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2010 | Buch

Radio Interferometric Angle of Arrival Estimation Kapitel lesen Erstes Kapitel lesen

Wireless Sensor Networks

7th European Conference, EWSN 2010, Coimbra, Portugal, February 17-19, 2010. Proceedings

herausgegeben von: Jorge Sá Silva, Bhaskar Krishnamachari, Fernando Boavida

Verlag: Springer Berlin Heidelberg

Buchreihe : Lecture Notes in Computer Science

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

It is our great pleasure to present the proceedings of the European Conference on Wireless Sensor Networks 2010 (EWSN 2010). As the field of wireless sensor networks matures, new design concepts, experim- tal and theoretical findings, and applications have continued to emerge at a rapid pace. As one of the leading international conferences in this area, EWSN has played a s- stantial role in the dissemination of innovative research ideas from researchers all over the globe. EWSN 2010 was organized by the University of Coimbra, Portugal, during February 17–19, 2010 and it was the seventh meeting in this series. Previous events were held in Berlin (Germany) in 2004, Istanbul (Turkey) in 2005, Zurich (Switz- land) in 2006, Delft (The Netherlands) in 2007, and Cork (Ireland) in 2009. A high-quality selection of papers made up EWSN 2010. Based on the reviews and the recommendations from the four live TPC discussions, we selected a total of 21 papers from 109 submissions (19.26% acceptance rate) for EWSN 2010. Topics of interest included hardware design and implementation, operating systems and so- ware, middleware and macroprogramming, communication and network protocols, information and signal processing, fundamental theoretical limits and algorithms, prototypes, field experiments, testbeds, novel applications, including urban sensing, security and fault-tolerance. Putting together EWSN 2010 was a team effort. We would like to thank the P- gram Committee members, the reviewers, our sponsors, all authors, and the Organ- ing Committee for their respective contributions.

Inhaltsverzeichnis

Frontmatter

Localization, Synchronization and Compression

Radio Interferometric Angle of Arrival Estimation
Abstract
Several localization algorithms exist for wireless sensor networks that use angle of arrival measurements to estimate node position. However, there are limited options for actually obtaining the angle of arrival using resource-constrained devices. In this paper, we describe a radio interferometric technique for determining bearings from an anchor node to any number of target nodes at unknown positions. The underlying idea is to group three of the four nodes that participate in a typical radio interferometric measurement together to form an antenna array. Two of the nodes transmit pure sinusoids at close frequencies that interfere to generate a low-frequency beat signal. The phase difference of the measured signal between the third array node and the target node constrains the position of the latter to a hyperbola. The bearing of the node can be estimated by the asymptote of the hyperbola. The bearing estimation is carried out by the node itself, hence the method is distributed, scalable and fast. Furthermore, this technique does not require modification of the mote hardware because it relies only on the radio. Experimental results demonstrate that our approach can estimate node bearings with an accuracy of approximately 3° in 0.5 sec.
Isaac Amundson, Janos Sallai, Xenofon Koutsoukos, Akos Ledeczi
Phoenix: An Epidemic Approach to Time Reconstruction
Abstract
Harsh deployment environments and uncertain run-time conditions create numerous challenges for postmortem time reconstruction methods. For example, motes often reboot and thus lose their clock state, considering that the majority of mote platforms lack a real-time clock. While existing time reconstruction methods for long-term data gathering networks rely on a persistent basestation for assigning global timestamps to measurements, the basestation may be unavailable due to hardware and software faults. We present Phoenix, a novel offline algorithm for reconstructing global timestamps that is robust to frequent mote reboots and does not require a persistent global time source. This independence sets Phoenix apart from the majority of time reconstruction algorithms which assume that such a source is always available. Motes in Phoenix exchange their time-related state with their neighbors, establishing a chain of transitive temporal relationships to one or more motes with references to the global time. These relationships allow Phoenix to reconstruct the measurement timeline for each mote. Results from simulations and a deployment indicate that Phoenix can achieve timing accuracy up to 6 ppm for 99% of the collected measurements. Phoenix is able to maintain this performance for periods that last for months without a persistent global time source. To achieve this level of performance for the targeted environmental monitoring application, Phoenix requires an additional space overhead of 4% and an additional duty cycle of 0.2%.
Jayant Gupchup, Douglas Carlson, Răzvan Musăloiu-E., Alex Szalay, Andreas Terzis
Trimming the Tree: Tailoring Adaptive Huffman Coding to Wireless Sensor Networks
Abstract
Nodes in wireless sensor networks are generally designed to operate on a limited energy budget, and must consciously use the available charge to allow for long lifetimes. As the radio transceiver is the predominant power consumer on current node platforms, the minimization of its activity periods and efficient use of the radio channel are major targets for optimization. Data compression is a viable option to increase the packet information density, resulting in reduced transmission durations and thus allowing for an optimized channel utilization. The computational and memory demands of many current compression algorithms however hamper their applicability on sensor nodes.
In this paper, we present a novel variant of the adaptive Huffman coding algorithm, operating on reduced code table sizes and thus significantly alleviating the resource demands for storing and updating the code table during runtime. An implementation for tmote sky hardware proves its adequacy to the capabilities of sensor nodes, and we present its achievable compression gains and energy requirements in both simulation and real world experiments. Results anticipate that overall energy savings can be achieved when transferring packets of reduced sizes, even when increased CPU utilization is incurred.
Andreas Reinhardt, Delphine Christin, Matthias Hollick, Johannes Schmitt, Parag S. Mogre, Ralf Steinmetz

Networking – I

Querying Dynamic Wireless Sensor Networks with Non-revisiting Random Walks
Abstract
The simplicity and low-overhead of random walks have made them a popular querying mechanism for Wireless Sensor Networks. However, most of the related work is of theoretical nature and present two important limitations. First, they are mainly based on simple random walks, where at each step, the next hop is selected uniformly at random among neighbors. This mechanism permits analytical tractability but wastes energy by unnecessarily visiting neighbors that have been visited before. Second, the studies usually assume static graphs which do not consider the impact of link dynamics on the temporal variation of neighborhoods.
In this work we evaluate the querying performance of Non-Revisiting Random Walks (NRWs). At each step, NRWs avoid re-visiting neighbors by selecting the next hop randomly among the neighbors with the minimum number of visits. We evaluated Pull-only and Pull-Push queries with NRWs in two ways: (i) on a test-bed with 102 tmotes and (ii) on a simulation environment considering link unreliability and asymmetry. Our main results show that non-revisiting random walks significantly improve upon simple random walks in terms of querying cost and load balancing, and that the push-pull mechanism is more efficient than the push-only for query resolution.
Marco Zuniga, Chen Avin, Manfred Hauswirth
TARF: A Trust-Aware Routing Framework for Wireless Sensor Networks
Abstract
Multi-hop routing in wireless sensor networks (WSNs) offers little protection against deception through replaying routing information. This defect can be taken advantage of by an adversary to misdirect significant network traffic, resulting in disastrous consequences. It cannot be solved solely by encryption or authentication techniques. To secure multi-hop routing in WSNs against intruders exploiting the replay of routing information, we propose TARF, a trust-aware routing framework for WSNs. Not only does TARF significantly reduce negative impacts from these attackers, it is also energy-efficient with acceptable overhead. It incorporates the trustworthiness of nodes into routing decisions and allows a node to circumvent an adversary misdirecting considerable traffic with a forged identity attained through replaying. Both our empirical and simulated experimental results indicate that TARF satisfactorily performs routing and is resilient against attacks by exploiting the replay of routing information.
Guoxing Zhan, Weisong Shi, Julia Deng
Low-Overhead Dynamic Multi-channel MAC for Wireless Sensor Networks
Abstract
Most of the existing popular MAC protocols for Wireless Sensor Networks (WSN) only use a single channel for relaying data. Most popular platforms however are equipped with a radio chip capable of switching its channel, and are therefor not restricted to a single-channel operation. Operating on multiple channels can increase bandwidth and can provide robustness against external interference. We argue that this feature is not only useful for dense, high-throughput WSNs but also for sparser networks with low average data rates but with occasional traffic bursts. We present MuChMAC, a low-overhead Multi-Channel MAC protocol which uses a combination of TDMA and asynchronous MAC techniques to exploit multi-channel operation without the need for coordination or tight synchronization between nodes. We describe an interface to scale MuChMAC’s duty cycle to adapt to varying traffic conditions or energy constraints. We demonstrate MuChMAC’s usefulness on a testbed consisting out Sentilla JCreate motes running it as the MAC layer for Contiki-based applications.
Joris Borms, Kris Steenhaut, Bart Lemmens
Exploiting Overlapping Channels for Minimum Power Configuration in Real-Time Sensor Networks
Abstract
Multi-channel communications can effectively reduce channel competition and interferences in a wireless sensor network, and thus achieve increased throughput and improved end-to-end delay guarantees with reduced power consumption. However, existing work relies only on a small number of orthogonal channels, resulting in degraded performance when a large number of data flows need to be transmitted on different channels. In this paper, we conduct empirical studies to investigate the interferences among overlapping channels. Our results show that overlapping channels can also be utilized for improved real-time performance if the node transmission power is carefully configured. In order to minimize the overall power consumption of a network with multiple data flows under end-to-end delay constraints, we formulate a constrained optimization problem to configure the transmission power level for every node and assign overlapping channels to different data flows. Since the optimization problem has an exponential computational complexity, we then present a heuristic algorithm designed based on Simulated Annealing to find a suboptimal solution. Our empirical results on a 25-mote testbed demonstrate that our algorithm achieves better real-time performance and less power consumption than two baselines including a scheme using only orthogonal channels.
Xiaodong Wang, Xiaorui Wang, Guoliang Xing, Yanjun Yao

New Directions

Privacy-Preserving Reconstruction of Multidimensional Data Maps in Vehicular Participatory Sensing
Abstract
The proliferation of sensors in devices of frequent use, such as mobile phones, offers unprecedented opportunities for forming self-selected communities around shared sensory data pools that enable community specific applications of mutual interest. Such applications have recently been termed participatory sensing. An important category of participatory sensing applications is one that construct maps of different phenomena (e.g., traffic speed, pollution) using vehicular participatory sensing. An example is sharing data from GPS-enabled cell-phones to map traffic or noise patterns. Concerns with data privacy are a key impediment to the proliferation of such applications. This paper presents theoretical foundations, a system implementation, and an experimental evaluation of a perturbation-based mechanism for ensuring privacy of location-tagged participatory sensing data while allowing correct reconstruction of community statistics of interest (computed from shared perturbed data). The system is applied to construct accurate traffic speed maps in a small campus town from shared GPS data of participating vehicles, where the individual vehicles are allowed to “lie” about their actual location and speed at all times. An extensive evaluation demonstrates the efficacy of the approach in concealing multi-dimensional, correlated, time-series data while allowing for accurate reconstruction of spatial statistics.
Nam Pham, Raghu K. Ganti, Yusuf S. Uddin, Suman Nath, Tarek Abdelzaher
Gathering Sensor Data in Home Networks with IPFIX
Abstract
New developments in military, health and home areas call for new approaches for data acquisition in real-time. Such application areas frequently include challenging requirements for collection, processing and analysis of environmental data. Wireless Sensor Networks can collect such environmental data efficiently. Collected sensor node data needs to be transmitted in an efficient way due to limitations of sensor node resources in battery power and available bandwidth. In this paper, we present a method for efficient transmission of sensor measurement data using the IETF standard IPFIX. We show that its template based design is suitable for efficient transmission of senor data with low bandwidth consumption. In this paper, we present the protocol and its implementation in Wireless Sensor Networks (WSNs). Additionally, a header compression scheme is introduced which further reduces communication cost during data transmission.
Thomas Kothmayr, Corinna Schmitt, Lothar Braun, Georg Carle
Sensing for Stride Information of Sprinters
Abstract
Accurate sprint-related information, such as stride times, stance times, stride lengths, continuous Centre-of-Mass (CoM) displacements and split times of sprinters are important to both sprint coaches and biomechanics researchers. These information are traditionally captured using camera-based systems which are very expensive and time-consuming to setup. This paper investigates - through a series of experiments - whether an integrated sensing system would provide a practical, cost-effective alternative to measuring stride-related information of sprinters. The results show that the system achieves an accuracy within 5ms for stance time and stride time measurements, and ~10cm for localisation-related information such as CoM forward displacement and CoM stride displacement (i.e. stride length).
Lawrence Cheng, Huiling Tan, Gregor Kuntze, Kyle Roskilly, John Lowe, Ian N. Bezodis, Stephen Hailes, Alan Wilson, David G. Kerwin

Programming & Architecture

Wiselib: A Generic Algorithm Library for Heterogeneous Sensor Networks
Abstract
One unfortunate consequence of the success story of wireless sensor networks (WSNs) in separate research communities is an ever-growing gap between theory and practice. Even though there is a increasing number of algorithmic methods for WSNs, the vast majority has never been tried in practice; conversely, many practical challenges are still awaiting efficient algorithmic solutions. The main cause for this discrepancy is the fact that programming sensor nodes still happens at a very technical level. We remedy the situation by introducing Wiselib, our algorithm library that allows for simple implementations of algorithms onto a large variety of hardware and software. This is achieved by employing advanced C++ techniques such as templates and inline functions, allowing to write generic code that is resolved and bound at compile time, resulting in virtually no memory or computation overhead at run time.
The Wiselib runs on different host operating systems, such as Contiki, iSense OS, and ScatterWeb. Furthermore, it runs on virtual nodes simulated by Shawn. For any algorithm, the Wiselib provides data structures that suit the specific properties of the target platform. Algorithm code does not contain any platform-specific specializations, allowing a single implementation to run natively on heterogeneous networks.
In this paper, we describe the building blocks of the Wiselib, and analyze the overhead. We demonstrate the effectiveness of our approach by showing how routing algorithms can be implemented. We also report on results from experiments with real sensor-node hardware.
Tobias Baumgartner, Ioannis Chatzigiannakis, Sándor Fekete, Christos Koninis, Alexander Kröller, Apostolos Pyrgelis
Selective Reprogramming of Mobile Sensor Networks through Social Community Detection
Abstract
We target application domains where the behavior of animals or humans is monitored using wireless sensor network (WSN) devices. The code on these devices is updated frequently, as scientists acquire in-field data and refine their hypotheses. Wireless reprogramming is therefore fundamental to avoid the (expensive) re-collection of the devices. Moreover, the code carried by the monitored individuals often depends on their characteristics, e.g., the behavior or preferred habitat. We propose a selective reprogramming approach that simplifies and automates the process of delivering a code update to a target subset of nodes. Target selection is expressed through constraints injected in the WSN, triggering automatic dissemination of code updates whenever verified. Update dissemination relies on a novel protocol exploiting the social behavior of the monitored individuals. We evaluate our approach through simulation, using real-world animal and human traces. The results shows that our protocol is able to capture the social network structure in a way comparable to existing offline algorithms with global knowledge while allowing runtime adaptation to community structure changes, and that existing dissemination approaches based on gossip generate up to three times more network overhead than our socially-aware dissemination.
Bence Pásztor, Luca Mottola, Cecilia Mascolo, Gian Pietro Picco, Stephen Ellwood, David Macdonald
Improving Sensornet Performance by Separating System Configuration from System Logic
Abstract
Many sensor network protocols are self-configuring, but independent self-configuration at different layers often results in suboptimal performance. We present Chi, a full-system configuration architecture that separates system logic from system configuration. Drawing from concepts in artificial intelligence, Chi allows full-system configuration that meets both changing application demands and changing environmental conditions. We show that configuration policies using Chi can improve throughput and energy efficiency without adding dependencies between layers. Our results show that sensornet systems can use Chi to adapt to changing conditions at all layers of the system, thus meeting the requirements of heterogeneous and continuously changing system conditions.
Niclas Finne, Joakim Eriksson, Nicolas Tsiftes, Adam Dunkels, Thiemo Voigt
Virtualising Testbeds to Support Large-Scale Reconfigurable Experimental Facilities
Abstract
Experimentally driven research for wireless sensor networks is invaluable to provide benchmarking and comparison of new ideas. An increasingly common tool in support of this is a testbed composed of real hardware devices which increases the realism of evaluation. However, due to hardware costs the size and heterogeneity of these testbeds is usually limited. In addition, a testbed typically has a relatively static configuration in terms of its network topology and its software support infrastructure, which limits the utility of that testbed to specific case-studies. We propose a novel approach that can be used to (i) interconnect a large number of small testbeds to provide a federated testbed of very large size, (ii) support the interconnection of heterogeneous hardware into a single testbed, and (iii) virtualise the physical testbed topology and thus minimise the need to relocate devices. We present the most important design issues of our approach and evaluate its performance. Our results indicate that testbed virtualisation can be achieved with high efficiency and without hindering the realism of experiments.
Tobias Baumgartner, Ioannis Chatzigiannakis, Maick Danckwardt, Christos Koninis, Alexander Kröller, Georgios Mylonas, Dennis Pfisterer, Barry Porter

Link Reliability

Mitigating the Effects of RF Interference through RSSI-Based Error Recovery
Abstract
On a common sensor node platform (Telos) we sample RSSI with high frequency during packet reception. We find that a packet collision (RF interference) often manifests as a measurable, temporal increase in RSSI. We investigate how the receiver can use this information to detect interference and, through temporal correlation, estimate the bit error positions in a corrupted packet. In an experimental study in two testbeds and several realistic BAN scenarios we show that a simple threshold-based algorithm often succeeds in estimating a large fraction of the bit error positions correctly. We develop an ARQ scheme that utilizes the error estimates to reduce the size of retransmitted packets. For this ARQ scheme we present an analytical model and verify it experimentally. Our results indicate that in comparison with a standard Send-and-Wait ARQ the expected number of bits per transmission can be reduced significantly (in our measurements by up to 14.7 %).
Jan-Hinrich Hauer, Andreas Willig, Adam Wolisz
F-LQE: A Fuzzy Link Quality Estimator for Wireless Sensor Networks
Abstract
Radio Link Quality Estimation (LQE) is a fundamental building block for Wireless Sensor Networks, namely for a reliable deployment, resource management and routing. Existing LQEs (e.g. PRR, ETX, Four-bit, and LQI) are based on a single link property, thus leading to inaccurate estimation. In this paper, we propose F-LQE, that estimates link quality on the basis of four link quality properties: packet delivery, asymmetry, stability, and channel quality. Each of these properties is defined in linguistic terms, the natural language of Fuzzy Logic. The overall quality of the link is specified as a fuzzy rule whose evaluation returns the membership of the link in the fuzzy subset of good links. Values of the membership function are smoothed using EWMA filter to improve stability. An extensive experimental analysis shows that F-LQE outperforms existing estimators.
Nouha Baccour, Anis Koubâa, Habib Youssef, Maissa Ben Jamâa, Denis do Rosário, Mário Alves, Leandro B. Becker
On the Mechanisms and Effects of Calibrating RSSI Measurements for 802.15.4 Radios
Abstract
Wireless sensor network protocols and applications, including those used for localization, topology control, link scheduling, and link quality estimation, make extensive use of Received Signal Strength Indication (RSSI) measurements. In this paper we show that inaccuracies in the RSSI values reported by widely used 802.15.4 radios, such as the CC2420 and the AT86RF230, have profound impact on these protocols and applications. Furthermore, we experimentally derive the response curves which translate actual RSSI values to the raw RSSI readings that the radios report and show that they contain non-linear and even non-injective regions. Fortunately, these curves are consistent across radios of the same model, making RSSI calibration practical. We present a calibration mechanism that removes the artifacts in the raw RSSI measurements, including ambiguities created by the non-injective regions in the response curves, and generates calibrated RSSI readings that are linear. This calibration removes many of the outliers generated when raw RSSI readings are used to estimate Signal to Noise (and Interference) ratios, estimate radio model parameters, and perform RF-based localization.
Yin Chen, Andreas Terzis
Making Sensornet MAC Protocols Robust against Interference
Abstract
Radio interference may lead to packet losses, thus negatively affecting the performance of sensornet applications. In this paper, we experimentally assess the impact of external interference on state-of-the-art sensornet MAC protocols. Our experiments illustrate that specific features of existing protocols, e.g., hand-shaking schemes preceding the actual data transmission, play a critical role in this setting. We leverage these results by identifying mechanisms to improve the robustness of existing MAC protocols under interference. These mechanisms include the use of multiple hand-shaking attempts coupled with packet trains and suitable congestion backoff schemes to better tolerate interference. We embed these mechanisms within an existing X-MAC implementation and show that they considerably improve the packet delivery rate while keeping the power consumption at a moderate level.
Carlo Alberto Boano, Thiemo Voigt, Nicolas Tsiftes, Luca Mottola, Kay Römer, Marco Antonio Zúñiga

Networking – II

MaxMAC: A Maximally Traffic-Adaptive MAC Protocol for Wireless Sensor Networks
Abstract
Energy efficiency is a major concern in the design of Wireless Sensor Networks (WSNs) and their communication protocols. As the radio transceiver typically accounts for a major portion of a WSN node’s power consumption, researchers have proposed Energy-Efficient Medium Access (E 2-MAC) protocols that switch the radio transceiver off for a major part of the time. Such protocols typically trade off energy-efficiency versus classical quality of service parameters (throughput, latency, reliability). Today’s E 2-MAC protocols are able to deliver little amounts of data with a low energy footprint, but introduce severe restrictions with respect to throughput and latency. Regrettably, they yet fail to adapt to varying traffic load at run-time.
This paper presents MaxMAC, an E 2-MAC protocol that targets at achieving maximal adaptivity with respect to throughput and latency. By adaptively tuning essential parameters at run-time, the protocol reaches the throughput and latency of energy-unconstrained CSMA in high-traffic phases, while still exhibiting a high energy-efficiency in periods of sparse traffic. The paper compares the protocol against a selection of today’s E 2-MAC protocols and evaluates its advantages and drawbacks.
Philipp Hurni, Torsten Braun
Energy-Aware Sparse Approximation Technique (EAST) for Rechargeable Wireless Sensor Networks
Abstract
Due to non-homogeneous spread of sunlight, sensing nodes typically have non-uniform energy profiles in rechargeable Wireless Sensor Networks (WSNs). An energy-aware work load distribution is therefore necessary for good data accuracy while ensuring an energy-neutral operation. Recently proposed signal approximation strategies, in form of Compressive Sensing, assume uniform sampling and thus cannot be deployed to facilitate energy neutral operation in rechargeable WSNs. We propose a sparse approximation driven sensing technique (EAST) that adapts sensor node sampling workload according to solar energy availability. To the best of our knowledge, we are the first to propose sparse approximation for modeling energy-aware work load distribution in order to improve signal approximation from rechargeable WSNs. Experimental result, by using data from an outdoor WSN deployment, suggests that EAST significantly improves the approximation accuracy while supporting approximately 50% higher sensor on-time compared to an approach that assumes uniform energy profile of the nodes.
Rajib Rana, Wen Hu, Chun Tung Chou
An Adaptive Strategy for Energy-Efficient Data Collection in Sparse Wireless Sensor Networks
Abstract
Sparse wireless sensor networks (WSNs) are being effectively used in several applications, which include transportation, urban safety, environment monitoring, and many others. Sensor nodes typically transfer acquired data to other nodes and base stations. Such data transfer operations are critical, especially in sparse WSNs with mobile elements. In this paper, we investigate data collection in sparse WSNs by means of special nodes called Mobile Data Collectors (MDCs), which visit sensor nodes opportunistically to gather data. As contact times and other information are not known a priori, the discovery of an incoming MDC by the static sensor node becomes a critical task. Ideally, the discovery strategy should be able to correctly detect contacts while keeping a low energy consumption. In this paper, we propose an adaptive discovery strategy that exploits distributed independent reinforcement learning to meet these two necessary requirements. We carry out an extensive simulation analysis to demonstrate the energy efficiency and effectiveness of the proposed strategy. The obtained results show that our solution provides superior performance in terms of both discovery efficiency and energy conservation.
Mario Di Francesco, Kunal Shah, Mohan Kumar, Giuseppe Anastasi
Backmatter
Metadaten
Titel
Wireless Sensor Networks
herausgegeben von
Jorge Sá Silva
Bhaskar Krishnamachari
Fernando Boavida
Copyright-Jahr
2010
Verlag
Springer Berlin Heidelberg
Electronic ISBN
978-3-642-11917-0
Print ISBN
978-3-642-11916-3
DOI
https://doi.org/10.1007/978-3-642-11917-0

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