| Lecture Notes in Electrical Engineering | 2 |
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| Preface | 5 |
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| Contents | 10 |
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| Contributors | 12 |
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| Optimized Seed Node Locations for Infrastructure Wireless Mesh Networks | 15 |
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| 1 Introduction | 15 |
| 2 The Seed Node Placement Problem | 17 |
| 2.1 Network Model | 17 |
| 3 Optimization | 19 |
| 3.1 NSGA-II | 21 |
| 3.2 Objective Functions | 21 |
| 4 Experimental Results | 22 |
| 4.1 Data Sets | 22 |
| 4.2 Results | 23 |
| 4.2.1 Parameter Tuning | 23 |
| 4.2.2 Subscription probability | 25 |
| 5 Conclusions and Future Directions | 30 |
| References | 33 |
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| Use of Non-monotonic Utility in Multi-Attribute Network Selection | 34 |
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| 1 Introduction | 34 |
| 1.1 Selection of MADM Algorithm | 35 |
| 1.1.1 Accuracy of the Results Obtained from an Algorithm | 36 |
| 1.1.2 Appropriateness of Applying the Algorithm to the Problem | 36 |
| 1.2 Types of QoS Profiles | 37 |
| 1.2.1 Service-Based QoS Profile | 37 |
| 1.2.2 Subscription-Based QoS Profile | 37 |
| 2 Use of Non-monotonic Utilities for Attributes in Network Selection | 38 |
| 3 Comparison of MADM Algorithms for Use with Non-monotonic Utilities of Attributes | 40 |
| 3.1 TOPSIS | 40 |
| 3.2 ELECTRE | 40 |
| 3.3 GRA | 40 |
| 4 Theory of Gray Relational Space | 42 |
| 5 Application of GRA Adapted to Network Selection with Non-monotonic Utility | 42 |
| 6 Evaluation of Using Non-monotonic Utilities in a Heterogeneous Wireless Network Environment | 45 |
| 6.1 Setting up GRA for Network Selection | 46 |
| 6.1.1 Determine Reference Attribute Values for Different Service or User Categories | 46 |
| 6.1.2 Determine Attribute Weights for Different Service or User Categories | 46 |
| 7 Conclusion | 51 |
| References | 52 |
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| RFID Indoor Tracking System Based on Inter-Tags Distance Measurements | 53 |
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| 1 Introduction | 53 |
| 2 Indoor Propagation Model for Far-Field Passive RFID System | 56 |
| 2.1 Backscattered Free-Space Link Budget | 56 |
| 2.2 Indoor Large-Scale Propagation Model | 57 |
| 3 The Proposed Algorithm | 58 |
| 3.1 Inter-tags Distance Measurement Algorithm | 58 |
| 3.2 Probabilistic RFID Map Generation | 62 |
| 3.3 Adaptive Kalman Filtering | 63 |
| 3.3.1 Motion Model | 63 |
| 3.3.2 The Observation Model | 64 |
| 4 Simulations and Evaluation | 65 |
| 4.1 System Model Setup | 66 |
| 4.2 Probabilistic RFID Map | 67 |
| 4.3 Localization Performance Evaluation | 67 |
| 4.4 Tracking Performance | 69 |
| 5 Conclusions | 72 |
| References | 73 |
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| Adaptive Virtual Queue Random Early Detectionin Satellite Networks | 75 |
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| 1 Introduction | 75 |
| 2 Overview of PEP PEP | 77 |
| 3 Overview of AQM Methods | 78 |
| 3.1 RED RED RED | 78 |
| 3.2 AVQ | 79 |
| 4 Problems | 80 |
| 4.1 Asynchronous Queuing Behavior | 81 |
| 4.2 Global Synchronization | 81 |
| 5 Solution | 81 |
| 5.1 Asynchronous Queuing Behavior | 83 |
| 5.2 Global Synchronization | 83 |
| 6 Emulation Framework | 83 |
| 6.1 Evaluation Methodologies | 85 |
| 6.2 Parameter Settings | 85 |
| 7 Emulation Results | 86 |
| 7.1 Link Utilization | 86 |
| 7.2 Queue Size | 87 |
| 7.3 Packet Drop | 89 |
| 8 Mathematical Model | 90 |
| 9 Conclusion and Future Work | 92 |
| References | 93 |
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| News Corporation: Facing the Wireless World of the 21st Century | 95 |
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| 1 Introduction | 95 |
| 2 News Corporation Worldwide Wireless Interests | 96 |
| 3 Satellite TV and Satellite Mobile TV | 97 |
| 4 Sports and Entertainment: Fuelling the Wireless ontent | 98 |
| 5 The Management of the Wireless Omnipresence to Consumers | 99 |
| 6 The Global Media Marketplace and Wireless for News Corp | 100 |
| 7 News Corporations Contribution to Secure Wireless Delivery | 100 |
| 8 Conclusions | 101 |
| References | 101 |
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| Delay Effect on Conversational Quality in TelecommunicationNetworks: Do We Mind? | 103 |
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| 1 Introduction | 103 |
| 1.1 Delay in Modern Telecommunication Networks | 104 |
| 1.2 Conversational Tests Versus Listening-only Tests | 104 |
| 1.3 Conversational Interactivity Versus Delay Annoyance -- Test Scenarios | 105 |
| 2 Performed Tests | 106 |
| 3 Test Results | 107 |
| 4 Disc
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