Frederik Hermans

SoNIC: classifying interference in 802.15.4 sensor networks

Sensor networks that operate in the unlicensed 2.4 GHz frequency band suffer cross-technology radio interference from a variety of devices, e.g., Bluetooth headsets, laptops using WiFi, or microwave ovens. Such interference has been shown to significantly degrade network performance. We present SoNIC, a system that enables resource-limited sensor nodes to detect the type of interference they are exposed to and select an appropriate mitigation strategy. The key insight underlying SoNIC is that different interferers disrupt individual 802.15.4 packets in characteristic ways that can be detected by sensor nodes. In contrast to existing approaches to interference detection, SoNIC does not rely on active spectrum sampling or additional hardware, making it lightweight and energy-efficient. In an office environment with multiple interferers, a sensor node running SoNIC correctly detects the predominant interferer 87% of the time. To show how sensor networks can benefit from SoNIC, we add it to a mobile sink application to improve the applications packet reception ratio under interference.

Global source mobility in the content-centric networking architecture

The Content-Centric Networking (CCN) architecture, a clean-slate network design, borrows its routing concepts from IP. If content is located on mobile sources, CCN also inherits some of the mobility problems known from IP. In this paper, we explore the design space of CCN mobility solutions by revisiting well-known IP approaches that aim to solve a remarkably similar problem. While mobility solutions may be quite similar in both architectures, we find that a locator/identifier split should be implemented at the network layer in CCN to prevent temporary, topology-dependent information to leak into content that ought to be permanent. Mobility handling further benefits from CCNs security model and multipath forwarding. To provide a starting point for further research, we present a simple mobility approach based on an explicit locator/identifier split.

A long-term study of correlations between meteorological conditions and 802.15.4 link performance

Outdoor wireless sensor networks are all exposed to a constantly changing environment that influences the performance of the network. In this paper, we study how variations in meteorological conditions influence IEEE 802.15.4 links. We show that the performance varies over both long and short periods of time, and correlate these variations to changes in meteorological conditions. The case study is based on six months of data from a sensor network deployed next to a meteorological research station running a continuous experiment, collecting both high-quality link and meteorological measurements. We present observations from the deployment, highlighting variations in packet reception ratio and signal strength. Furthermore, we show how the variations correlate with four selected meteorological factors, temperature, absolute humidity, precipitation and sunlight. Our results show that packet reception ratio and signal strength correlate the most with temperature and the correlation with other factors are less pronounced. We also identify a diurnal cycle as well as a seasonal variation in the packet reception ratio aggregated over all links. We discuss the implication of the findings and how they can be used when designing wireless sensor networks.

Repeatable Experiments with Mobile Nodes in a Relocatable WSN Testbed

We present Sensei-UU, a testbed that supports mobile sensor nodes. The design objectives are to provide wireless sensor network (WSN) experiments with repeatable mobility and to be able to use the same testbed at different locations, including the target location. The testbed is inexpensive, expandable, relocatable and it is possible to reproduce it by other researchers. Mobile sensor nodes are carried by robots that use floor markings for navigation and localization. The testbed is typically used to evaluate WSN applications when sensor nodes move in meters rather than millimeters, eg. when human carries a mobile data sink (mobile phone) collecting data while passing fixed sensor nodes. To investigate the repeatability of robot movements, we have measured the achieved precision and timing of the robots. This precision is of importance to ensure the same radio link characteristics from one protocol experiment to another. We find that our robot localization is accurate to ±1 cm and variations in link characteristics are acceptably low to capture fading phenomena in IEEE 802.15.4. In the paper we show repeatable experiment results from three environments, two university corridors and from an anechoic chamber. We conclude that the testbed is relocatable between different environments and that the precision is good enough to capture fading effects in a repeatable way.

Sensei-uu: a relocatable sensor network testbed

A testbed is a powerful complement to simulation and emulation for evaluation of wireless sensor network (WSN) applications. However, testbeds tend to be limited to lab environments and tightly coupled to specific hardware and sensor OS configurations. These limitations, in addition to dependency on local infrastructure make it hard to evaluate applications on actual hardware in the intended target environment. We introduce Sensei-UU, a WSN testbed designed to be easily relocatable between different physical environments and not tightly dependent on specific sensor hardware or OS. The ability to relocate the testbed enables users to evaluate WSN applications in their intended target environments. The wide range of supported sensor node platforms allows users to evaluate heterogeneous applications. Sensei-UU achieves its flexibility by following a distributed design in which control functionality is put on control machines close to the sensor nodes, and by using a wireless control channel. We have run experiments to ensure that our wireless control channel does not interfere with the WSN application under evaluation. We show that Sensei-UU can be relocated between environments and that seemingly similar physical locations can have a large difference in radio environment. These differences between locations motivate the need for relocatable testbeds like Sensei-UU

Repeatable experiments with mobile nodes in a relocatable WSN testbed

We present Sensei-UU, a testbed that supports mobile sensor nodes. The design objectives are to provide wireless sensor network (WSN) experiments with repeatable mobility and to be able to use the same testbed at different locations, including the target location. The testbed is inexpensive, expandable, relocatable and it is possible to reproduce it by other researchers. Mobile sensor nodes are carried by robots that use floor markings for navigation and localization. The testbed is typically used to evaluate WSN applications when sensor nodes move in meters rather than millimeters, eg. when human carries a mobile data sink (mobile phone) collecting data while passing fixed sensor nodes. To investigate the repeatability of robot movements, we have measured the achieved precision and timing of the robots. This precision is of importance to ensure the same radio link characteristics from one protocol experiment to another. We find that our robot localization is accurate to ±1 cm and variations in link characteristics are acceptably low to capture fading phenomena in IEEE 802.15.4. In the paper we show repeatable experiment results from three environments, two university corridors and from an anechoic chamber. We conclude that the testbed is relocatable between different environments and that the precision is good enough to capture fading effects in a repeatable way.

Quality estimation based data fusion in wireless sensor networks

The main purpose of wireless sensor networks (WSNs) is to obtain information about their environment. However, WSNs often produce imprecise and incorrect sensor data, e.g. because of sensor failure or unreliable radio communication. We propose a system for WSN applications that allows to assess the quality of sensor data and further allows to fuse data based on their estimated quality. Our system comprises local and distributed heuristics to estimate the quality of sensor data, with a focus on data accuracy and data consistency. In the fusion step, the most plausible value of the measured quantity is inferred from multiple sensor readings by use of the Dempster-Shafer theory of evidence. Both quality assessment and data fusion are carried out within the network and thus do not rely on a powerful sink node. We demonstrate the effectiveness of our system by means of a wireless game controller for the game Pong, built from multiple sensor nodes. The controller can detect and reject incorrect sensor readings and thus improve the players control over the in-game paddle.

Detecting and Avoiding Multiple Sources of Interference in the 2.4 GHz Spectrum

Sensor networks operating in the 2.4 GHz band often face cross-technology interference from co-located WiFi and Bluetooth devices. To enable effective interference mitigation, a sensor network needs to know the type of interference it is exposed to. However, existing approaches to interference detection are not able to handle multiple concurrent sources of interference. In this paper, we address the problem of identifying multiple channel activities impairing a sensor network’s communication, such as simultaneous WiFi traffic and Bluetooth data transfers. We present SpeckSense, an interference detector that distinguishes between different types of interference using a unsupervised learning technique. Additionally, SpeckSense features a classifier that distinguishes between moderate and heavy channel traffic, and also identifies WiFi beacons. In doing so, it facilitates interference avoidance through channel blacklisting. We evaluate SpeckSense on common mote hardware and show how it classifies concurrent interference under real-world settings. We also show how SpeckSense improves the performance of an existing multichannel data collection protocol by 30%.

A lightweight approach to online detection and classification of interference in 802.15.4-based sensor networks

With a rapidly increasing number of devices sharing access to the 2.4 GHz ISM band, interference becomes a serious problem for 802.15.4-based, low-power sensor networks. Consequently, interference mitigation strategies are becoming commonplace. In this paper, we consider the step that precedes interference mitigation: interference detection. We have performed extensive measurements to characterize how different types of interferers affect individual 802.15.4 packets. From these measurements, we define a set of features which we use to train a neural network to classify the source of interference of a corrupted packet. Our approach is sufficiently lightweight for online use in a resource-constrained sensor network. It does not require additional hardware, nor does it use active spectrum sensing or probing packets. Instead, all information about interferers is gathered from inspecting corrupted packets that are received during the sensor networks regular operation. Even without considering a history of earlier packets, our approach reaches a mean classification accuracy of 79.8%, with per interferer accuracies of 64.9% for WiFi, 82.6% for Bluetooth, 72.1% for microwave ovens, and 99.6% for packets that are corrupted due to insufficient signal strength.

LoRea: A Backscatter Architecture that Achieves a Long Communication Range

There is the long-standing assumption that radio communication in the range of hundreds of meters needs to consume mWs of power at the transmitting device. In this paper, we demonstrate that this is not necessarily the case for some devices equipped with backscatter radios. We present LOREA an architecture consisting of a tag, a reader and multiple carrier generators that overcomes the power, cost and range limitations of existing systems such as Computational Radio Frequency Identification (CRFID). LOREA achieves this by: First, generating narrow-band backscatter transmissions that improve receiver sensitivity. Second, mitigating self-interference without the complex designs employed on RFID readers by keeping carrier signal and backscattered signal apart in frequency. Finally, decoupling carrier generation from the reader and using devices such as WiFi routers and sensor nodes as a source of the carrier signal. An off-the-shelf implementation of LOREA costs 70 USD, a drastic reduction in price considering commercial RFID readers cost 2000 USD. LOREAs range scales with the carrier strength, and proximity to the carrier source and achieves a maximum range of 3.4 km when the tag is located at 1 m distance from a 28 dBm carrier source while consuming 70 μW at the tag. When the tag is equidistant from the carrier source and the receiver, we can communicate upto 75 m, a significant improvement over existing RFID readers.