Olof Rensfelt

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.

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.

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.

Sensei — a flexible testbed for heterogeneous wireless sensor networks

We present Sensei - a nomadic, relocatable, wireless sensor network (WSN) testbed with support for mobile nodes. The nomadism makes it possible to evaluate a WSN application in different environments ranging from lab environments to in-situ installations to prototype deployments. Other WSN testbeds are often static and can not easily mobed between sites. We also support reproducibility mobility in the testbed, using robots or humans as actuators with movement patterns defined in mobility scripts.

Efficient Mobile Data Collection with Mobile Collect

The main task of most deployed wireless sensor networks is data collection. While a number of solutions have been designed for static networks, there are currently no widely used data collection algorithms for mobile sensor networks. In this paper, we concentrate on scenarios where many nodes, both data sources and sinks, move along a certain track in one direction, a scenario that is common in sports events. Rather than designing a new protocol from scratch, we extend an existing data collection protocol with lightweight mechanisms to make it efficient for mobility. Our extensive simulations and results in a test bed that includes mobile robots demonstrate that our solution is able to achieve high packet delivery rates at low energy consumption. For our target scenario, our solution more than doubles packet delivery rates when the network is sparse. Our solution also works well in scenarios with a higher degree of mobility where nodes move according to a more demanding random waypoint model.

Vendetta - A Tool for Flexible Monitoring and Management of Distributed Testbeds

Writing a powerful tool for monitoring and management of a testbed can have a positive effect when doing research on the testbed. Despite this, many testbeds use primitive scripts for data collection, code updates and other basic tasks. We introduce Vendetta, a flexible and powerful platform for monitoring and management of distributed testbeds. It is designed to be relatively easy to adapt to different testbeds by having a modular design, being written in Java and defining much of the testbed-specific behavior in two configuration files. The novelty in comparison with similar tools is the integration of a GUI supporting 30 graphics, flexible monitoring and management into one single tool. We will present the general design of Vendetta and then illustrate how it has been used for monitoring and management of an experimental DHT deployment running on PlanetLab. Experiences from this combination shows that usage of a tool like Vendetta simplifies testbed management and makes it easier to discover and analyze different phenomena.

Revisiting the need for mobile MAC protocols in wireless sensor networks

There exists a number of MAC protocols targeted for mobile scenarios. These include MMAC, MS-MAC and AM-MAC. These MAC protocols have in common that they seem to be evaluated only in simulation. This might indicate that these MAC are either too complex to use or they are not needed, at least for data collection, the major task of sensor networks. In this paper we show that extending a traditional data collection protocol with lightweight, carefully selected mechanisms is sufficient to provide reliable data collection at low energy cost for mobile sensor networks where both sinks and sources move.