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3rd international symposium on information processing in sensor networks

作者： Mitra, U Sabharwal, A Univ So Calif Inst Commun Sci Dept Elect Engn Los Angeles CA 90089 USA

ISBN: (纸本)1581138466

Motivated by limited computational resources in sensor nodes, the impact of complexity constraints on the communication efficiency of sensor networks is studied. A single-parameter characterization of processing limitation of nodes in sensor networks is invoked. Specifically, the relaying nodes are assumed to "donate" only a small part of their total processor time to relay other nodes information. The amount of donated processor time is modelled by the node's ability to decode a channel code reliably at given rate (R) over bar. Focusing on a four node network, with two relays, prior work for a complexity constrained single relay network is built upon. In the proposed coding scheme, the transmitter sends a broadcast code such that the relays decode only the "coarse" information, and assist the receiver in removing ambiguity only in that information. Via numerical examples, the impact of different power constraints in the system, ranging from per node power bound to network wide power constraint is explored. As the complexity bound (R) over bar increases, the proposed scheme becomes identical to the recently proposed achievable rate by Gupta & Kumar. Both discrete memoryless and Gaussian channels are considered.

关键词： information theory relay networks sensor networks achievable rates channel capacity ad hoc wireless networks complexity constraints limited code rate

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Improved interval-based clock synchronization in sensor networks

Improved interval-based clock synchronization in sensor netw...

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3rd international symposium on information processing in sensor networks

作者： Blum, P Meier, L Thiele, L ETH Swiss Fed Inst Technol Comp Engn & Networks Lab CH-8092 Zurich Switzerland

ISBN: (纸本)1581138466

Interval-based synchronization provides the nodes of a distributed system with guaranteed bounds on a common time. This is a crucial piece of infrastructure in many distributed sensing and actuating systems. In this paper, we propose a modification to a known interval-based synchronization algorithm;our new algorithm obtains substantially better results in sensor-network scenarios by taking advantage of the typical drift diversity of the nodes' clocks. We propose a model for synchronization in ad-hoc, sporadic-communication scenarios. The model allows us to identify the worst and the best case in terms of achievable time uncertainty and to show the worst-case optimality of the discussed algorithms. Simulations show that in the average case, our modification significantly reduces the time uncertainty.

关键词： sensor networks time synchronization clock drift delay uncertainty

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Loss inference in wireless sensor networks based on data aggregation

Loss inference in wireless sensor networks based on data agg...

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3rd international symposium on information processing in sensor networks

作者： Hartl, G Li, BC Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada

ISBN: (纸本)1581138466

In this paper, we consider the problem of inferring per node loss rates from passive end-to-end measurements in wireless sensor networks. Specifically, we consider the case of inferring loss rates during the aggregation of data from a collection of sensor nodes to a sink node. Previous work has studied the general problem of network inference, which considers the cases of inferring link-based metrics in wireline networks. We show how to adapt previous work on network inference so that loss rates in wireless sensor networks may be inferred as well. This includes (1) considering the pernode, instead of per-link, loss rates;and (2) taking into account the unique characteristics of wireless sensor networks. We formulate the problem as a Maximum-Likelihood Estimation (MLE) problem and show how it can be efficiently solved using the Expectation-Maximization (EM) algorithm. The results of the inference procedure may then be utilized in various ways to effectively streamline the data collection process. Finally, we validate our analysis through simulations.

关键词： sensor networks tomography data aggregation

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Ontological Middleware for Dynamic Wireless sensor Data processing

Ontological Middleware for Dynamic Wireless Sensor Data Proc...

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3rd international Conference on sensor Technologies and Applications

作者： Gomez, Laurent Laube, Annett SAP Research France

ISBN: (纸本)9781424443093

Wireless sensor networks (WSN) raise the interest of multiple business domains. Their ability to monitor and control large physical environment made them very attractive for many application domains. Nevertheless, Wireless sensor networks encounter several technical obstacles, which may hinder their integration within business applications. Considering the fact that Wireless sensor networks produce a large and diverse amount of data, business applications may have difficulties to select and process relevant information. We distinguish two approaches which address this issue: in-network processing and data processing within dedicated middleware. Whereas in-nerwork processing mainly aims at resource saving in Wireless sensor networks, middlewares ease the definition and execution of Wireless sensor Network data processing for business applications. In this paper we propose to enhance the common middleware processing approach with the introduction of a contextual ontology. The purpose of this approach is two-fold:(i) to provide only information that match the business application interests, and (ii) to dynamically process Wireless sensor Network information in order to provide higher semantic level of information to business application.

关键词： Wireless sensor Network Event processing Ontology

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Robust distributed estimation in sensor networks using the embedded polygons algorithm

Robust distributed estimation in sensor networks using the e...

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3rd international symposium on information processing in sensor networks

作者： Delouille, V Neelamani, R Baraniuk, R Rice Univ ECE Dept Houston TX 77251 USA

ISBN: (纸本)1581138466

We propose a new iterative distributed algorithm for linear minimum mean-squared-error (LMMSE) estimation in sensor networks whose measurements follow a Gaussian hidden Markov graphical model with cycles. The embedded polygons algorithm decomposes a loopy graphical model into a number of linked embedded polygons and then applies a parallel block Gauss-Seidel iteration comprising local LMMSE estimation on each polygon (involving inversion of a small matrix) followed by an information exchange between neighboring nodes and polygons. The algorithm is robust to temporary communication faults such as link failures and sleeping nodes and enjoys guaranteed convergence under mild conditions. A simulation study indicates that energy consumption for iterative estimation increases substantially as more links fail or nodes sleep. Thus, somewhat surprisingly, energy conservation strategies such as low-powered transmission and aggressive sleep schedules could actually be counterproductive.

关键词： sensor networks distributed estimation graphical models hidden Markov models Wiener filter matrix splitting

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Nonparametric belief propagation for self-localization of sensor networks

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2005年第4期23卷 809-819页

作者： Ihler, AT Fisher, JW Moses, RL Willsky, AS MIT Informat & Decis Syst Lab Cambridge MA 02139 USA MIT Comp Sci & Artificial Intelligence Lab Cambridge MA 02139 USA Ohio State Univ Dept Elect & Comp Engn Columbus OH 43210 USA

Automatic self-localization is a critical need for the effective use of ad hoe sensor networks in military or civilian applications. In general, self-localization involves the combination of absolute location information (e.g. from a global positioning system) with relative calibration information (e.g., distance measurements between sensors) over regions of the network. Furthermore, it is generally desirable to distribute the computational burden across the network and minimize the amount of intersensor communication. We demonstrate that the information used for sensor localization is fundamentally local with regard to the network topology and use this observation to reformulate the problem within a graphical model framework. We then present and demonstrate the utility of nonparametric belief propagation (NBP), a recent generalization of particle filtering, for both estimating sensor locations and representing location uncertainties. NBP has the advantage that it is easily implemented in a distributed fashion, admits a wide variety of statistical models, and can represent multimodal uncertainty. Using simulations of small to moderately sized sensor networks, we show that NBP may be made robust to outlier measurement errors by a simple model augmentation, and that judicious message construction can result in better estimates. Furthermore, we provide an analysis of NBP's communications requirements, showing that typically only a few messages per sensor are required, and that even low bit-rate approximations of these messages can be used with little or no performance impact.

关键词： algorithms calibration distributed estimation localization message passing sensor network

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sensor Collection and Analysis of Radio Frequencies (SCARF)

Sensor Collection and Analysis of Radio Frequencies (SCARF)

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3rd international Conference on information Warfare and Security

作者： Boleng, Jeff Wirges, Thorsten Schweitzer, Dino Hagerman, Seana Thurimella, Ramakrishna US Air Force Acad Colorado Springs CO 80840 USA Univ Denver Denver CO USA

ISBN: (纸本)9781906638009

In today's net-centric warfare environment, effective management and use of the electromagnetic spectrum is critical. Increasing demands on wireless spectrum from radio traffic, unmanned aerial vehicle (UAV) communication, wireless networks, improvised explosive device (IED) jammers, and sensor networks result in sources competing for, and at times conflicting over, limited frequency spectrum. From an intelligence perspective, having a clear understanding of the RF environment, both friendly and foe, is an important essential of battlefield management. This paper presents the sensor Collection and Analysis of Radio Frequencies (SCARF) system with a focus on the information processing requirements of the sensors and various system components. The overall architecture, sensor processing and fusion challenges, visualization algorithms, and current implementation status are discussed.

关键词： RF collection visualization data fusion system integration

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On the effect of localization errors on geographic face routing in sensor networks

On the effect of localization errors on geographic face rout...

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3rd international symposium on information processing in sensor networks

作者： Seada, K Helmy, A Govindan, R Univ So Calif Dept Elect Engn Los Angeles CA 90089 USA

ISBN: (纸本)1581138466

In the absence of location errors, geographic routing - using a combination of greedy forwarding and face routing - has been shown to work correctly and efficiently. The effects of location errors on geographic routing have not been studied before. In this work we provide a detailed analysis of the effects of location errors on the correctness and performance of geographic routing in static sensor networks. First, we perform a micro-level behavioral analysis to identify the possible protocol error scenarios and their conditions and bounds. Then, we present results from an extensive simulation study of GPSR and GHT to quantify the performance degradation due to location errors. Our results show that even small location errors (of 10% of the radio range or less) can in fact lead to incorrect (non-recoverable) geographic routing with noticeable performance degradation. We then introduce a simple modification for face routing that eliminates probable errors and leads to near perfect performance.

关键词： geographic routing face routing localization inaccuracy location errors wireless sensor networks data-centric storage

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The impact of spatial correlation on routing with compression in wireless sensor networks

The impact of spatial correlation on routing with compressio...

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3rd international symposium on information processing in sensor networks

作者： Pattem, S Krishnamachari, B Govindan, R Univ So Calif Dept Elect Engn Syst Los Angeles CA 90036 USA

ISBN: (纸本)1581138466

The efficacy of data aggregation in sensor networks is a function of the degree of spatial correlation in the sensed phenomenon. While several data aggregation (i.e., routing with data compression) techniques have been proposed in the literature, an understanding of the performance of various data aggregation schemes across the range of spatial correlations is lacking. We analyze the performance of routing with compression in wireless sensor networks using an application-independent measure of data compression (an empirically obtained approximation for the joint entropy of sources as a function of the distance between them) to quantify the size of compressed information, and a bit-hop metric to quantify the total cost of joint routing with compression. Analytical modeling and simulations reveal that while the nature of optimal routing with compression does depend on the correlation level, surprisingly, there exists a practical static clustering scheme which can provide near-optimal performance for a wide range of spatial correlations. This result is of great practical significance as it shows that a simple cluster-based system design can perform as well as sophisticated adaptive schemes for joint routing and compression.

关键词： sensor networks analytical modeling simulations

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Increasing wireless sensor network lifetime through the application of SOM neural networks

Increasing wireless sensor network lifetime through the appl...

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3rd IEEE international symposium on Control, Communications and Signal processing (ISCCSP 2008)

作者： Cordina, Mario Debono, Carl J. Univ Malta Dept Commun & Comp Engn Msida Malta

ISBN: (纸本)9781424416875

Wireless sensor networks are an emerging technology that have garnered significant research attention due to their extensive ability to monitor the physical world and their applicability to an extensive range of applications. These networks are generally battery powered making the lifetime of the network a major concern. This energy consumption. problem can be mitigated to some extent through the use of energy-aware cluster-based routing algorithms. This work presents a novel cluster-based routing algorithm based on self-organizing map (SOM) neural networks. This solution optimizes the network in clusters in an attempt to balance the energy and reduce the transmission power required by the nodes. Results show that through the application of this optimization technique the system's lifetime is increased by 57% (in terms of First Node Dies) when compared to LEACH.

关键词： SOM neural networks clustering algorithms wireless sensor networks

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