000 12880nam a2201429 i 4500
001 5237066
003 IEEE
005 20191218152113.0
006 m o d
007 cr |n|||||||||
008 151221s2006 njua ob 001 eng d
020 _a9780471784173
_qelectronic
020 _z9780471719762
_qprint
020 _z0471784176
_qelectronic
024 7 _a10.1002/0471784176
_2doi
035 _a(CaBNVSL)mat05237066
035 _a(IDAMS)0b00006481095295
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
050 4 _aTK7872.D48
_bS435 2006eb
082 0 4 _a621.3821
_222
245 0 0 _aSensor network operations /
_cedited by Shashi Phoha, Thomas LaPorta, Christopher Griffin.
264 1 _aPiscataway, New Jersey :
_bIEEE Press,
_cc2006.
264 2 _a[Piscataqay, New Jersey] :
_bIEEE Xplore,
_c[2006]
300 _a1 PDF (xix, 724 pages) :
_billustrations.
336 _atext
_2rdacontent
337 _aelectronic
_2isbdmedia
338 _aonline resource
_2rdacarrier
504 _aIncludes bibliographical references and index.
505 0 _aPREFACE -- CONTRIBUTORS -- I SENSOR NETWORK OPERATIONS OVERVIEW -- 1 Overview of Mission-Oriented Sensor Networks -- 1.1 Introduction -- 1.2 Trends in Sensor Development -- 1.3 Mission-Oriented Sensor Networks: Dynamic Systems Perspective -- References -- II SENSOR NETWORK DESIGN AND OPERATIONS -- 2 Sensor Deployment, Self-Organization, and Localization -- 2.1 Introduction -- 2.2 SCARE: A Scalable Self-Configuration and Adaptive Reconfiguration Scheme for Dense Sensor Networks -- 2.3 Robust Sensor Positioning in Wireless Ad Hoc Sensor Networks -- 2.4 Trigonometric k Clustering (TKC) for Censored Distance Estimation -- 2.5 Sensing Coverage and Breach Paths in Surveillance Wireless Sensor Networks -- References -- 3 Purposeful Mobility and Navigation -- 3.1 Introduction -- 3.2 Controlled Mobility for Efficient Data Gathering in Sensor�Networks with Passively Mobile Nodes -- 3.3 Purposeful Mobility in Tactical Sensor Networks -- 3.4 Formation and Alignment of Distributed Sensing Agents with Double-Integrator Dynamics and Actuator Saturation -- 3.5 Modeling and Enhancing the Data Capacity of Wireless Sensor Networks -- References -- 4 Lower Layer Issues-MAC, Scheduling, and Transmission -- 4.1 Introduction -- 4.2 SS-TDMA: A Self-Stabilizing Medium Access Control (MAC) for Sensor Networks -- 4.3 Comprehensive Performance Study of IEEE 802.15.4 -- 4.4 Providing Energy Efficiency for Wireless Sensor Networks�Through Link Adaptation Techniques -- References -- 5 Network Routing -- 5.1 Introduction -- 5.2 Load-Balanced Query Protocols for Wireless Sensor Networks -- 5.3 Energy-Efficient and MAC-Aware Routing for Data Aggregation in Sensor Networks -- 5.4 LESS: Low-Energy Security Solution for Large-scale Sensor�Networks Based on Tree-Ripple-Zone Routing Scheme -- References -- 6 Power Management -- 6.1 Introduction -- 6.2 Adaptive Sensing and Reporting in Energy-Constrained Sensor Networks -- 6.3 Sensor Placement and Lifetime of Wireless Sensor Networks: Theory and Performance Analysis.
505 8 _a6.4 Algorithms for Maximizing Lifetime of Battery-Powered Wireless Sensor Nodes -- 6.5 Battery Lifetime Estimation and Optimization for Underwater Sensor Networks -- References -- 7 Distributed Sensing and Data Gathering -- 7.1 Introduction -- 7.2 Secure Differential Data Aggregation for Wireless Sensor Networks -- 7.3 Energy-Conserving Data Gathering Strategy Based on Trade-off Between Coverage and Data Reporting Latency in Wireless Sensor Networks -- 7.4 Quality-Driven Information Processing and Aggregation in Distributed Sensor Networks -- 7.5 Progressive Approach to Distributed Multiple-Target Detection in Sensor Networks -- References -- 8 Network Security -- 8.1 Introduction -- 8.2 Energy Cost of Embedded Security for Wireless Sensor Networks -- 8.3 Increasing Authentication and Communication Confidentiality in Wireless Sensor Networks -- 8.4 Efficient Pairwise Authentication Protocols for Sensor and Ad Hoc Networks -- 8.5 Fast and Scalable Key Establishment in Sensor Networks -- 8.6 Weil Pairing-Based Round, Efficient, and Fault-Tolerant Group Key Agreement Protocol for Sensor Networks -- References -- III SENSOR NETWORK APPLICATIONS -- 9 Pursuer-Evader Tracking in Sensor Networks -- 9.1 Introduction -- 9.2 The Problem -- 9.3 Evader-Centric Program -- 9.4 Pursuer-Centric Program -- 9.5 Hybrid Pursuer-Evader Program -- 9.6 Efficient Version of Hybrid Program -- 9.7 Implementation and Simulation Results -- 9.8 Discussion and Related Work -- References -- 10 Embedded Soft Sensing for Anomaly Detection in Mobile Robotic Networks -- 10.1 Introduction -- 10.2 Mobile Robot Simulation Setup -- 10.3 Software Anomalies in Mobile Robotic Networks -- 10.4 Soft Sensor -- 10.5 Software Anomaly Detection Architecture -- 10.6 Anomaly Detection Mechanisms -- 10.7 Test Bed for Software Anomaly Detection in Mobile Robot Application -- 10.8 Results and Discussion -- 10.9 Conclusions and Future Work -- Appendix A -- Appendix B -- References -- 11 Multisensor Network-Based Framework for Video Surveillance: Real-Time Superresolution Imaging.
505 8 _a11.1 Introduction -- 11.2 Basic Model of Distributed Multisensor Surveillance System -- 11.3 Superresolution Imaging -- 11.4 Optical Flow Computation -- 11.5 Superresolution Image Reconstruction -- 11.6 Experimental Results -- 11.7 Conclusion -- References -- 12 Using Information Theory to Design Context-Sensing Wearable Systems -- 12.1 Introduction -- 12.2 Related Work -- 12.3 Theoretical Background -- 12.4 Adaptations -- 12.5 Design Considerations -- 12.6 Case Study -- 12.7 Results -- 12.8 Conclusion -- Appendix -- References -- 13 Multiple Bit Stream Image Transmission over Wireless Sensor Networks -- 13.1 Introduction -- 13.2 System Description -- 13.3 Experimental Results -- 13.4 Summary and Discussion -- References -- 14 Hybrid Sensor Network Test Bed for Reinforced Target Tracking -- 14.1 Introduction -- 14.2 Sensor Network Operational Components -- 14.3 Sensor Network Challenge Problem -- 14.4 Integrated Target Surveillance Experiment -- 14.5 Experimental Results and Evaluation -- 14.6 Conclusion -- References -- 15 Noise-Adaptive Sensor Network for Vehicle Tracking in the Desert -- 15.1 Introduction -- 15.2 Distributed Tracking -- 15.3 Algorithms. 15.4 Experimental Methods -- 15.5 Results and Discussion -- 15.6 Conclusion -- References -- ACKNOWLEDGMENTS -- INDEX -- ABOUT THE EDITORS.
506 1 _aRestricted to subscribers or individual electronic text purchasers.
520 _aThis excellent title introduces the concept of mission-oriented sensor networks as distributed dynamic systems of interacting sensing devices that are networked to jointly execute complex real-time missions under uncertainity. It provides the latest, yet unpublished results on the main technical and application challenges of mission-oriented sensor networks. The authors of each chapter are research leaders from multiple disciplines who are presenting their latest innovations on the issues. Together, the editors have compiled a comprehensive treatment of the subject that flows smoothly from chapter to chapter. This interdisciplinary approach significantly enhances the science and technology knowledge base and influences the military and civilian applications of this field. Author Information: Dr. Shashi Phoha is the Guest Editor of IEEE Transactions in Mobile Computing, Special Issue on Mission-Oriented Sensor Networks. She is the Head of the Information Sciences and Technology Division of ARL and Professor of Electrical and Computer Engineering at Pennsylvania State University. She has led major research programs of multimillion dollars for military sensor networks in industry as well as in academia. In addition to more than a hundred journal articles, she authored or co-authored several books in related areas. Dr. Thomas La Porta is the Editor of the IEEE Transactions on Mobile Computing. He received his B.S.E.E. and M.S.E.E. degrees from The Cooper Union, New York, NY and his Ph.D. degree in Electrical Engineering from Columbia University, New York, NY. He joined the Computer Science and Engineering Department at Penn State in 2002 as a Full Professor. He is Director of the Networking Research Center at Penn State. Prior to joining Penn State, Dr. LaPorta was with Bell Laboratories since 1986. He was the Director of the Mobile Networking Research Department Bell Laboratories, Lucent Technologies, where he led various projects in wireless and mobile networking. He is an IEEE Fellow, Bell Labs Fellow, received the Bell Labs Distinguished Technical Staff Award, and an Eta Kappa Nu Outstanding Young Electrical Engineer Award. He has published over 50 technical papers and holds over 20 patents. Christopher Griffin holds a Masters degree in Mathematics from Penn State and is currently pursuing his Ph.D. there. Mr. Griffin has worked as a research engineer at the Penn State Applied Research Laboratory for the last six years on several DARPA and or Army Research Laboratory sponsored programs, including: the Emergent Surveillance Plexus (ESP) program as a lead engineer; the DARPA sponsored Semantic Information Fusion program under the SensIT initiative, where he co-developed a distributed target tracking system and managed the development of a target classification algorithm using Level 1 sensor fusion techniques; as a co-principal software architect for the DARPA Joint Force Component Controller (JFACC) initiative, an adaptive C2 program aimed at improving Air Force response times; and he was the principal software architect for the Boeing/ARFL Insertion of Embedding Infosphere Technology (IEIST) program. His areas of research expertise are distributed tracking systems, mission oriented control, and system modeling.
530 _aAlso available in print.
538 _aMode of access: World Wide Web
588 _aDescription based on PDF viewed 12/21/2015.
650 0 _aSensor networks.
655 0 _aElectronic books.
695 _aRouting protocols
695 _aSections
695 _aSecurity
695 _aSensor fusion
695 _aSensors
695 _aSignal processing algorithms
695 _aSignal to noise ratio
695 _aSoftware
695 _aStreaming media
695 _aSurveillance
695 _aSwitches
695 _aSynchronization
695 _aTarget tracking
695 _aTesting
695 _aThree dimensional displays
695 _aTime division multiple access
695 _aTopology
695 _aTransducers
695 _aTransient analysis
695 _aVehicle dynamics
695 _aVehicles
695 _aVideo surveillance
695 _aWireless sensor networks
695 _aAd hoc networks
695 _aAdaptive systems
695 _aAnalytical models
695 _aArray signal processing
695 _aBase stations
695 _aBiographies
695 _aCameras
695 _aComputational modeling
695 _aComputer architecture
695 _aContext
695 _aData communication
695 _aDecoding
695 _aDistributed databases
695 _aElliptic curves
695 _aEncoding
695 _aEncryption
695 _aEnergy consumption
695 _aEntropy
695 _aError correction codes
695 _aEstimation
695 _aFault tolerance
695 _aFault tolerant systems
695 _aGlobal Positioning System
695 _aHardware
695 _aHeuristic algorithms
695 _aHistograms
695 _aImage coding
695 _aImage communication
695 _aIndexes
695 _aInterference
695 _aJoints
695 _aLoad modeling
695 _aMarkov processes
695 _aMedia Access Protocol
695 _aMemory management
695 _aMobile communication
695 _aMobile computing
695 _aMobile robots
695 _aMonitoring
695 _aMutual information
695 _aNetwork topology
695 _aOperating systems
695 _aPeer to peer computing
695 _aPower demand
695 _aProtocols
695 _aPublic key
695 _aQuality of service
695 _aRandom access memory
695 _aRandom variables
695 _aRelays
695 _aRobot kinematics
695 _aRobot sensing systems
695 _aRouting
700 1 _aPhoha, Shashi,
_d1948-
700 1 _aLa Porta, Thomas F.
700 1 _aGriffin, Christopher,
_d1979-
710 2 _aJohn Wiley & Sons,
_epublisher.
710 2 _aIEEE Xplore (Online service),
_edistributor.
776 0 8 _iPrint version:
_z9780471719762
856 4 2 _3Abstract with links to resource
_uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5237066
999 _c41926
_d41926