Lars-Åke Larzon

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

Reducing the TCP acknowledgment frequency

Delayed acknowledgments were introduced to conserve network and host resources. Further reduction of the acknowledgment frequency can be motivated in the same way. However, reducing the dependency on frequent acknowledgments in TCP is difficult because acknowledgments support reliable delivery, loss recovery, clock out new segments, and serve as input when determining an appropriate sending rate. Our results show that in scenarios where there are no obvious advantages of reducing the acknowledgment frequency, performance can be maintained although fewer acknowledgments are sent. Hence, there is a potential for reducing the acknowledgment frequency more than is done through delayed acknowledgments today. Advancements in TCP loss recovery is one of the key reasons that the dependence on frequent acknowledgments has decreased. We propose and evaluate an end-to-end solution, where four acknowledgments per send window are sent. The sender compensates for the reduced acknowledgment frequency using a form of Appropriate Byte Counting. The proposal also includes a modification of fast loss recovery to avoid frequent timeouts.

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.

Performance of Pastry in a heterogeneous system

We study how Pastry performs in a heterogeneous network environment of varying size. The large traffic overhead for management traffic makes the overlay nonfunctional if it grows too large. This can be circumvented by partitioning the routing tables at the cost of increased path lengths and response times.

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.

Student perceptions of reflections as an aid to learning

An important aspect in any learning situation is the approach that students take to learning. Studies in the 1980s built an increasingly convincing case for the existance of three learning approaches; deep, surface and achieving. These approaches are not mutually exclusive, and a single student may use any or all of them in combination. In addition, a connection has been demonstrated between deep learning approaches and understanding of the material being learned. Encouraging deep learning behaviour, however, is a much more complex issue, since choice of learning approach seems to be dependent on the manner in which the student experiences the learning environment. This paper explores the use of reflections in the instructional design of two computing courses based on the text of the reflections and student feedback regarding the reflection exercise collected through surveys and interviews. Students learning approaches are infered from a textual analysis of the reflection texts. Results describing students perceptions of the utility of reflections as a learning tool are explored using interview data collected from students in one of the study cohorts.

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.

Sensei-UU — A Relocatable WSN Testbed Supporting Repeatable Node Mobility

General purpose testbeds for Wireless Sensor Network (WSN) systems are often deployed in lab environments. This means that the testbed environment may differ considerably from the target environment of a system with respect to e.g. radio interference and sensory input. Furthermore, many WSN scenarios include mobile nodes, such as mobile sensors and mobile sinks, whose movements can affect the experimental results considerably. Both these features pose a challenge to achieving consistent and reliable experimental results during the evaluation and testing of a WSN system.