compromising network reliability.

Task Graph (ATaG) is a sensor network application development paradigm where the application is visually described by a graph where the nodes correspond to application-level tasks and edges correspond to data flows. We extend ATaG with the option to add non-functional requirements: constraints on end-to-end delay and packet delivery rate. Setting up these constraints at the design phase naturally leads to enabling run-time assurance at the deployment phase, when the conditions of the constraints are used as network's performance goals. We provide both run-time middleware that checks the conditions of these constraints and a central management unit that dynamically adapts the system by doing task reallocation and putting task copies on redundant nodes. Through extensive simulations we show that the system is efficient enough to enable adaptations within tens of seconds even in large networks.

Often software for wireless sensor networks (WSNs) is developed using a specific event based operating system (OS) such as TinyOS. However, this requires steep learning curve for the new developers. Other operating systems for embedded devices have limited support for new hardware platforms. Our goal is to provide an operating system for resource constrained devices that is easy to use for the wide range of researchers and developers familiar with C programming language and Unix operating system concepts. In addition, we provide a framework for agile portability to new hardware platforms, due to the nature of WSN systems that require specific hardware or features for the sensing tasks at hand. We propose Multiple agent netted sensor Operating System (MansOS), that demonstrates ability to execute the same application on different platforms including x86 CPU based computers for easy simulation and debugging of a single node or a whole network. The new platforms are easily added to MansOS thanks to the well defined abstraction layers. MansOS is being successfully used in real world applications, such as wild animal tracking and environmental monitoring in a fruit care research garden. It has also been used in academic environment for teaching wireless sensor networks.