000			13730cam a2200421 i 4500
005			20221101223009.0
008			091019s2009 gw a b 001 0 eng d
011			_aBIB MATCHES WORLDCAT
020			_a3642018769
020			_a9783642018763
035			_a(ATU)b11597574
035			_a(OCoLC)401159860
040			_aBTCTA _beng _erda _cBTCTA _dYDXCP _dBWX _dLDL _dATU
050		4	_aTK7872.D48 _bA43 2009
082	0	4	_a621.381 _222
100	1		_aAmmari, Habib, _eauthor. _91067019
245	1	0	_aChallenges and opportunities of connected k-covered wireless sensor networks : _bfrom sensor deployment to data gathering / _cHabib M. Ammari.
264		1	_a[Berlin] : _bSpringer Verlag, _c[2009]
264		4	_c©2009
300			_axxvi, 342 pages : _billustrations ; _c24 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
490	1		_aStudies in computational intelligence _vv. 2
504			_aIncludes bibliographical references (pages 321-334) and index.
505	0	0	_gPart 1. _tIntroduction and Background Concepts -- _g1. _tOverview of Wireless Sensor Networks -- _g1.1. _tIntroduction -- _g1.2. _tMajor Challenges -- _g1.2.1. _tLimited Resources and Capabilities -- _g1.2.2. _tLocation Management -- _g1.2.3. _tSensor Deployment -- _g1.2.4. _tTime-Varying Network Characteristics -- _g1.2.5. _tNetwork Scalability, Heterogeneity, and Mobility -- _g1.2.6. _tSensing Application Requirements -- _g1.3. _tSample Sensing Applications -- _g1.4. _tMotivations of This Book -- _g1.5. _tDesign Requirements -- _g1.6. _tContributions of This Book -- _g1.7. _tSummary -- _g2. _tBackground and Fundamentals -- _g2.1. _tIntroduction -- _g2.2. _tTerminology -- _g2.3. _tDeterministic and Stochastic Sensing Models -- _g2.4. _tNetwork Connectivity and Fault Tolerance -- _g2.5. _tEnergy Consumption Model -- _g2.6. _tPercolation Model -- _g2.6.1. _tWhy a Continuum Percolation Model? -- _g2.7. _tNetwork Model -- _g2.8. _tSummary -- _gPart 2. _tAlmost Sure Coverage and Connectivity -- _g3. _tPhase Transitions in Coverage and Connectivity in Two-Dimensional Deployment Fields -- _g3.1. _tIntroduction -- _g3.2. _tPhase Transition in Sensing Coverage -- _g3.2.1. _tEstimation of the Shape of Covered Components -- _g3.2.2. _tCritical Density of Covered Components -- _g3.2.3. _tCritical Radius of Covered Components -- _g3.2.4. _tCharacterization of Critical Percolation -- _g3.2.5. _tNumerical Results -- _g3.3. _tPhase Transition in Network Connectivity -- _g3.3.1. _tIntegrated Sensing Coverage and Network Connectivity -- _g3.3.1. _t1 Simultaneous Phase Transitions When R >= 2r -- _g3.3.1. _t2 Simultaneous Phase Transitions When r <= R < 2r -- _g3.4. _tDiscussion -- _g3.5. _tRelated Work -- _g3.6. _tSummary -- _g4. _tPhase Transitions in Coverage and Connectivity in Three-Dimensional Deployment Fields -- _g4.1. _tIntroduction -- _g4.2. _tThree Percolation Problems -- _g4.2.1. _tSensing Coverage Percolation -- _g4.2.2. _tNetwork Connectivity Percolation -- _g4.2.3. _tCoverage and Connectivity Percolation -- _g4.2.3. _t1 Two-Concentric-Sphere Model -- _g4.2.3. _t2 Integrated Continuum Percolation -- _g4.3. _tFurther Discussion -- _g4.3.1. _tPracticality and Generalizability Issues -- _g4.3.2. _tSensor Deployment in Three-Dimensional Fields -- _g4.3.3. _tRelaxations of Assumptions -- _g4.3.3. _t1 Relaxing the Unit Sphere Model -- _g4.3.3. _t2 Relaxing the Homogeneous Sensor Model -- _g4.4. _tRelated Work -- _g4.5. _tSummary --
505	0	0	_gPart 3. _tConnected k-Coverage -- _g5. _tConnected k-Coverage in Two-Dimensional Deployment Fields -- _g5.1. _tIntroduction -- _g5.2. _tAchieving Connected k-Coverage -- _g5.2.1. _tConnected k-Coverage Problem Modeling -- _g5.2.2. _tSufficient Condition to Ensure k-Coverage -- _g5.3. _tCentralized k-Coverage Protocol -- _g5.3.1. _tDeployment Field Slicing -- _g5.3.2. _tSensor Selection -- _g5.3.3. _tSlicing Grid Dynamics -- _g5.4. _tClustered k-Coverage Protocol -- _g5.4.1. _tCluster-Head Selection and Attributed Roles -- _g5.4.2. _tThe T-CRACCk Protocol -- _g5.4.3. _tThe D-CRACCk Protocol -- _g5.4.3. _t1 Deployment Field Clustering -- _g5.4.3. _t2 Cluster-Heads Coordination and Sensor Selection -- _g5.5. _tDistributed k-Coverage Protocol -- _g5.5.1. _tk-Coverage Checking Algorithm and Sensor Selection -- _g5.5.2. _tState Transition Diagram of Trig-DIRACCk -- _g5.5.3. _tEnsuring Network Connectivity -- _g5.6. _tSelf-scheduling Based k-Coverage -- _g5.6.1. _tk-Coverage Candidacy Algorithm -- _g5.6.2. _tState Transition Diagram of Self-DIRACCk -- _g5.6.3. _tTri-DIRACCk Versus Self-DIRACCk -- _g5.7. _tRelaxation of Assumptions -- _g5.7.1. _tRelaxing the Unit Disk Model -- _g5.7.2. _tRelaxing the Sensor Homogeneity Model -- _g5.8. _tPerformance Evaluation -- _g5.8.1. _tSimulation Settings -- _g5.8.2. _tSimulation Results -- _g5.8.3. _tComparison of Self-DIRACCk with CCP -- _g5.9. _tRelated Work -- _g5.10. _tSummary -- _g6. _tHeterogeneous and Mobile Connected k-Coverage in Two-Dimensional Deployment Fields -- _g6.1. _tIntroduction -- _g6.2. _tHeterogeneous Connected k-Coverage -- _g6.2.1. _tRandom Deployment Approach -- _g6.2.1. _t1 Centralized Connected k-Coverage Protocol -- _g6.2.1. _t2 Distributed Connected k-Coverage Protocol (R-Het-DCCk) -- _g6.2.2. _tPseudo-random Deployment Approach -- _g6.2.2. _t1 Centralized Connected k-Coverage Protocol (PR-Het-CCCk) -- _g6.2.2. _t2 Distributed Connected k-Coverage Protocol (PR-Het-DCCk) -- _g6.2.3. _tPerformance Evaluation -- _g6.3. _tMobile Connected k-Coverage -- _g6.3.1. _tPseudo-random Sensor Placement -- _g6.3.2. _tSensor Mobility for k-Coverage of a Region of Interest -- _g6.3.2. _t1 Centralized Approach for Mobile Sensor Selection (CAMSEL) -- _g6.3.2. _t2 Distributed Approach for Mobile Sensor Selection (DAMSEL) -- _g6.3.2. _t3 How to Ensure Network Connectivity? -- _g6.3.3. _tPerformance Evaluation -- _g6.4. _tRelated Work -- _g6.4.1. _tSensor Heterogeneity -- _g6.4.2. _tSensor Mobility -- _g6.5. _tSummary -- _g7. _tTwo-Dimensional Stochastic Connected k - Coverage and Three-Dimensional Connected k - Coverage -- _g7.1. _tIntroduction -- _g7.2. _tTwo-Dimensional Stochastic Connected k-Coverage -- _g7.2.1. _tStochastic k-Coverage Characterization -- _g7.2.2. _tStochastic k-Coverage-Preserving Scheduling -- _g7.2.2. _t1 k-Coverage Candidacy Algorithm -- _g7.2.2. _t2 State Transition of SCPk -- _g7.2.3. _tSimulation Results -- _g7.3. _tThree-Dimensional Connected k-Coverage -- _g7.3.1. _tProblem Analysis: The Curse of Dimensionality -- _g7.3.2. _tOur Distributed k-Coverage Protocol -- _g7.3.3. _tPerformance Evaluation -- _g7.4. _tRelated Work -- _g7.5. _tSummary -- _g8. _tNetwork Connectivity and Fault-Tolerance Measures in Two-Dimensional Deployment Fields -- _g8.1. _tIntroduction -- _g8.2. _tUnconditional Fault-Tolerance Measures -- _g8.2.1. _tHomogeneous Sensors -- _g8.2.2. _tHeterogeneous Sensors -- _g8.2.3. _tConditional Fault-Tolerance Measures -- _g8.2.4. _tHomogeneous Sensors -- _g8.2.5. _tHeterogeneous Sensors -- _g8.3. _tRelated Work -- _g8.4. _tSummary --
505	0	0	_gPart 4. _tData Forwarding and Gathering -- _g9. _tGeographic Forwarding on Always-On Sensors -- _g9.1. _tIntroduction -- _g9.2. _tThe WLDT Protocol -- _g9.2.1. _tLong-Range Versus Short-Range Forwarding -- _g9.2.2. _tA Two-Step Data Forwarding Protocol -- _g9.2.2. _t1 Checkpoint Selection -- _g9.2.2. _t2 Checkpoint-Based Short-Range Forwarding -- _g9.2.3. _tIllustrative Example -- _g9.3. _tAnalysis of WLDT -- _g9.4. _tShort-Range Versus Long-Range -- _g9.4.1. _tEnergy Gain -- _g9.4.2. _tControlled Short-Range Data Forwarding -- _g9.5. _tDiscussion -- _g9.6. _tRelated Work -- _g9.7. _tSummary -- _g10. _tTrade-Off between Energy and Delay in Geographic Forwarding on Always-On Sensors -- _g10.1. _tIntroduction -- _g10.2. _tA Slicing Approach -- _g10.2.1. _tSlicing of Communication Range -- _g10.2.2. _tSelection of Candidate Proxy Forwarders -- _g10.2.3. _tUniform Energy Depletion Characterization -- _g10.3. _tTrading-Off Energy with Delay -- _g10.3.1. _tSimple Analytical Bounds -- _g10.3.1. _t1 Data Forwarding along Shortest Paths -- _g10.3.1. _t2 Data Forwarding along Non-direct Paths -- _g10.3.1. _t3 Numerical Results -- _g10.3.2. _tMulti-objective Optimization Approach -- _g10.3.2. _t1 Overview of the WES Approach -- _g10.3.2. _t2 Solving the Trade-Off Problem Using WES -- _g10.3.2. _t3 Numerical Results -- _g10.3.3. _tTED Detailed Description -- _g10.3.3. _t1 Communication Range Slicing -- _g10.3.3. _t2 Concentric Circular Band Selection -- _g10.3.3. _t3 Proxy Forwarder Selection -- _g10.3.3. _t4 Is k Fixed for All Proxy Forwarders or Not? -- _g10.4. _tRelaxation of Several Key Assumptions -- _g10.4.1. _tRelaxing the Sensor Homogeneity Model -- _g10.4.2. _tRelaxing the Communication Disk Model -- _g10.4.3. _tRelaxing the Dense Network Model -- _g10.4.4. _tRelaxing the Energy Consumption Model -- _g10.4.5. _tRelaxing the Always-On Sensors Model -- _g10.5. _tSimulation Results -- _g10.5.1. _tSimulation Settings -- _g10.5.2. _tImpact of Selection Space Size -- _g10.5.3. _tUsing the Energy x Delay Metric -- _g10.5.4. _tImpact of Variability of k -- _g10.5.5. _tImpact of Sensor Heterogeneity -- _g10.6. _tRelated Work -- _g10.7. _tSummary -- _g11. _tEnergy Sink-Hole Problem with Always-On Sensors in Two-Dimensional Deployment Fields -- _g11.1. _tIntroduction -- _g11.2. _tEnergy Sink-Hole Problem Analysis -- _g11.2.1. _tBase Protocol Average Energy Consumption -- _g11.2.2. _tNominal Communication Range-Based Data Forwarding -- _g11.2.3. _tAdjustable Communication Range-Based Data Forwarding -- _g11.2.3. _t1 Perfect Uniform Energy Depletion -- _g11.2.3. _t2 Partial Uniform Energy Depletion -- _g11.3. _tUsing Heterogeneous Sensors -- _g11.3.1. _tMulti-tier Architecture -- _g11.3.2. _tNEAR Performance Evaluation -- _g11.4. _tSink Mobility and Energy Aware Voronoi Diagram -- _g11.4.1. _tWhy Energy Aware Voronoi Diagram? -- _g11.4.2. _tEVEN Detailed Description -- _g11.4.2. _t1 Computing Relative Positions -- _g11.4.2. _t2 Computing Energy-Aware Voronoi Diagram -- _g11.4.3. _tEVEN Performance Evaluation -- _g11.4.3. _t1 Impact of Sink Mobility -- _g11.4.3. _t2 Comparing EVEN with VGF -- _g11.4.3. _t3 Comparing EVEN with Another Protocol -- _g11.5. _tRelated Work -- _g11.5.1. _tBalancing Energy Consumption -- _g11.5.2. _tMinimizing Energy Consumption -- _g11.5.3. _tMobility-Based Forwarding Protocols -- _g11.6. _tSummary -- _g12. _tGeographic Forwarding on Duty-Cycled Sensors in Two-Dimensional and Three-Dimensional Deployment Fields -- _g12.1. _tIntroduction -- _g12.2. _tTwo-Dimensional Sensor Deployment -- _g12.2.1. _tPotential Fields Based Modeling Approach -- _g12.2.2. _tData Forwarding without Aggregation -- _g12.2.3. _tData Forwarding with Aggregation -- _g12.2.3. _t1 Locally Aggregated Data Forwarding -- _g12.2.3. _t2 Globally Aggregated Data Forwarding -- _g12.2.4. _tGeneralizability of GEFIB -- _g12.2.4. _t1 Convex Sensing and Communication Model -- _g12.2.4. _t2 Sensor Heterogeneity Model -- _g12.2.5. _tPerformance Evaluation -- _g12.3. _tThree-Dimensional Sensor Deployment -- _g12.3.1. _tHybrid Geographic Forwarding -- _g12.3.2. _tPerformance Evaluation -- _g12.4. _tRelated Work -- _g12.5. _tSummary --
505	0	0	_gPart 5. _tSummary and Further Extensions -- _g13. _tConclusion and Future Work -- _g13.1. _tContributions of This Book -- _g13.2. _tResearch Directions -- _tAppendix: Network Connectivity and Fault-Tolerance Measures in Three-Dimensional Deployment Fields -- _g1. _tIntroduction -- _g2. _tk-Coverage Characterization -- _g3. _tUnconditional Connectivity -- _g4. _tConditional Connectivity -- _g5. _tDiscussion -- _g6. _tRelaxing the Unit Sphere Model: Convex Model -- _g7. _tUnderwater Sensor Networks -- _g8. _tSummary.
520			_a"Wireless sensor networks have received significant attention because of their important role and many conveniences in our lives. Indeed, the recent and fast advances in inexpensive sensor technology and wireless communications has made the design and development of large-scale wireless sensor networks cost-effective and appealing to a wide range of mission-critical situations, including civilian, natural, industrial, and military applications, such as health and environmental monitoring, seism monitoring, industrial process automation, and battlefields surveillance, respectively. A wireless sensor network consists of a large number of tiny, low-powered devices, called sensors, which are randomly or deterministically deployed in a field of interest while collaborating and coordinating for the successful accomplishment of their mission. These sensors suffer from very scarce resources and capabilities, such as bandwidth, storage, CPU, battery power (or energy), sensing, and communication, to name a few, with energy being the most critical one. The major challenge in the design process of this type of network is mainly due to the limited capabilities of the sensors, and particularly, their energy, which makes them unreliable. This book aims to develop a reader's thorough understanding of the opportunities and challenges of k-covered wireless sensor networks, where each point in a deployment field is covered (or sensed) by at least k sensors. Following Rene Descartes' most elegant methodology of dividing each difficulty into as many parts as might be possible and necessary to best solve it (Discours de la Method, 1637), this book presents a variety of theoretical studies based on percolation theory and computational geometry, as well as protocols that lead to the design of a unified framework, where connected k-coverage, sensor scheduling, and data routing and dissemination are jointly considered ."--Publisher's website.
588			_aMachine converted from AACR2 source record.
650		0	_aWireless sensor networks _9339822
830		0	_aStudies in computational intelligence _vv. 2. _9292380
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