Olga Saukh

Assistant Professor at TU Graz, Institute for Technical Informatics
Scientist at Complexity Science Hub Vienna

List of Publications

Please also visit my Google scholar profile and my ResearchGate profile.

Journals, Conferences, and Workshops

2017

B. Maag, Z. Zhou, O. Saukh, L. Thiele
2017
BARTON: Low Power Tongue Movement Sensing with In-ear Barometers
IEEE International Conference on Parallel and Distributed Systems (ICPADS), Best Paper Candidate
B. Maag, Z. Zhou, O. Saukh, L. Thiele
2017
SCAN: Multi-Hop Calibration for Mobile Sensor Arrays
ACM Journal on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT and UBICOMP)

2016

B. Maag, O. Saukh, D. Hasenfratz, L. Thiele
2016
Pre-Deployment Testing, Augmentation and Calibration of Cross-Sensitive Sensors
International Conference on Embedded Wireless Systems and Networks (EWSN)
Over the past few years, many low-cost pollution sensors have been integrated into measurement platforms for air quality monitoring. However, using these sensors is challenging: concentrations of toxic gases in ambient air often lie at sensors’ sensitivity boundaries, environmental conditions affect the sensor signal, and the sensors are crosssensitive to multiple pollutants. Datasheet information on these effects is scarce or may not cover deployment conditions. Consequently the sensors need to undergo extensive pre-deployment testing to examine their feasibility for a given application and to find the optimal measurement setup that allows accurate data collection and calibration.
In this work, we propose a novel method to conduct infield testing of low-cost sensors. The algorithm proposed is based on multiple least-squares and leverages the physical variation of urban air pollution to quantify the amount of explained and unexplained sensor signal. We verify (i) whether a sensor is feasible for air quality monitoring in a given environment, (ii) model sensor cross-sensitivities to interfering gases and environmental effects and (iii) compute the optimal sensor array and its calibration parameters for stable and accurate sensor measurements over long time periods. Finally, we apply our testing approach on five off-the-shelf low-cost sensors and twelve reference signals using over 9 million measurements collected in an urban area. We propose an optimized sensor array and show—compared to a state-of-the-art calibration technique—an up to 45% lower calibration error with better long-time stability of the calibration parameters.
M. Mueller, D. Hasenfratz, O. Saukh, M. Fierz, C. Hueglin.,
2016
Statistical modelling of particle number concentration in Zurich at high spatio-temporal resolution utilizing data from a mobile sensor network
Journal of Atmospheric Environment, Elsevier
Highly resolved pollution maps are a valuable resource for many issues related to air quality including exposure modelling and urban planning. We present an approach for their generation based on data from a mobile sensor network and statistical modelling.
An extensive record of particle number concentrations (PNCs) spanning more than 1.5 years was compiled by the tram-based OpenSense mobile sensor network in the City of Zurich. The sensor network consists of 10 sensor nodes installed on the roof of trams operating on different services according to their regular operation schedules. We developed a statistical modelling approach based on Generalized Additive models (GAMs) utilizing the PNC data obtained along the tram tracks as well as georeferenced information as predictor variables. Our approach includes a variable selection algorithm to ensure that individual models rely on the optimal set of predictor variables. Our models have high temporal and spatial resolutions of 30 min and 10 m by 10 m, respectively, and allow the spatial prediction of PNC in the municipal area of Zurich.
We applied our approach to PNC data from two dedicated time periods: July--Sept. 2013 and Dec. 2013--Feb. 2014. The models strongly rely on traffic related predictor variables (vehicle counts) and, due to the hilly topography of Zurich, on elevation. We assessed the model performance by leave-one-out crossvalidation and by comparing PNC predictions to measurements at fixed reference sites and to PNC measurements obtained by pedestrians. Model predictions reproduce well the main features of the PNC field in environment types similar to those passed by individual trams. Model performance is worse at elevated background locations probably due to the weak coverage of similar spots by the tram network.
We end the paper by outlining a route finding algorithm which utilizes the highly resolved PNC maps providing the exposure minimal route for cyclists.

2015

O. Saukh, D. Hasenfratz, L. Thiele
2015
Reducing Multi-Hop Calibration Errors in Mobile Sensor Networks
International Conference on Information Processing in Sensor Networks (IPSN), Best Paper Award
Frequent sensor calibration is essential in sensor networks with low-cost sensors. We exploit the fact that temporally and spatially close measurements of different sensors measuring the same phe- nomenon are similar. Hence, when calibrating a sensor, we ad- just its calibration parameters to minimize the differences between co-located measurements of previously calibrated sensors. In turn, freshly calibrated sensors can now be used to calibrate other sen- sors in the network, referred to as multi-hop calibration.
We are the first to study multi-hop calibration with respect to a reference signal (micro-calibration) in detail. We show that ordi- nary least squares regression—commonly used to calibrate noisy sensors—suffers from significant error accumulation over multiple hops. In this paper, we propose a novel multi-hop calibration al- gorithm using geometric mean regression, which (i) highly reduces error propagation in the network, (ii) distinctly outperforms ordi- nary least squares in the multi-hop scenario, and (iii) requires con- siderably fewer ground truth measurements compared to existing network calibration algorithms. The proposed algorithm is espe- cially valuable when calibrating large networks of heterogeneous sensors with different noise characteristics. We provide theoretical justifications for our claims. Then, we conduct a detailed analy- sis with artificial data to study calibration accuracy under various settings and to identify different error sources. Finally, we use our algorithm to accurately calibrate 13 million temperature, ground ozone (O3), and carbon monoxide (CO) measurements gathered by our mobile air pollution monitoring network.
D. Hasenfratz, O. Saukh, C. Walser, C. Hueglin, M. Fierz, T. Arn, J. Beutel, L. Thiele
2015
Deriving High-Resolution Urban Air Pollution Maps Using Mobile Sensor Nodes
Journal of Pervasive and Mobile Computing (PMC), Elsevier
Up-to-date information on urban air pollution is of great importance for environmental protection agencies to assess air quality and provide advice to the general public in a timely manner. In particular, ultrafine particles (UFPs) are widely spread in urban environments and may have a severe impact on human health. However, the lack of knowledge about the spatio-temporal distribution of UFPs hampers profound evaluation of these effects. In this paper, we analyze one of the largest spatially resolved UFP data set publicly available today containing over 50 million measurements. We collected the measurements throughout more than two years using mobile sensor nodes installed on top of public transport vehicles in the city of Zurich, Switzerland. Based on these data, we develop land-use regression models to create pollution maps with a high spatial resolution of 100 m × 100 m. We compare the accuracy of the derived models across various time scales and observe a rapid drop in accuracy for maps with sub-weekly temporal resolution. To address this problem, we propose a novel modeling approach that incorporates past measurements annotated with metadata into the modeling process. In this way, we achieve a 26% reduction in the root-mean-square error – a standard metric to evaluate the accuracy of air quality models – of pollution maps with semi-daily temporal resolution. We believe that our findings can help epidemiologists to better understand the adverse health effects related to UFPs and serve as a stepping stone towards detailed real-time pollution assessment.

2014

D. Hasenfratz, O. Saukh, C. Walser, C. Hueglin, M. Fierz, L. Thiele
2014
Pushing the Spatio-Temporal Resolution Limit of Urban Air Pollution Maps
Proceedings of the 12th International Conference on Pervasive Computing and Communications (PerCom), Best Paper Award
Up-to-date information on urban air pollution is of great importance for health protection agencies to assess air quality and provide advice to the general public in a timely manner. In particular, ultrafine particles (UFPs) are widely spread in urban environments and may have a severe impact on human health. However, the lack of knowledge about the spatio-temporal distribution of UFPs hampers profound evaluation of these effects. In this paper, we analyze one of the largest spatially resolved UFP data set publicly available today containing over 25 million measurements. We collected the measurements throughout more than a year using mobile sensor nodes installed on top of public transport vehicles in the city of Zurich, Switzerland. Based on these data, we develop land-use regression models to create pollution maps with a high spatial resolution of 100 m × 100 m. We compare the accuracy of the derived models across various time scales and observe a rapid drop in accuracy for maps with subweekly temporal resolution. To address this problem, we propose a novel modeling approach that incorporates past measurements annotated with metadata into the modeling process. In this way, we achieve a 26 % reduction in the root-mean-square error -- a standard metric to evaluate the accuracy of air quality models -- of pollution maps with semi-daily temporal resolution. We believe that our findings can help epidemiologists to better understand the adverse health effects related to UFPs and serve as a stepping stone towards detailed real-time pollution assessment.

2013

D. Hasenfratz, S. Sturzenegger, O. Saukh, L. Thiele
2013
Spatially Resolved Monitoring of Radio-Frequency Electromagnetic Fields
Proceedings of the 1st International Workshop on Sensing and Big Data Mining (SenseMine)
Radio-frequency electromagnetic fields are emitted by many applications, such as radio broadcasting and mobile communication. A part of the general public is increasingly concerned about the long-term ects of electromagnetic radiation on human health. However, the accurate exposure assessment in people's everyday life remains a formidable challenge. State-of-the-art personal exposure meters are expensive and tedious to use. Epidemiological large-scale studies are rare and governmental compliance measurements can only cover a small number of locations of high interest (e.g., schools). In this paper, we demonstrate that accurate, spatially resolved electromagnetic field measurements are feasible with commodity sensor nodes. We show the design, implementation, and evaluation on mobile air quality sensor nodes, which traverse a large urban area on top of public transport vehicles in Zurich, Switzerland. We collect a data set with over 4 million measurements and use it to develop the first exposure map of Zurich with a spatial resolution of 100 m. Further, we compare the found exposure levels to measurements from different urban cities across Europe.
O. Saukh, D. Hasenfratz, C. Walser, L. Thiele
2013
On Rendezvous in Mobile Sensing Networks
Proceedings of the 5th Workshop on Real-World Wireless Sensor Networks (RealWSN)
A rendezvous is a temporal and spatial vicinity of two sensors. In this paper, we investigate rendezvous in the context of mobile sensing systems. We use an air quality dataset obtained with the OpenSense monitoring network to explore rendezvous properties for carbon monoxide, ozone, temperature, and humidity processes. Temporal and spatial locality of a physical process impacts the number of rendezvous between sensors, their duration, and their frequency. We introduce a rendezvous connection graph and explore the trade-off between locality of a process and the amount of time needed for the graph to be connected. Rendezvous graph connectivity has many potential use cases, such as sensor fault detection. We successfully apply the proposed concepts to track down faulty sensors and to improve sensor calibration in our deployment.
D. Hasenfratz, O. Saukh, L. Thiele
2013
Model-Driven Accuracy Bounds for Noisy Sensor Readings
Proceedings of the 9th IEEE Conference on Distributed Computing in Sensor Systems (DCoSS)
Wireless sensor networks are increasingly used in application scenarios where a high data quality is inevitable, e.g., the control of industrial production areas. Nevertheless, many deployments must live with strict constraints regarding the sensing hardware and may not employ newest sensing technologies, e.g., due to limited energy budget, size, and bandwidth. Additionally, many applications would benefit from not only gathering absolute sensor readings but also knowing the quality of their low-cost sensor measurements. In this paper, we introduce a model-driven approach that (i) provides reliable accuracy bounds for individual noisy sensor readings and (ii) detects systematic and transient sensor errors. We apply our method to static and mobile real-world deployments of noisy and unstable low-cost sensors by analyzing large sets of urban temperature and ozone measurements. We find that the proposed algorithm successfully calculates precise accuracy bounds. We compare them to measurements of high-quality instruments and show that up to 96 % of the reference measurements are inside the computed accuracy bounds in the static scenario and up to 94 % in the mobile scenario. This is surprisingly high for the used low-cost sensors. By analyzing data from our static longterm deployment, we reveal that the ozone sensor's reliability is dependent on seasonal weather conditions.
O. Saukh, D. Hasenfratz, L. Thiele
2013
Route Selection for Mobile Sensor Nodes on Public Transport Networks
Journal of Ambient Intelligence and Humanized Computing, Springer
The sensing range of a sensor is spatially limited. Thus, achieving a good coverage of a large area of interest requires installation of a huge number of sensors which is cost and labor intensive. For example, monitoring air pollution in a city needs a high density of measurement stations installed throughout the area of interest. As alternative, we install a smaller number of mobile sensing nodes on top of public transport vehicles that regularly traverse the city. In this paper, we consider the problem of selecting a subnetwork of a city's public transport network to achieve a good coverage of the area of interest. In general case, public transport vehicles are not assigned to ^Lx lines but rather to depots where they are parked overnight. We introduce an algorithm that selects the installation locations, i.e., number of vehicles within each host depot, such that sensing coverage is maximized. Since we are working with low-cost sensors, which exhibit failures and drift over time, vehicles selected for sensor installation have to be in each other's vicinity from time to time to allow comparing sensor readings. We refer to such meeting points as checkpoints. Our algorithm optimizes sensing coverage while providing a suitablecient number of checkpoint locations. We evaluate our algorithm based on the tram network of Zurich and show how an accurate selection of vehicles for installing measurement stations acts the overall system quality. We show that our algorithm outperforms random search, simulated annealing, and the greedy approach.

2012

M. Keller, J. Beutel, O. Saukh, L. Thiele
2012
Visualizing Large Sensor Network Data Sets in Space and Time with Vizzly
Proceedings of the 7th IEEE International Workshop on Practical Issues in Building Sensor Network Applications (SenseApp)
This paper presents Vizzly, a middleware for the interactive browsing of large sensor network data sets. Provided map and line plot widgets allow to visualize structured data from mobile and static sensors. A user is completely free in selecting sensor data based on time and location, suitable levels of temporal and spatial detail are automatically chosen by the Vizzly server. Vizzly automatically adapts to user interactions, new data is automatically loaded when query parameters change. Request response times are significantly reduced by the use of caching techniques, most requests are served from already pre-computed data that is stored in the memory of the Vizzly server. Vizzly has already been successfully integrated into the PermaSense and OpenSense projects, a single instance is currently handling more than 550 millions of data points.
K. Flouri, O. Saukh, R. Sauter, K. E. Jalsan, R. Bischoff, J. Meyer, G. Feltrin
2012
A versatile software architecture for civil structure monitoring with wireless sensor networks
pp 209–228
Smart Structures and Systems, Vol. 10, Nr. 3, Techno Press
Structural health monitoring with wireless sensor networks has received much attention in recent years due to the ease of sensor installation and low deployment and maintenance costs. However, sensor network technology needs to solve numerous challenges in order to substitute conventional systems: large amounts of data, remote configuration of measurement parameters, on-site calibration of sensors and robust networking functionality for long-term deployments. We present a structural health monitoring network that addresses these challenges and is used in several deployments for monitoring of bridges and buildings. Our system supports a diverse set of sensors, a library of highly optimized processing algorithms and a lightweight solution to support a wide range of network runtime configurations. This allows flexible partitioning of the application between the sensor network and the backend software. We present an analysis of this partitioning and evaluate the performance of our system in three experimental network deployments on civil structures.
J. J. Li, B. Faltings, O. Saukh, D. Hasenfratz, J. Beutel
2012
Sensing the Air We Breathe - the OpenSense Dataset
Proceedings of the 26th International Conference on Artificial Intelligence (AAAI)
Toronto, Canada
Monitoring and managing urban air pollution is a significant challenge for the sustainability of our environment. We quickly survey the air pollution modeling problem, introduce a new dataset of mobile air quality measurements in Zurich, and discuss the challenges of making sense of these data.
D. Hasenfratz, O. Saukh, S. Sturzenegger, L. Thiele
2012
Participatory Air Pollution Monitoring Using Smartphones
Proceedings of the 1st International Workshop on Mobile Sensing: From Smartphones and Wearables to Big Data
Air quality monitoring is extremely important as air pollution has a direct impact on human health. In this paper we introduce a low-power and low-cost mobile sensing system for participatory air quality monitoring. In contrast to traditional stationary air pollution monitoring stations, we present the design, implementation, and evaluation of GasMobile, a small and portable measurement system based on off-the-shelf components and suited to be used by a large number of people. Vital to the success of participatory sensing applications is a high data quality. We improve measurement accuracy by (i) exploiting sensor readings near governmental measurement stations to keep sensor calibration up to date and (ii) analyzing the ect of mobility on the accuracy of the sensor readings to give user advice on measurement execution. Finally, we show that it is feasible to use GasMobile to create collective high-resolution air pollution maps.
O. Saukh, D. Hasenfratz, A. Noori, T. Ulrich, L. Thiele
2012
Route Selection for Mobile Sensors with Checkpointing Constraints
Proceedings of the 8th International Workshop on Sensor Networks and Systems for Pervasive Computing (PerSeNS)
The sensing range of a sensor is spatially limited. Thus, achieving a good coverage of a large area of interest requires installation of a huge number of sensors which is cost and labor intensive. For example, monitoring air pollution in a city needs a high density of measurement stations installed throughout streets and courtyards. An alternative is to install a smaller number of mobile stations which traverse the city. The public transport network builds a perfect backbone for this purpose as public transport vehicles follow fixed and regular mobility patterns. In this paper, we consider the problem of selecting a subnetwork of a city's public transport network to achieve a good coverage in the area. Since we are working with low-cost sensors which exhibit failures and drift over time, vehicles selected for sensor installation have to be in each other's vicinity from time to time to allow comparing sensor readings. We refer to such meeting points as checkpoints. Due to high computational complexity of the route selection problem, both with and without checkpointing support, we adapt an evolutionary algorithm solution and evaluate its output based on the tram network of Zurich.
D. Hasenfratz, O. Saukh, L. Thiele
2012
On-the-fly Calibration of Low-cost Gas Sensors
Proceedings of the 9th European Conference on Wireless Sensor Networks (EWSN)
Air quality monitoring is extremely important as air pollution has a direct impact on human health. Low-cost gas sensors are used to effectively perceive the environment by mounting them on top of mobile vehicles, for example, using a public transport network. Thus, these sensors are part of a mobile network and perform from time to time measurements in each others vicinity. In this paper, we study three calibration algorithms that exploit co-located sensor measurements to enhance sensor calibration and consequently the quality of the pollution measurements on-the-fly. Forward calibration, based on a traditional approach widely used in the literature, is used as performance benchmark for two novel algorithms: backward and instant calibration. We validate all three algorithms with real ozone pollution measurements carried out in an urban setting by comparing gas sensor output to high-quality measurements from analytical instruments. We find that both backward and instant calibration reduce the average measurement error by a factor of two compared to forward calibration. Furthermore, we unveil the arising difficulties if sensor calibration is not based on reliable reference measurements but on sensor readings of low-cost gas sensors which is inevitable in a mobile scenario with only a few reliable sensors. We propose a solution and analyze the influence on the measurement accuracy in experiments and simulation.

2011

R. Sauter, R. Figura, O. Saukh, P. J. Marrón
2011
Boreas: Efficient Synchronization for Scalable Emulation of Sensor Networks
Proceedings of the 8th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS)
Cycle-accurate emulation of sensor networks allows a detailed analysis of platform target code for development and evaluation. However, the high overhead incurred by providing the necessary fidelity limits the size of the emulated networks considerably. The use of multiple cores provided by modern hardware can significantly improve the speed of emulation but requires synchronization algorithms to preserve causality. Based on the well-known multithreaded event-driven emulator Avrora, we investigate a number of synchronization methods including an algorithm that does not require any locks to improve the performance. We show that both the speed and the scalability can be significantly improved without sacrificing correctness. Additionally, we evaluate the impact of modern CPU technologies such as simultaneous multithreading on emulation performance.
R. Sauter, O. Saukh, O. Frietsch, P. J. Marrón
2011
TinyLTS: Efficient Network-Wide Logging and Tracing System for TinyOS
Proceedings of the 30th IEEE International Conference on Computer Communications (INFOCOM)
Logging and tracing are important methods to gain insight into the behavior of sensor network applications. Existing generic solutions are often limited to nodes with a direct serial connection and do not provide the required efficiency for network-wide logging. Instead, this is often realized by application-specific subsystems developed for predefined logging statements. In this paper, we present TinyLTS - a generic and efficient Logging and Tracing System for TinyOS. TinyLTS consists of a compiler extension that separates dynamic from static information at compile time, a declarative solution for inserting logging statements, an extensible framework for flexible storing and transmitting of logging data and a frontend for recombining dynamic and static information. Our system provides concise yet expressive programming abstractions for the developer combined with efficiency comparable to custom solutions.
F. Ferrari, M. Zimmerling, L. Thiele, O. Saukh
2011
Efficient Network Flooding and Time Synchronization with Glossy
Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), Best Paper Award
This paper presents Glossy, a novel flooding architecture for wireless sensor networks. Glossy exploits constructive interference of IEEE 802.15.4 symbols for fast network flooding and implicit time synchronization. We derive a timing requirement to make concurrent transmissions of the same packet interfere constructively, allowing a receiver to decode the packet even in the absence of capture effects. To satisfy this requirement, our design temporally decouples flooding from other network activities. We analyze Glossy using a mixture of statistical and worst-case models, and evaluate it through experiments under controlled settings and on three wireless sensor testbeds. Our results show that Glossy floods packets within a few milliseconds and achieves an average time synchronization error below one microsecond. In most cases, a node receives the flooding packet with a probability higher than 99.99 %, while having its radio turned on for only a few milliseconds during a flood. Moreover, unlike existing flooding schemes, Glossy's performance exhibits no noticeable dependency on node density, which facilitates its application in diverse real-world settings.
G. Feltrin, O. Saukh, R. Bischoff, J. Meyer, M. Motavalli
2011
Structural Monitoring with Wireless Sensor Networks: Experiences From Field Deployments
Proceedings of the 1st Middle East Conference on Smart Monitoring (SMAR)
In the last years, wireless sensor networks have emerged as a promising technology that is inducing a deep innovation in the field of structural monitoring. The main advantages of wireless sensor networks are fast deployment, little interference and selforganization. However, since wireless sensor nodes are battery powered, in long term monitoring applications the power management influences significantly the operation of a wireless sensor network. In data intensive applications, e.g. vibration based monitoring, low power hardware, duty cycle operation and efficient communication policies are not sufficient for achieving a sustainable system lifetime. Since data communication is the most energy consuming task, long system lifetimes can only be achieved by a significant data reduction in the nodes. This data reduction is a challenging task, since it has to be performed with very limited computational and memory resources and in competition with tasks providing the basic network functionality. The objective of the paper is to provide a brief overview of the wireless sensor network technology and to present our experience over the past three years with data intensive structural monitoring using wireless sensor networks. Deployments on two bridges are illustrated and specific aspects of sensing, data quality, stability, availability, and system lifetime are analyzed.

2010

O. Saukh, R. Sauter, M. Gauger, P. J. Marrón
2010
On Boundary Recognition without Location Information in Wireless Sensor Networks
pp 1–35
ACM Transactions on Sensor Networks (TOSN)
Boundary recognition is an important and challenging issue in wireless sensor networks when no coordinates or distances are available. The distinction between inner and boundary nodes of the network can provide valuable knowledge to a broad spectrum of algorithms. This paper tackles the challenge of providing a scalable and range-free solution for boundary recognition that does not require a high node density. We explain the challenges of accurately defining the boundary of a wireless sensor network with and without node positions and provide a new definition of network boundary in the discrete domain. Our solution for boundary recognition approximates the boundary of the sensor network by determining the majority of inner nodes using geometric constructions that guarantee that, for a given d, a node lies inside of the construction for a d-quasi unit disk graph model of the wireless sensor network. Moreover, such geometric constructions make it possible to compute a guaranteed distance from a node to the boundary. We present a fully distributed algorithm for boundary recognition based on these concepts and perform a detailed complexity analysis. We provide a thorough evaluation of our approach and show that it is applicable to dense as well as sparse deployments.

2009

O. Saukh, R. Sauter, P. J. Marrón
2009
Convex Groups for Self-organizing Multi-sink Wireless Sensor Networks
Proceedings of the 35th Annual Conference of the IEEE Industrial Electronics Society (IECON)
Mobile ad-hoc networks have long been proposed for rescue scenarios to support and coordinate the efforts of helpers. Low power wireless sensor networks are a natural extension of this approach. They can provide valuable environmental data enriched with location information to deepen the insight of the operational area. Gateways between these two communication paradigms are necessary to facilitate the collaboration of both systems. We study such multi-sink wireless sensor network scenarios and explore the use of convex groups to efficiently disseminate location dependent information, for example, for query distribution. Convex groups show significant advantages in terms of message overhead compared to straightforward approaches without sacrificing connectivity. They do not exhibit high computational complexity and handle node mobility as well as gateway mobility gracefully. The evaluation results presented in this paper show the broad applicability of convex grouping.
M. Gauger, O. Saukh, P. J. Marrón
2009
Enlighten Me! Secure Key Assignment in Wireless Sensor Networks
Proceedings of the 6th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS)
The availability of secret keys is a precondition for the use of many security solutions and protocols. However, securely assigning such keys to nodes is a challenging task in the context of wireless sensor networks. In this paper we present a novel solution for a secure key assignment in wireless sensor networks that can be used during the initial configuration of nodes or for an ad-hoc key assignment by mobile nodes. The idea is to transmit the key information over a side channel using a controllable light source as the sender and the light sensors available on wireless sensor nodes as receivers. We demonstrate that our solution fulfills the relevant security requirements while at the same time being cost effective and easy to use.
M. Gauger, O. Saukh, P. J. Marrón
2009
Talk to Me! On Interacting with Wireless Sensor Nodes
Proceedings of the Seventh Annual IEEE International Conference on Pervasive Computing and Communications (PerCom)
Wireless sensor networks play an essential role in many pervasive computing scenarios as providers of context data. However, interacting with sensor nodes and selecting specific nodes for an interaction is difficult due to the constraints of the sensor node hardware. In this paper, we present and discuss three different approaches for this node interaction problem based on gestures, on light signals and on information provided by the sensor nodes using their LEDs. We demonstrate in our evaluation that these mechanisms solve the interaction problem for a variety of scenarios and effectively support the user in the interaction process. At the same time, our solutions set only low requirements on the wireless sensor node hardware.
O. Saukh
2009
Ph.D. Thesis: Efficient Algorithms for Structuring Wireless Sensor Networks
Berlin, Germany

2008

O. Saukh, R. Sauter, P. J. Marrón
2008
Time-Bounded and Space-Bounded Sensing in Wireless Sensor Networks
Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems (DCOSS)
pp 357–371
Springer-Verlag
Most papers on sensing in wireless sensor networks use only very simple sensors, e.g. humidity or temperature, to illustrate their concepts. However, in a large number of scenarios including structural health monitoring, more complex sensors that usually employ medium to high frequency sampling and post-processing are required. Additionally, to capture an event completely several sensors of different types are needed which have to be in range of the event and used in a timely manner. We study the problem of time-bounded and space-bounded sensing where parallel use of different sensors on the same node is impossible and not all nodes possess all required sensors. We provide a model formalizing the requirements and present algorithms for spatial grouping and temporal scheduling to tackle these problems.
M. Gauger, O. Saukh, M. Handte, P. J. Marrón, A. Heydlauff, K. Rothermel
2008
Sensor-based clustering for indoor applications
5th IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON)
pp 478–486
The lifetime requirements on wireless sensor networks often require the redundant deployment of sensor nodes with appropriate management mechanisms based on node clustering. Yet, existing clustering approaches do not take the primary task of sensor networks into account: performing relevant measurements. They usually form 'arbitrary' clusters, e.g., using connectivity information, and thus, the resulting measurements are often of only limited use to the applications. This problem can be avoided by considering application-specific semantics. For indoor applications, the notion of a room provides a natural unit of clustering since walls are constructed deliberately to ensure locality. This paper shows that it is feasible to automatically create clusters that reflect boundaries between rooms by analyzing the measurements of inexpensive, broadly available sensors. The paper first analyzes the applicability of statistical clustering methods and based on this analysis, it proposes and evaluates a lightweight approach to determine clusters in real deployments.
O. Saukh, R. Sauter, J. Meyer, P. J. Marrón
2008
MoteFinder: a deployment tool for sensor networks
Proceedings of the ACM Workshop on Real-World Wireless Sensor Networks (REALWSN)
pp 41–45
The support for the actual deployment of wireless sensor networks is, notwithstanding an increased interest and work in this field, still an underdeveloped area of research. We discuss the use of two simple objects built from household materials - a cantenna and a tinfoil cylinder - to increase the directivity of an antenna of a standard mote. This MoteFinder can be used in a variety of applications including node localization and as a tool for selective communication with groups of nodes. We show in our evaluation that both devices provide a good sense of direction in indoor and outdoor scenarios and provide a foundation for future research.
O. Saukh, R. Sauter, M. Gauger, P. J. Marrón, Kurt Rothermel
2008
On Boundary Recognition without Location Information in Wireless Sensor Networks
Proceedings of the 7th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)
pp 207–218
Boundary recognition is an important and challenging issue in wireless sensor networks when no coordinates or distances are available. The distinction between inner and boundary nodes of the network can provide valuable knowledge to a broad spectrum of algorithms. This paper tackles the challenge of providing a scalable and range-free solution for boundary recognition that does not require a high node density. Our solution approximates the boundary of the sensor network by determining the inner nodes using geometric constructions that guarantee that, for a given d, a node lies inside of the construction for a d-quasi unit disk graph model of the wireless sensor network. Moreover, such geometric constructions make it possible to compute a guaranteed distance from a node to the boundary. We provide a thorough evaluation of our approach and show that it is applicable to dense as well as sparse deployments.
M. Gauger, P. J. Marrón, M. Handte, O. Saukh, D. Minder, A. Lachenmann, Kurt Rothermel
2008
Integrating sensor networks in pervasive computing environments using symbolic coordinates
Proceedings of the 3rd International Conference on Communication System Software and Middleware (COMSWARE)
pp 564–573
Wireless sensor networks can monitor different types of physical phenomena and are able to provide a diverse set of context data to interested clients. Allowing mobile pervasive computing devices to access such data requires solutions for routing messages between mobile devices and the static sensor network. This paper presents a novel approach that addresses this problem with the help of symbolic coordinates. It requires only a small amount of topology information distributed in the network and allows mobile devices to send messages to arbitrary areas. The routing task is split among the client nodes, which specify a symbolic source route, and the sensor nodes that handle node-to-node routing. The paper describes the algorithm, specific challenges associated with its design and gives an extensive evaluation of the approach and its properties, showing that the use of symbolic coordinates in these environments is a viable alternative to more traditional types of routing.

2007

A. Lachenmann, P. J. Marrón, M. Gauger, D. Minder, O. Saukh, K. Rothermel
2007
Removing the Memory Limitations of Sensor Networks with Flash-Based Virtual Memory
Proceedings of the 2nd ACM EuroSys Conference
pp 131–144
Virtual memory has been successfully used in different domains to extend the amount of memory available to applications. We have adapted this mechanism to sensor networks, where, traditionally, RAM is a severely constrained resource. In this paper we show that the overhead of virtual memory can be significantly reduced with compile-time optimizations to make it usable in practice, even with the resource limitations present in sensor networks. Our approach, ViMem, creates an efficient memory layout based on variable access traces obtained from simulation tools. This layout is optimized to the memory access patterns of the application and to the specific properties of the sensor network hardware. Our implementation is based on TinyOS. It includes a pre-compiler for nesC code that translates virtual memory accesses into calls of ViMem's runtime component. ViMem uses flash memory as secondary storage. In order to evaluate our system we have modified nontrivial existing applications to make use of virtual memory. We show that its runtime overhead is small even for large data sizes.
A. Lachenmann, P. J. Marrón, D. Minder, O. Saukh, M. Gauger, K. Rothermel
2007
Versatile Support for Efficient Neighborhood Data Sharing
Proceedings of the 4th European Conference on Wireless Sensor Networks (EWSN)
pp 1–16
Many applications in wireless sensor networks rely on data from neighboring nodes. However, the effort for developing efficient solutions for sharing data in the neighborhood is often substantial. Therefore, we present a general-purpose algorithm for this task that makes use of the broadcast nature of radio transmission to reduce the number of packets. We have integrated this algorithm into TinyXXL, a programming language extension for data exchange. This combined system offers seamless support both for data exchange among the components of a single node and for efficient neighborhood data sharing. We show that compared to existing solutions, such as Hood, our approach further reduces the work of the application developer and provides greater efficiency.

2006

A. Lachenmann, P. J. Marrón, D. Minder, M. Gauger, O. Saukh, K. Rothermel
2006
TinyXXL: Language and Runtime Support for Cross-Layer Interactions
Proceedings of the 3rd IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON)
pp 178–187
In the area of wireless sensor networks, cross-layer interactions are often preferred to strictly layered architectures. However, architectural properties such as modularity and the reusability of components suffer from such optimizations. In this paper we present TinyXXL that provides programming abstractions for data exchange, a form of cross-layer interaction with a large potential for optimizations. Our approach decouples components providing and using data, and it allows for automatic optimizations of applications composed of reusable components. Its runtime representation is efficient regarding memory consumption and processing overhead.
J. Meyer, R. Bischoff, O. Saukh, G. Feltrin
2006
A Low Power Wireless Sensor Network for Structural Health Monitoring
Proceedings of the 3rd International Conference on Bridge Maintenance (IABMAS)
G. Feltrin, J. Meyer, R. Bischoff, O. Saukh
2006
A Wireless Sensor Network for Force Monitoring of Cable Stays
Proceedings of the 3rd International Conference on Bridge Maintenance (IABMAS)
P. J. Marrón, R. Sauter, O. Saukh, M. Gauger, K. Rothermel
2006
Challenges of Complex Data Processing in Real World Sensor Network Deployments
Proceedings of the ACM Workshop on Real-World Wireless Sensor Networks (REALWSN)
pp 43–47
Long-term deployments of wireless sensor networks so far have been focused on the periodic gathering of simple sensor readings. However, technological advances allow working with more complex types of data that also create larger data volumes. In this paper we use a real world engineering application to identify a series of challenges related to complex data processing in sensor networks. We present a classification of these challenges and outline a set of preliminary solutions that we are currently in the process of developing for our motivating application.
O. Saukh, P. J. Marrón, A. Lachenmann, M. Gauger, D. Minder, K. Rothermel
2006
Generic Routing Metric and Policies for WSNs
Proceedings of the 3rd European Workshop on Wireless Sensor Networks (EWSN)
pp 99–114
Energy-aware algorithms have proven to be a crucial part of sensor network applications, especially if they are required to operate for extended periods of time. Among these, efficient routing algorithms are of utter importance since their effect can be experienced by all other layers. Thus, the optimization and accurate prediction of the lifetime of the system can only be performed in the presence of accurate execution models that take energy consumption into account. In this paper, we propose a generic routing metric and associated policies that encompass most other existing metrics in the literature and use this model for the optimal construction of a routing tree to the sink. We also provide experimental results that show the benefits of using our novel metric.
P. J. Marrón, M. Gauger, A. Lachemannn, D. Minder, O. Saukh, K. Rothermel
2006
FlexCup: A Flexible and Efficient Code Update Mechanism for Sensor Networks
3rd European Workshop on Wireless Sensor Networks (EWSN)
pp 212–227
The ability to update the program code installed on wireless sensor nodes plays an import role in the highly dynamic environments sensor networks are often deployed in. Such code update mechanisms should support flexible reconfiguration and adaptation of the sensor nodes but should also operate in an energy and time efficient manner. In this paper, we present FlexCup, a flexible code update mechanism that minimizes the energy consumed on each sensor node for the installation of arbitrary code changes. We describe two different versions of FlexCup and show, using a precise hardware emulator, that our mechanism is able to perform updates up to 8 times faster than related code update algorithms found in the literature, while consuming only an eighth of the energy.

2005

P. J. Marrón, D. Minder, A. Lachenmann, O. Saukh, Kurt Rothermel
2005
Generic Model and Architecture for Cooperating Objects in Sensor Network Environments
Proceedings of the 12th International Conference on Telecommunications (ICT)
Also published in African Journal of Telecommunications, 2006
The complexity and heterogeneity of cooperating object applications in ubiquitous environments or of applications in the sensor network domain require the use of generic models and architectures. These architectures should provide support for the following three key issues: flexible installation, management and reconfiguration of components in the system; optimization strategies whose implementation usually involves the proper management of cross-layer information; and proper adaptation techniques that allow for the self-configuration of nodes and components in the system with minimal human intervention. In this paper, we present one possible instance of such a generic model and architecture and show its applicability using Sustainable Bridges, a sensor network application that requires the analysis of complex sensor data to achieve its goal of effectively monitoring bridges for the detection of structural defects.
P. J. Marrón, O. Saukh, M. Krüger, C. Grosse
2005
Sensor Network Issues in the Sustainable Bridges Project
European Projects Session of the 2nd European Workshop on Wireless Sensor Networks
2005
P. J. Marrón, A. Lachenmann, D. Minder, M. Gauger, O. Saukh, K. Rothermel
2005
Management and Configuration Issues for Sensor Networks
pp 235–253
Special Issue: Wireless Sensor Networks
In this paper, we define three of the key issues that need to be solved in order to provide efficient management and configuration of applications and system software in sensor networks: the distribution and management of roles within the network, efficient code distribution algorithms, and efficient on-the-fly code update algorithms for sensor networks. The first issue is motivated by the increasing heterogeneity of sensor network applications and their need for more complex (nonhomogeneous) network topologies and structures. The second one is motivated by the intrinsic energy constraint issues and, in general, the resource limitation of sensor networks. Finally, the third one is needed due to the nature of monitoring applications and optimization needs from applications that should be able to efficiently incorporate code updates so that the network can adapt to its surroundings on the fly. In this paper we present related work and some results for each of these issues as we have dealt with them within the TinyCubus project.
P. J. Marrón, M. Gauger, A. Lachenmann, D. Minder, O. Saukh, K. Rothermel
2005
Adaptive System Software Support for Cooperating Objects
Workshop on Smart Object Systems
2005
Efficient system software support is essential for cooperating object applications in order to cope with the complexity and heterogeneity of typical scenarios in this domain. In this paper, we argue that adaptation capabilities should be an integral part of such system software and present the TinyCubus framework as one possible solution that provides the features required of system software for cooperating objects.

Posters and Demos

D. Hasenfratz, T. Arn, I. de Concini, O. Saukh, L. Thiele
2015
Demo Abstract: Health-Optimal Routing in Urban Areas
Demos and Posters of IPSN'15
D. Hasenfratz, O. Saukh, C. Walser, C. Hueglin, M. Fierz, L. Thiele
2013
Poster Abstract: Revealing the Limits of Spatio-Temporal High-Resolution Pollution Maps
Demos and Posters of SenSys'13
M. Zimmerling, F. Ferrari, R. Lim, O. Saukh, F. Sutton, R. Da Forno, R. S. Schmid, M. A. Wyss
2013
Poster Abstract: A Reliable Wireless Nurse Call System: Overview and Pilot Results from a Summer Camp for Teenagers with Duchenne Muscular Dystrophy
Demos and Posters of SenSys'13
O. Saukh, D. Hasenfratz, A. Noori, T. Ulrich, L. Thiele
2012
Demo Abstract: Route Selection of Mobile Sensors for Air Quality Monitoring
Demos and Posters of EWSN'12