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Housewarming party 
Moving of members of the Pervasive System group to the other side of the corridor was finalized and this called for a small party in the new coffee room.

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Mihai Marin-Perianu successfully defended his PhD thesis 
On 6 November 2008, Mihai Marin-Perianu successfully defended his doctoral thesis entitled "Collaborative Wireless Sensor Networks in Industrial and Business Processes”. The research has been performed under supervision of Dr. Paul Havinga (assistant-promotor)

Complete thesis can be found at:

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Supriyo Chatterjea successfully defended his PhD thesis 
On 26 September 2008, Supriyo Chatterjea successfully defended his doctoral thesis entitled "Distributed and Self-Organizing Data Management Strategies for Wireless Sensor Networks. A Cross-Layered Approach”. The research has been performed under supervision of Dr. Paul Havinga (assistant-promotor).

Complete thesis can be found at: http://eprints.eemcs.utwente.nl/13614/

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SENSEI project begins 
SENSEI (Integrating the Physical with the Digital World of the Network of the Future) is an Integrated Project in the EU's Seventh Framework Programme , in the ICT (Information and Communication Technologies). Thematic Priority of Challenge 1: Pervasive and Trusted Network and Service Infrastructures: ICT-2007.1.1: The Network of the Future.

The SENSEI project (Contract no. 215923) started on 1st January 2008, and is set out to run for three years. 19 partners from 11 European countries participate in the project.

In order to realise the vision of Ambient Intelligence in a future network and service environment, heterogeneous wireless sensor and actuator networks (WS&AN) have to be integrated into a common framework of global scale and made available to services and applications via universal service interfaces. SENSEI creates an open, business driven architecture that fundamentally addresses the scalability problems for a large number of globally distributed WS&A devices. It provides necessary network and information management services to enable reliable and accurate context information retrieval and interaction with the physical environment. By adding mechanisms for accounting, security, privacy and trust it enables an open and secure market space for context-awareness and real world interaction.

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Papers recently accepted for publication 
Members of PS have recently had several publications accepted in conferences such as SECON’08, DCOSS’08, WiOpt’08 and others. Abstracts of the accepted publications are listed below.


Authors: Ozlem Durmaz Incel and Bhaskar Krishnamachari

Conference: Proceedings of Fifth Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON 2008)

Title: Enhancing the Data Collection Rate of Tree-Based Aggregation in Wireless Sensor Networks

What is the fastest rate at which we can collect a stream of aggregated data from a set of wireless sensors organized as a tree? We explore a hierarchy of techniques using realistic simulation models to address this question. We begin by considering TDMA scheduling on a single channel, reducing the original problem to minimizing the number of time slots needed to schedule each link of the aggregation tree. The second technique is to combine the scheduling with transmission power control to reduce the effects of interference.

To better cope with interference, we then study the impact of utilizing multiple frequency channels by introducing a simple receiver-based frequency and time scheduling approach. We find that for networks of about a hundred nodes, the use of multi-frequency scheduling can suffice to eliminate most of the interference. The data collection rate then becomes limited not by interference, but by the maximum degree of the routing tree. Therefore we consider finally how the data collection rate can be further enhanced by the use of degree-constrained routing trees. Considering deployments at different densities, we show that these enhancements can improve the streaming aggregated data collection by as much as 10 times compared to the baseline of single-channel data collection over non-degree constrained routing trees. Addition to our primary conclusion, in the frequency scheduling domain we evaluate the impact of different interference models on the scheduling performance and give topology-specific bounds on time slot and frequency channel requirements.


Authors: M. Marin-Perianu, C. Lombriser, O. Amft, P. Havinga, G. Tröster

Conference: Proceedings of 4th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS '08)

Title: Activity Recognition with Fuzzy-Enabled Wireless Sensor Networks

Abstract: Wireless sensor nodes can act as distributed detectors for recognizing activities online, with the final goal of assisting the users in their working environment. We propose an activity recognition architecture based on fuzzy logic, through which multiple nodes collaborate to produce a reliable recognition result from unreliable sensor data. As an extension to the regular fuzzy inference, we incorporate temporal order knowledge of the sequences of operations involved in the activities. The performance evaluation is based on experimental data from a car assembly trial. The system achieves an overall recognition performance of 0.81 recall and 0.79 precision with regular fuzzy inference, and 0.85 recall and 0.85 precision when considering temporal order knowledge. We also present early experiences with implementing the recognition system on sensor nodes. The results show that the algorithms can run online, with execution times in the order of 40ms, for the whole recognition chain, and memory overhead in the order of 1.5kB RAM.


Authors: S. Chatterjea and P. Havinga

Conference: Proceedings of 4th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS '08)

Title: An Adaptive and Autonomous Sensor Sampling Frequency Control Scheme for Energy-Efficient Data Acquisition in Wireless Sensor Networks

Abstract: Wireless sensor networks are increasingly being used in environmental monitoring applications. Collecting raw data from these networks can lead to excessive energy consumption. This is especially true when the application requires specialized sensors that have very high energy consumption, e.g. hydrological sensors for monitoring marine environments. We describe an adaptive sensor sampling scheme where nodes change their sampling frequencies autonomously based on the variability of the measured parameters. The sampling scheme also meets the user's sensing coverage requirements by using information provided by the underlying MAC protocol. This allows the scheme to automatically adapt to topology changes. Our results based on real and synthetic data sets, indicate a reduction in sensor sampling by up to 93%, reduction in message transmissions by up to 99% and overall energy savings of up to 87%. We also show that generally more than 90% of the collected readings fall within the user-defined error threshold.


Authors: Ozlem Durmaz Incel and Pierre Jansen

Conference: Proceedings of 6th Intl. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt ’08)

Title: Characterization of Multi-Channel Interference

Abstract: Multi-channel communication protocols in wireless networks usually assume perfect orthogonality between wireless channels or consider only the use of interference-free channels.

The first approach may overestimate the performance whereas the second approach may fail to utilize the spectrum efficiently.

Therefore, a more realistic approach would be the careful use of interfering channels by controlling the interference at an acceptable level. We present a methodology to estimate the packet error rate (PER) due to inter-channel interference in a wireless network. The methodology experimentally characterizes the multi-channel interference and analytically estimates it based on the observations from the experiments. Furthermore, the analytical estimation is used in simulations to derive estimates of the capacity in larger networks. Simulation results show that the achievable network capacity, which is defined as the number of simultaneous transmissions, significantly increases with realistic interfering channels compared with the use of only orthogonal channels. When we consider the same number of channels, the achievable capacity with realistic interfering channels can be close to the capacity of idealistic orthogonal channels. This shows that overlapping channels which constitute a much smaller band, provides more efficient use of the spectrum. Finally, we explore the correctness of channel orthogonality and show why this assumption may fail in a practical setting.


Authors: M. Horsman, M. Marin-Perianu, P. Jansen, P. Havinga

Conference: International IEEE Symposium on Wireless Pervasive Computing (ISWPC’08)

Title: A Simulation Framework for Evaluating Complete Reprogramming Solutions in Wireless Sensor Networks

Abstract: We propose a simulation framework developed in Simulink for analyzing the performance of code dissemination in wireless sensor networks. The complete solution relies on a three-layer network stack where the LMAC, FixTree and RMD protocols operate in conjunction. For performance evaluation, we use in our simulations the radio link quality model derived from previous field trials. In this way, we can study the impact of real network conditions (e.g. fluctuating link quality, changing

neighborhood) on the higher layer protocols and thus verify our design choices in non-idealized circumstances.


Authors: R. Marin-Perianu, C. Lombriser, M. Marin-Perianu, P. Havinga, G. Tröster

Conference: ICT Mobile and Wireless Communications Summit

Title: Towards Activity Recognition in Service-Oriented Body Area Networks

Abstract: Body Area Networks (BANs) are heterogeneous and dynamically changing collections of wireless nodes ranging from hand-held devices or smart objects in the environment to miniaturized sensor nodes integrated into garments. By using context information, such as human activity, BAN can make autonomous decisions and hide the complexities of handling the network peculiarities from the user. In this paper, we present the approach of the SENSEI project to design a service-oriented architecture enabling the inference of context information in wireless sensor and body area networks. We describe the challenges encountered in service discovery and composition, in-network processing, and integration into the Internet of the Future. As an example, we show how the recognition of activities of a worker in a car assembly site can be recognized in a distributed fashion.


Authors: Yang Zhang, Nirvana Meratnia, Paul Havinga

Book chapter: Intelligent Techniques for Warehousing and Mining Sensor Network Data, IGI Global

Title: Why General Outlier Detection Techniques do not Suffice for Wireless Sensor Networks?

Abstract: Raw sensor data collected in wireless sensor networks (WSNs) are often unreliable and inaccurate due to noise, faulty sensors and harsh environmental effects. A sensor's data that is significantly different from other data of the sensor node or the node's neighboring nodes can be declared as an outlier. Outlier detection in WSNs aims at identifying such outliers, which represent either measurement errors or interesting events. Due to numerous shortcomings, commonly used outlier detection techniques for general data seem not to be directly applicable to outlier detection in WSNs. In this chapter, we report on the current state-of-the-art of outlier detection techniques for general data and provide a comprehensive taxonomy framework. We also address the challenges of outlier detection in WSNs and explain why general outlier detection techniques do not suffice for WSNs. Furthermore, we highlight the requirements for an outlier detection technique designed specially for WSNs.

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