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Energy-efficient multi-query optimization over large-scale sensor networks

Energy-efficient multi-query optimization over large-scale s...

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1st International conference on Wireless algorithms, Systems and applications

作者： Xie, Lei Chen, Lijun Lu, Sanglu Xie, Li Chen, Daoxu Nanjing Univ State Key Lab Novel Software Technol NJU POLU Cooperat Lab Wireless Sensor Network Nanjing 210008 Peoples R China

ISBN: (纸本)3540371893

Currently much research work has been done to attempt to efficiently conserve the energy consumption for sensor networks, recently a database approach to programming sensor networks has gained much attention from the sensor network research area. In this paper we developed an optimized multi-query processing paradigm for aggregate queries, we proposed an equivalence class based merging algorithm for in-network merging of partial aggregate values of multi-queries, and an adaptive fusion degree based routing scheme as a cross-layer designing technique. Our optimized multi-query processing paradigm efficiently takes advantage of the work sharing mechanism by sharing common aggregate values among multiple queries to fully reduce the communication cost for sensor networks, thus extending the life time of sensor networks. The experimental evaluation shows that our optimization paradigm can efficiently result in dramatic energy savings, compared to previous work.

关键词： Telecommunication networks

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Rule based situation assessment for sea-surveillance

Rule based situation assessment for sea-surveillance

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conference on Multisensor, Multisource Information fusion

作者： Edlund, Johan Gronkvist, Magnus Lingvall, Andreas Sviestins, Egils Saab AB Nettovagen 6 S-17588 Jarfalla Sweden

ISBN: (纸本)0819462985

In order to achieve greater situation awareness it is necessary to identify relations between individual entities and their immediate surroundings, neighboring entities and important landmarks. The idea is that long-term intentions and situations can be identified by patterns of more rudimentary behavior, in essence situations formed by combinations of different basic relationships. In this paper we present a rule based situation assessment system that utilizes both COTS and in-house software. It is built upon an agent framework that speeds up development times, since it takes care of many of the infrastructural. issues of such a communication intense application as this is, and a rule based reasoner that can reason about situations that develop over time. The situation assessment system is developed to be simple, but structurally close to an operational system, with connections to outside data sources and graphical editors and data displays. It is developed with a specific simple Sea-surveillance scenario in mind, which we also present, but the ideas behind the system are general and are valid for other areas as well.

关键词： Databases Surveillance Computing systems Data fusion Software Data conversion Data modeling Detection and tracking algorithms Transform theory Visualization

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A local-centralized adaptive clustering algorithm for wireless sensor networks

A local-centralized adaptive clustering algorithm for wirele...

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IEEE International conference on Information Acquisition

作者： Chen, Weike Li, Wenfeng Ming, Xinzhu Hunan Met Profess Tech Coll Dept Engn Mech Zhuzhou 412000 Peoples R China Wuhan Univ Technol Sch Logist Engn Wuhan 430063 Peoples R China

ISBN: (纸本)1424405289

Existing hierarchical routing algorithms for wireless sensor networks (WSNs) mainly focus on distributing energy load among all nodes. They pay little attention to Quality of Services (QoS) support in WSNs. In this paper, we developed an algorithm, Local-centralized Adaptive Clustering algorithm (LAC), which concerns not only energy consumption but also the reliability and the steadiness of the wireless sensor networks. LAC proposes a local-centralized mechanism to elect cluster-heads which makes election of cluster-head more reasonable, and provides a twice cluster-formation model which impose the feature of load balance on wireless sensor networks by distributing evenly the communication load and the load of data fusion among cluster-heads. LAC also suggests a parameter to measure the probability of network congestion in hierarchical applications of WSNs.

关键词： wireless sensor networks hierarchical model QoS support routing algorithm data fusion

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Data fusion cm a distributed heterogeneous sensor network

Data fusion cm a distributed heterogeneous sensor network

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Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2006

作者： Lamborn, Peter Williams, Pamela J. Mississippi State University 302 B Park Circle Place Starkville MS 39759 United States Sandia National Laboratories MS9159 P.O. Box 969 Livermore CA 94551-0969 United States

ISBN: (纸本)0819462985

Alarm-based sensor systems are being explored as a tool to expand perimeter security for facilities and force protection. However, the collection of increased sensor data has resulted in an insufficient solution that includes faulty data points. Data analysis is needed to reduce nuisance and false alarms, which will improve officials' decision making and confidence levels in the system's alarms. Moreover, operational costs can be allayed and losses mitigated if authorities are alerted only when a real threat is detected. In the current system, heuristics such as persistence of alarm and type of sensor that detected an event are used to guide officials' responses. We hypothesize that fusing data from heterogeneous sensors in the sensor field can provide more complete situational awareness than looking at individual sensor data. We propose a two stage approach to reduce false alarms. First, we use self organizing maps to cluster sensors based on global positioning coordinates and then train classifiers on the within cluster data to obtain a local view of the event. Next, we train a classifier on the local results to compute a global solution. We investigate the use of machine learning techniques, such as k-nearest neighbor, neural networks, and support vector machines to improve alarm accuracy. On simulated sensor data, the proposed approach identifies false alarms with greater accuracy than a weighted voting algorithm.

关键词： sensor data fusion

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On Bayesian tracking of extended objects

On Bayesian tracking of extended objects

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2006 IEEE International conference on Multisensor fusion and Integration for Intelligent Systems, MFI

作者： Koch, Wolfgang 53343 Wachtberg Germany

ISBN: (纸本)1424405661

In tracking and sensor data fusion targets of interest are usually considered as point source objects;i.e. compared to the sensor resolution their extension is neglected. Due to the increasing resolution capabilities of modern sensors, however, this assumption is often no longer valid: Different scattering centers of an object can cause distinct detections. Examples of extended targets are found in short-range applications (littoral surveillance, autonomous weapons, or robotics). As an extended target also a collectively moving, loosely structured group can be considered. This point of view is all the more appropriate, the smaller the mutual distances between the individual targets are. Due to the resulting data association and resolution conflicts any attempt of tracking the individual objects is no longer reasonable. With reference to simulated radar data produced by a partly resolvable aircraft formation a Bayesian solution to the resulting tracking problem is proposed. Ellipsoidal object extensions are modeled by random matrices and treated as additional state variables to be estimated or 'tracked'. We expect that the resulting tracking algorithms are relevant also for tracking large, collectively moving target swarms. © 2006 IEEE.

关键词： sensor data fusion

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Modular robotics and intelligent imaging for unmanned systems

Modular robotics and intelligent imaging for unmanned system...

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conference on Unmanned Systems Technology VIII

作者： Chen, Chung-Hao Cheng, Chang Page, David Koschan, Andreas Abidi, Mongi Univ Tennessee Imaging Robot & Intelligent Syst Lab Dept Elect & Comp Engn Knoxville TN 37996 USA

ISBN: (纸本)0819462861

The Imaging, Robotics, and Intelligent Systems (IRIS) Laboratory at the University of Tennessee is currently developing a modular approach to unmanned systems to increase mission flexibility and aid system interoperability for security and surveillance applications. The main focus of the IRIS research is the development of sensor bricks where the term brick denotes a self-contained system that consists of the sensor itself, a processing unit, wireless communications, and a power source. Prototypes of a variety of sensor bricks have been developed. These systems include a thermal imaging brick, a quad video brick, a 3D range brick, and a nuclear (gamma ray and neutron) detection bricks. These bricks have been integrated in a modular fashion into mobility platforms to form functional unmanned systems. Research avenues include sensor processing algorithms, system integration, communications architecture, multi-sensor fusion, sensor planning, sensor-based localization, and path planning. This research is focused towards security and surveillance applications such as under vehicle inspection, wide-area perimeter surveillance, and high-value asset monitoring. This paper presents an overview of the IRIS research activities in modular robotics and includes results from prototype systems.

关键词： modular architecture navigation planning sensor brick multimodal data fusion

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Measuring Situational Awareness and resolving inherent high-level fusion obstacles

Measuring Situational Awareness and resolving inherent high-...

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conference on Multisensor, Multisource Information fusion

作者： Sudit, Moises Stotz, Adam Holender, Michael Tagliaferri, William Canarelli, Kathie SUNY Coll Buffalo Ctr Multisource Informat Fus Buffalo NY 14062 USA CUBRC Buffalo NY 14221 USA Alion Sci & Technol Rome 13440 NY USA

ISBN: (纸本)0819462985

Information fusion Engine for Real-time Decision Making (INFERD) is a tool that was developed to supplement current graph matching techniques in Information fusion models. Based on sensory data and a priori models, INFERD dynamically generates, evolves, and evaluates hypothesis on the current state of the environment. The a priori models developed are hierarchical in nature lending them to a multi-level Information fusion process whose primary output provides a situational awareness of the environment of interest in the context of the models running. In this paper we look at INFERD's multi-level fusion approach and provide insight on the inherent problems such as fragmentation in the approach and the research being undertaken to mitigate those deficiencies. Due to the large variance of data in disparate environments, the awareness of situations in those environments can be drastically different. To accommodate this, the INFERD framework provides support for plug-and-play fusion modules which can be developed specifically for domains of interest. However, because the models running in INFERD are graph based, some default measurements can be provided and will be discussed in the paper. Among these are a Depth measurement to determine how much danger is presented by the action taking place, a Breadth measurement to gain information regarding the scale of an attack that is currently happening, and finally a Reliability measure to tell the user the credibility of a particular hypothesis. All of these results will be demonstrated in the Cyber domain where recent research has shown to be an area that is well-defined and bounded, so that new models and algorithms can be developed and evaluated.

关键词： graphs defragmentation real-time decision-making Situational Awareness

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Combining elements of information fusion and knowledge-based systems to support situation analysis

Combining elements of information fusion and knowledge-based...

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conference on Multisensor, Multisource Information fusion

作者： Roy, Jean Def R&D Canada Valcartier Val Belair PQ G3J 1X5 Canada

ISBN: (纸本)0819462985

Situation awareness has emerged as an important concept in military and public security environments. Situation analysis is defined as a process, the examination of a situation, its elements, and their relations, to provide and maintain a product, i.e., a state of situation awareness for the decision maker(s). It is well established that information fusion, defined as the process of utilizing one or more information sources over time to assemble a representation of aspects of interest in an environment, is a key enabler to meeting the demanding requirements of situation analysis. However, although information fusion is important, developing and adopting a knowledge-centric view of situation analysis should provide a more holistic perspective of this process. This is based on the notion that awareness ultimately has to do with having knowledge of something. Moreover, not all of the situation elements and relationships of interest are directly observable. Those aspects of interest that cannot be observed must be inferred, i.e., derived as a conclusion from facts or premises, or by reasoning from evidence. This paper discusses aspects of knowledge, and how it can be acquired from experts, formally represented and stored in knowledge bases to be exploited by computer programs, and validated. Knowledge engineering is reviewed, with emphasis given to cognitive and ontological engineering. Facets of reasoning are discussed, along with inferencing methods that can be used in computer applications. Finally, combining elements of information fusion and knowledge-based systems, an overall approach and framework for the building of situation analysis support systems is presented.

关键词： situation analysis situation awareness information fusion knowledge-based systems knowledge engineering

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Hybrid methods for multisource information fusion and decision support

Hybrid methods for multisource information fusion and decisi...

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conference on Multisensor, Multisource Information fusion

作者： Braun, Jerome J. Glina, Yan MIT Lincoln Lab 244 Wood St Lexington MA 02173 USA

ISBN: (纸本)0819462985

This paper presents the progress of an ongoing research effort in multisource information fusion for biodefense decision support. The effort concentrates on a novel machine-intelligence hybrid-of-hybrids decision support architecture termed FLASH (fusion, Learning, Adaptive Super-Hybrid) we proposed. The highlights of FLASH discussed in the paper include its cognitive-processing orientation and the hybrid nature involving heterogeneous multiclassifier machine learning and approximate reasoning paradigms. Selected specifics of the FLASH internals, such as its feature selection techniques, supervised learning, clustering, recognition and reasoning methods, and their integration, are discussed. The results to date are presented, including the background type determination and bioattack detection computational experiments using data obtained with a multisensor fusion testbed we have also developed. The processing of imprecise information originating from sources other than sensors is considered. Finally, the paper discusses applicability of FLASH and its methods to complex battlespace management problems such as course-of-action decision support.

关键词： multisource information fusion machine intelligence cognitive processing decision support biodefense

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A diversity-controllable genetic algorithm for optimal fused traffic planning on sensor networks

A diversity-controllable genetic algorithm for optimal fused...

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11th Asia-Pacific conference on Advances in Computer Systems Architecture

作者： Pan, Yantao Lu, Xicheng Zhu, Peidong Ma, Shen Natl Def Univ Sch Comp Changsha Peoples R China

ISBN: (纸本)3540400567

In some sensor network applications e.g. target tracing, multi-profile data about an event are fused at intermediate nodes. The optimal planning of such fused traffic is important for prolonging the network lifetime, because data communications consume the most energy of sensor networks. As a general method for such optimization problems, genetic algorithms suffer from tremendous communication diversities that increase greatly with the network size. In this paper, we propose a diversity-controllable genetic algorithm for optimizing fused traffic planning. Simulation shows that it gains remarkable improvements.

关键词： sensor networks lifetime optimization and data fusion

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