NOR flash memory is widely used as storage in embedded systems as it offers dense non-volatile memory up to the gigabit range while being more reliable than NAND flash. To avoid the cost of a standalone flash controller in such small systems, specialized flash file systems are used to handle the limited write endurance and asymmetric program/erase characteristics. While many NOR file systems exist and are extensively deployed, there is a lack of systematic comparisons of their performance. In this paper, we present vflashsim, a simulator for capturing interactions between file systems and flash memory and for running representative benchmarks. Unlike evaluations on physical hardware, our simulation-based approach avoids prohibitively long erase latencies and cell wear. We implement a NOR flash model and, using vflashsim, evaluate four representative file systems, SPIFFS, LittleFS, YAFFS2, and NF2FS, in terms of write amplification, garbage-collection behavior, and RAM utilization. Our analysis shows how design choices and implementation bugs, such as excessive device scanning, unconditional sector erases, and a lack of garbage collection in allocation paths, cause substantial performance issues. Additionally, we identify how to provoke failure conditions in different file systems, which can result in unrecoverable crashes. Among the evaluated file systems, YAFFS demonstrates the best overall performance and reliability at the cost of high RAM usage, whereas a modified LittleFS remains the best option for more memory-constrained systems. Since performance trade-offs vary by workload and hardware constraints, no single file system is universally optimal. With vflashsim, we provide a tool that enables developers and users of flash file systems to analyze their behavior under diverse configurations and workloads.

Managing the life cycle of an embedded Linux stack is difficult, as we have to integrate in-house and third-party services, prepare firmware images, and update the devices in the field. Further, if device deployment is expensive (e.g. in space), our stack should support multi-mission setups to make the best use of our investment.

In this demo paper the recently started project SatelLight is introduced at an early stage. SatelLight utilizes LiFi (Light Fidelity) as a novel approach for intra-satellite communication. In future, satellite harness (physical connection of the internal components) can be reduced, immune to internal and external EMC interference and possible fully autonomous operation of components can be enabled. In addition to the presentation of the project scope, this demo paper presents a first LiFi-Transceiver prototype, which will be used for reliable data transmission in the further course of the project.

We propose a comprehensive health monitoring of astronauts which is based on Ballistocardiography (BCG). BCG uses high-precision accelerometers to measure the motion of the heart at the body surface. In contrast to conventional methods (e.g. Electrocardiography (ECG)), BCG enables the derivation of heart-related parameters that can otherwise only be recorded by imaging methods such as echocardiography. A huge issue is the signal quality of the acceleration measurement, however, by means of differential arrangement of digital acceleration sensors, the signal quality and also the susceptibility to interference can be reduced when measuring the smallest accelerations. In preparation for a BCG experiment on the International Space Station (ISS), a pre-flight measurement system was developed whose architectural design is similar to the flight hardware, but extended by a reference ECG. To simplify measurement campaigns, the simultaneously recorded BCG and ECG data can be visualized in real time, which will be shown in this demo.

Comprehensive health monitoring is highly relevant for the safety of manned spaced missions. Ballistocardiography (BCG) is a method for providing information of the heart physiology by measuring accelerations on the body surface that are caused by forwarded heart and blood movements in the vascular system. In order to provide a sensor system with a high signal quality, this paper presents differential BCG sensing at the system level for digital accelerometers and its integration into a sensing system. The system is part of a running experiment of the Cosmic Kiss mission on the International Space Station (ISS). Compared to single sensor solutions, the noise power scales down to about 50%, the Signal to Noise Ratio (SNR) is increased by a factor of 1.87 and the BCG signal variability especially improves for diastole area. Furthermore, by exploiting differential sensing techniques, both high reliability is achieved and common mode interference is mitigated, which is of high importance within the scope of space applications. Beside the presentation of the entire wireless sensor system including differential sensing approach, pre-processing unit and Ultra Wideband (UWB) communication module, results of the pre-flight tests show the performance of the system as well as the suitability for targeted mission.

Simulation is a common technique for the evaluation of new approaches and protocols in networked systems and provides many benefits. However, it is also well known that the relevance of the simulation results for real-world applications depends on the various models which are used within the simulation, e.g., for the characteristics of the radio communication. In this paper, we introduce the EMRM, an extension to the ray-tracing radio medium available in Cooja, to improve the modelling of wireless links in simulated WSNs. Our extension allows the simulation of environmental influences onto links on a per node basis, allowing the analysis of various effects observed in experiments in a virtual environment. Furthermore, the packet-based modelling of transmission errors is extended to provide the simulation of bit errors, allowing new usage scenarios, like for instance the simulation of error detection and FEC codes in Cooja.

Wireless Sensor Networks establish the foundation for a revolution in precision agriculture. As an integral part of smart farming systems, they can collect detailed information about crop health, air and soil conditions, and other relevant parameters to support agriculturists in their decision-making. Likewise, decentralized actuation (e.g., opening sprinkler valves) becomes possible when embedded sensor and actuator devices are deployed. From a technical point of view, smart farming systems strongly rely on embedded devices with wireless communication interfaces to cater for their convenient deployment. The operation of their wireless radio transceivers, however, often represents a significant energetic burden. This is particularly conspicuous when compared to the low-power microcontrollers that have become ubiquitous on current-generation sensing systems. We mitigate this issue by following an entirely different approach in this work, namely by exploiting the presence of electric fence energizers that are widely used in farming scenarios. Our solution called PULSEHV modulates data onto the highvoltage electric pulses emitted by fence energizers and thus enables broadcast communications at no extra overhead. As electrical fences commonly encircle entire patches of cropland, they act as large sending antennas; a proximity between deployed sensing devices and this antenna is implicitly ensured thereby. We practically demonstrate how PulseHV accomplishes an effective data rate of 2.7 bit/s through the application of pulse position modulation. This limited throughput is counterbalanced by the fact that receiving the broadcast transmissions incurs virtually no energy overhead.

Since years the amount of medical incidents on passenger flights is increasing. Beside the personal stress and strains for concerned passenger, every incident leads to huge costs for the specific airline. To avoid both, the SCARAB^2 project proposes to monitor passenger's health condition to identify imminent risk of health issues. Therefore, SCARAB^2 faces the challenge of using Ballistocardiography (BCG) in passenger planes and noisy environments respectively. With accelerometer arrays mounted on the seats, cardiac signals of each passenger can be recorded. These data are collected non-invasive while several parameters can be measured, e.g. respiratory rate, heart rate, etc. but even complex parameters like blood pressure can be derived. However, the acceleration of BCG signals is rather small and the shaking and vibrating (noisy) environment of planes leads to strong requirements on hardware, signal processing and meaningful evaluations.

The efficiency and effectiveness of network flooding protocols has recently been shown by many publications as well as real world deployments. One notable protocol is Glossy which combines Concurrent Transmission (CT) with Constructive Interference (CI). A drawback of Glossy is that up to now it has only been implemented and evaluated for one type of radio transceiver. In this paper we first present the Glossy implementation for an AT86RF233 radio transceiver which simplifies the packet forwarding due to a shared receive and transmit buffer. We evaluate our implementation against the original Glossy implementation in a minimalist setup as well as in a real world testbed. However, we observed a noticeable difference in the timing accuracy of the transceiver chips but without adverse effects on the network’s performance. For this reason, in the second part of this paper we provide a deeper investigation by using Software Defined Radios to emulate concurrent transmission for different types of transceivers. This work confirms the general benefit of constructive interference but also shows its limitations. Moreover, we give novel insight into hardware dependability of constructive interference in concurrent transmissions.

Energy is the most limiting factor for remote outdoor deployments of Wireless Sensor Networks (WSNs). This paper proposes a novel routing algorithm for dual-platform nodes targeting WSN applications as found in smart farming applications. For scenarios in which high power components of nodes and radio links will be switched on at known points in time, our algorithm tries to make use of scheduled uptimes of nodes with the possibilities to turn other nodes on to send the nodes' data to a sink on time. We compare our method with a traditional flooding-based algorithm as well as with a greedy version which tries to transfer the data immediately. We show that our mechanism works energy-efficient while meeting all deadlines and keeping the amount of control traffic at a necessary minimum.

We describe a testbed for studying battery discharge behavior and the lifetime of wireless devices under controlled temperature conditions and present preliminary measurement results.

The Ballistocardiography (BCG) aims to analyze the ballistic forces on the heart in terms of vibrations that are transmitted to the body's surface. These vibrations can be measured by accelerometers. But instead of highly specialized analog sensors, we propose BCG based on commercially available digital accelerometers. To achieve this, we performed a bunch of trials to gain information about proper acceleration sensor technology, as well as needed requirements to create a full-fledged BCG sensor board. This sensor board as well as first results are presented within this paper.

The Routing Protocol for Low power and Lossy Networks (RPL) is a wide-spread, flexible routing protocol specifically designed for energy-constrained networks such as Wireless Sensor Networks (WSNs). The resilience of RPL has been verified in several existing evaluations, but how a simple node reset can impact the energy efficiency has not been investigated so far. Thus, in this paper we examine the energy costs of transient node failures in a RPL network. We show that such temporary node failures can have a significant impact on the network's total energy usage. As transient node failures are common in WSNs this work reveals an important weakness of RPL which can even be exploited for attacks.

The fault-tolerant character of WSN protocols and applications that do not assume completely reliable systems legitimize undervolting - a highly efficient energy management technique where the supply voltage is set below the minimum specifications. As has been shown in earlier work, by using thereliable IdealVolting undervolting scheme the lifetime of WSN applications can be increased significantly while keeping the node in a safe state even under rough environmental conditions. To show the usability of undervolting in a real world WSN deployment, we performed a long-term study of IdealVolting in a Smart Farming application. All measurements were performed on a generic outdoor testbed for WSNs (PotatoNet) which is also presented within this paper. We collected a long-term dataset of a WSN running for one farming season on a potato fieldto compare the reliability and performance characteristics of IdealVolting against a regular powered WSN.

This demo paper describes the usability and effectiveness of our distributed energy measurement system for WSNs. The system is composed of several micro-controller-based oscilloscopes - named PotatoScope. The intention of PotatoScope was to enable a scalable and dependable energy measurement for challenging environmental conditions, e.g., WSN outdoor deployments. We will present the general architecture by using two of our nodes and demonstrate how to measure energy consumption of nodes in our testbed. Certainly, the PotatoScope can be used standalone to measure energy comsumption of other devices, such as other micro controllers or single-board computers, e.g. Raspberry Pis. The demo will introduce a GUI, that displays information directly on a computer. Both the PotatoScope, including the hardware layout and the firmware, as well as the distributed energy measurement system is free to be used in own projects.

Energy is one of the most critical resources in Wireless Sensor Networks (WSN). For any WSN deployment, being it for a productive use case or for a testbed, the ability to perform energy measurements is of major importance, e.g., to estimate the status of the WSN, the need for maintenance, or for remaining lifetime. This paper presents a distributed energy measurement system for outdoor applications. An existing testbed has been extended by the micro controller unit (MCU)- based oscilloscope PotatoScope. Measuring voltage and current of the sensor node, undervolting effects and energy consumption of realtime applications can be observed. The PotatoScope is capable of capturing the power dissipation precisely at a high temperature range of 100 K. Using high sample rates with up to 500 kHz, the system needs to be capable of storing and archiving the measured data. A final evaluation shows a 0.9% drift for voltage measurements and a 1.6% drift for current measurements over the range of 100K. Using an SD card, long-term measurements can be made with up to 500 kHz. Nevertheless, a live mode allows sample rates up to 2 MHz when using the PotatoScope with a computer.

The energy consumption of Wireless Sensor Networks (WSNs) correlates with the voltage level at which the nodes are powered—a lowered voltage leads to a prolonged lifetime of nodes and networks. Operating nodes at voltage levels below the recommendation—so-called undervolting—saves energy but is accompanied by an increased risk of failures. In this article, we show that a WSN can still work reliably, even if the voltage recommendations are violated. We show that there is a correlation between temperature and error-proneness at the same voltage level and that ideal voltage levels depend on environmental conditions. Especially in outdoor deployments, temperatures fluctuate often and heavily. Additionally, we show that these ideal voltage levels are different for each individual node. To deal with these individual variations and varying temperatures, we present a supervised learning strategy that is able to keep the nodes in uncritical states even if environmental conditions are constantly and heavily changing while saving as much energy as possible by constantly adapting the voltage level of these nodes to an individually ideal level. All measurements were performed on sensor node prototypes that are also presented in this article. In detailed evaluations, it is shown (i) that a single node will never run in the same unsafe state twice, (ii) that only five known bias points are needed to predict nearly all temperature dependencies for an individual node, and, thus, (iii) that a system of undervolted nodes can be as reliable as a conventionally powered network while prolonging the lifetime by more than 40%.

Adapting the voltage level of a processing unit to the actual system load leads to an increased energy efficiency. The aim is to extend the battery lifetime, but existing voltage scaling approaches still act with reserve. To reduce the energy consumption even further, it is possible to power the electric circuits below the specified voltage levels. Considering the processing unit of wireless sensor nodes, this “undervolting” saves up to 42% of energy per clock cycle, and hence would lead to a significant longer lifetime of nodes and networks. Contrariwise, operating processors or nodes outside their specifications add some extra incertitude to the system. In this paper, we analyze the effects of undervolting for a typical wireless sensor node in theory and practice. Moreover, we give a detailed insight into the dependencies and used a prototype implementation to characterize the influence of lower than recommended voltage levels on the microcontroller unit (MCU). In addition, the impact of different temperatures is considered as well as the behavior of an undervolted transceiver unit and, therefore, the effects on the wireless communication. While classical computer applications may contain too many hazards to outweigh the improved energy consumption when using undervolting, we show that it is particularly suitable for wireless sensor networks (WSNs) with a huge potential of saving energy and the opportunity of novel power management approaches on every layer.

In mobile applications, like wireless sensor networks, it is often inevitable to use a location-independent source of energy. Wherever the batteries capacity or inefficient energy harvesting limits the lifetime, other solutions have to be implemented to increase the energy efficiency. Dynamic Voltage Scaling (DVS) is a well known technique with the ability to adapt the voltage level to the actual system load to save energy. While it has been used in many application areas, DVS has not been studied sufficiently for wireless sensor nodes. In this paper, we present a method to estimate the gain of DVS. We study DVS theoretically as well as in a practical manner, i.e., we using a prototype implementation of a DVS capable wireless sensor node. With the theoretical considerations we were able to optimize DVS for an 8-Bit ULP micro controller by a combination of DVS and dynamic power management (DPM). In addition, we proved the calculated results with an extensive practical evaluation of the concept using a prototypical implementation. Moreover, we analysed the effect of voltage scaling on other components of the sensor node (transceiver, sensors and memory).

In mobile applications, like wireless sensor networks, it is often inevitable to use a location-independent source of energy. Wherever the batteries capacity or inefficient energy harvesting limits the lifetime, other solutions have to be implemented to increase the energy efficiency. Dynamic Voltage Scaling (DVS) is a well known technique with the ability to adapt the voltage level to the actual system load to save energy. While it has been used in many application areas, DVS has not been studied sufficiently for wireless sensor nodes. In this demo, we show the benefits of DVS. We were able to optimize DVS for an 8-Bit ULP micro controller by a combination of DVS and dynamic power management (DPM). Moreover, we analyzed the effect of voltage scaling on other components of the sensor node (transceiver, sensors and memory).

In this demo, we present some exemplary applications for INGA, a new and affordable wireless sensor node for general applications. INGA's hardware design is completely under open source license and it runs the open source operating system Contiki "out of the box". Several up-to-date sensors are included in the basic design and we developed it for research, medical applications and universal usage.