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[null,null,"Titolo",null,"Wireless Sensor Networks : 17th China Conference, CWSN 2023, Dalian, China, October 13–15, 2023, Proceedings / / edited by Lei Wang, Tie Qiu, Chi Lin, Xinbing Wang"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"981-9710-10-3"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (329 pages)"]
[null,null,"Collana",null,"Communications in Computer and Information Science, , 1865-0937 ; ; 1994"]
[null,null,"Disciplina",null,"681"]
[null,null,"Soggetti",null,"Computer networks"]
[{"$nulls":4},"Computers"]
[{"$nulls":4},"Image processing - Digital techniques"]
[{"$nulls":4},"Computer vision"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Computer Communication Networks"]
[{"$nulls":4},"Computing Milieux"]
[{"$nulls":4},"Computer Imaging, Vision, Pattern Recognition and Graphics"]
[{"$nulls":4},"Computer and Information Systems Applications"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents -- Theory and Technology on Wireless Sensor Network -- MPR Node Selection Improvement in OLSR Based on Binary Cuckoo Search -- 1 Introduction -- 2 Related Works -- 3 Cuckoo Search and Binary Cuckoo Search -- 3.1 Cuckoo Search -- 3.2 Binary Cuckoo Search -- 4 Proposed Protocol -- 4.1 Weight of Candidate Nodes -- 4.2 The MPR Node Selection Based on BCS -- 5 Performance Evaluation -- 6 Conclusions -- References -- Research on Energy Consumption Optimization Using a Lyapunov-Based LSTM-PSO Algorithm -- 1 Introduction -- 2 System Model -- 2.1 System Basic Elements -- 2.2 Transmission Model -- 2.3 Task Queue Model -- 2.4 Energy Model -- 3 Problem Formulation -- 3.1 Setting up Lyapunov Virtual Pairs of Columns -- 3.2 Constructing the Lyapunov Function -- 4 Algorithm Design -- 5 Numerical Results -- 5.1 Basic Settings -- 5.2 Evaluation with Different Delay Requirement Task -- 6 Conclusion -- References -- Attitude-Aware Based Geographical Opportunity Routing Protocol for Floating Wireless "]
[{"$nulls":4},"Sensor Network -- 1 Introduction -- 2 Background and Motivation -- 2.1 Attitude-Aware Based Link Model -- 2.2 Geographical Opportunity Routing Protocol -- 3 Design -- 3.1 Overview -- 3.2 Network Initialization -- 3.3 Forwarding Area Establishment -- 3.4 Relay Node Selection -- 4 Evaluation -- 4.1 Experiment Setup -- 4.2 Attitude Angle in Real Scenario -- 4.3 End-to-End Reliability -- 4.4 End-to-End Delay -- 5 Related Work -- 6 Conclusion -- References -- Dynamic Liveness Detection Based on Fusion of mmWave Radar and Vision -- 1 Introduction -- 2 Motivation -- 2.1 Limitation of Existing Solutions -- 2.2 Opportunity -- 3 mmWave Radar Feature Extraction Mechanism for Live Cyclist -- 3.1 Radar Data Collection and Processing -- 3.2 Radar Cross Section (RCS) -- 3.3 Building Signal Strength Reference Database."]
[{"$nulls":4},"3.4 RCS Value: Cyclists vs. Visual Interference -- 3.5 Summary -- 4 mmWave Radar and Vision Fusion Mechanism -- 4.1 mmWave Radar Pixel Image -- 4.2 Multi-modal Feature Extraction -- 4.3 Feature Fusion Module Based on Attention Mechanism -- 5 Evaluation -- 5.1 Dataset and System Environment -- 5.2 Evaluation Methodology -- 5.3 Overall Performance -- 5.4 Sensitivity Analysis -- 6 Conclusion -- References -- LMCRA: A Reliable Satellite Internet Routing Method with Low Maintenance Cost -- 1 Introduction -- 2 Related Work -- 2.1 Centralized Routing -- 2.2 Distributed Routing -- 2.3 Hybrid Routing -- 3 System Architecture -- 4 Algorithm Design -- 4.1 Calculation of Satellite Network Period and Design of Low Maintenance Cost Routing -- 4.2 A Routing Algorithm Considering Latency and Path Stability During a Cycle -- 4.3 Fast ReRouting Mechanism -- 5 Simulation Experiment Evaluation -- 5.1 Simulation Environment -- 5.2 The Impact of Networking Methods on Algorithm Performance -- 5.3 The Impact of Time Spans (Parameter N) on Algorithm Performance -- 5.4 The Impact of Constellation Density on Algorithm Performance -- 5.5 Evaluation of FRR-BP -- 6 Conclusion -- References -- Application on Internet of Things -- WiHI: Indoor Human Identification with WiFi Signals -- 1 Introduction -- 2 Preliminary -- 3 System Design -- 3.1 System Architecture -- 3.2 Data Collection -- 3.3 Data Processing -- 3.4 Motion Change Pattern Extraction -- 3.5 Human Identification -- 4 Experiments and Evaluation -- 4.1 Overall Performance -- 4.2 Performance Evaluation -- 4.3 Limitations and Discussion -- 5 Conclusion -- References -- Age of Information-Based Channel Scheduling Policy in IoT Networks Under Dynamic Channel Conditions -- 1 Introduction -- 2 System Model -- 2.1 AoI and Throughput Model -- 2.2 Problem Definition -- 3 Scheduling Policy."]
[{"$nulls":4},"3.1 Priority-Based Scheduling Policy Considering AoI and Throughput, PSP-AT -- 3.2 Dynamic Classification-Based Priority Scheduling Policy, DCP-AT -- 4 Experiment and Result -- 4.1 Experiment Setup and Parameter Settings -- 4.2 Result -- 5 Conclusion -- References -- Underwater Target Detection Based on Dual Inversion Dehazing and Multi-Scale Feature Fusion Network -- 1 Introduction -- 2 Multiscale Feature Fusion Deep Learning Object Detection Network -- 2.1 Dual Inverted Dehazing Module (DRDM) -- 2.2 Feature Enhancement Module (SFEM) -- 3 Simulation Experiment Results -- 3.1 Wilder Fish New Dataset and Environment -- 3.2 Comparison of Output Feature Maps -- 3.3 Comparison of Loss Function -- 3.4 Comparison of Algorithm Detection Effects -- 4 Conclusion -- References -- Security and Privacy Protection on Internet of Things -- Honeynet Module Simulation and Dynamic Configuration of Honeypots Based on Online Learning -- 1 Introduction -- 2 Background -- 2.1 Virtual Honeypot Module Simulation -- 2.2 Physical Honeypot Module Simulation -- 2.3 Data Collection Module -- 3 Dynamic Honeypot Configuration Based on Online Learning -- 3.1 Specific Implementation "]
[{"$nulls":4},"-- 3.2 Experiment and Analysis -- 4 Honeynet System Deployment and Testing -- 4.1 Honeynet System Construction -- 4.2 Honeynet System Deception Test -- 4.3 Honeynet System Interactivity Test -- 5 Conclusion -- References -- Fog Computing and Wireless Computing -- Edge-Assisted Multi-camera Tracking for Digital Twin Systems -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Design Overview -- 3.2 Target Tracking in 3D Coordinate System -- 3.3 Multi-camera Target Identity Re-identification Algorithm -- 3.4 Occlusion Processing -- 4 Evaluation -- 5 Conclusion -- References -- Layer-First ``Cache-Rollback'' Collaborative Pruning Method -- 1 Introduction."]
[{"$nulls":4},"2 Layer Pruning Method Based on Model Recovery Force -- 3 Layer-First ``Cache-Rollback'' Collaborative Pruning Method -- 3.1 Layer-Channel Collaborative Pruning Method -- 3.2 Efficiency Analysis -- 4 Simulation Experiment -- 4.1 Experiment Setup -- 4.2 Rationality and Universality Verification -- 4.3 Comparison of Common Pruning Methods -- 5 Conclusion -- References -- The Model and Method of Electricity Consumption Data Collection Based on Producer and Consumer -- 1 Introduction -- 2 Strategies for Dynamic Adjustment of Consumer Numbers -- 3 Evaluation of the Performance of the Dynamic Adjustment Strategy for the Number of Consumers -- 4 Experimental Results and Analysis -- 5 Conclusions and Future Work -- References -- Design and Analysis of Service Resource Allocation Scheme Based on Mobile Edge Computing -- 1 Introduction -- 1.1 Background -- 1.2 Contribution and Structure -- 2 System Model -- 2.1 Terminal Device -- 2.2 Sever -- 3 Problem Solving -- 3.1 Offload Decision -- 3.2 Offloading Stage -- 4 Algorithm Introduction -- 4.1 State Space Definition -- 4.2 Action Space Definition -- 4.3 Reward Function Definition -- 5 Analysis of Experimental Results -- 5.1 Convergence -- 5.2 Performance -- References -- Edge Computing Task Unloading Decision Optimization Algorithm Based on Deep Reinforcement Learning -- 1 Introduction -- 2 System Model -- 2.1 Serial Task Model -- 2.2 Delay Model -- 2.3 Energy Consumption Model -- 2.4 Problem Statement -- 3 Algorithm Model -- 4 Experimental Results and Analysis -- 5 Conclusion -- References -- Intelligent Internet of Things -- WiKnow: A Human Activity Recognition Method in Office Scene with Coordinate Attention from WiFi Channel State Information -- 1 Introduction -- 2 Related Work -- 2.1 Vision-Based HAR -- 2.2 Wearable Device-Based HAR -- 2.3 WiFi-Based HAR -- 3 Background of CSI -- 4 System Design."]
[{"$nulls":4},"4.1 System Overview -- 4.2 Signal Pre-processing Module -- 4.3 CSI Data Reconstruction Module -- 4.4 HAR Classification Module -- 5 Dataset -- 5.1 Own Dataset -- 5.2 StanWiFi -- 6 Performance Evaluation -- 6.1 Experimental Results on Own Dataset -- 6.2 Experimental Results on StanWiFi -- 7 Conclusion and Future Work -- References -- DRL-Based Scheduling Scheme with Age of Information for Real-Time IoT Systems -- 1 Introduction -- 2 System Model and Problem Formulate -- 2.1 Network Model -- 2.2 AoI Model -- 2.3 Problem Formulation -- 3 Online Algorithm Design Based on DRL -- 4 Simulation Results -- 5 Conclusion -- References -- Reverse Multidimensional Auction Based Vehicle Selection and Resource Allocation for IoV -- 1 Introduction -- 2 System Model and Problem Formulation -- 2.1 Heterogeneous Data Model -- 2.2 Training Cost Model -- 2.3 Auction Model -- 2.4 Problem Formulation -- 3 Algorithm Design and Theorem Analysis -- 3.1 Algorithm Design -- 3.2 Payment Confirmation -- 3.3 Theoretical Analysis -- 4 Performance Evaluation -- 4.1 Comparison of Social Welfare -- 4.2 Virtual Global Dataset Quality Comparison -- 5 Conclusion -- References -- "]
[{"$nulls":4},"Universal Handwriting Recognition for Mobile Devices via Acoustic Sensing -- 1 Introduction -- 2 Related Works -- 2.1 Sensors-Based Handwriting Recognition -- 2.2 Acoustic-Based Handwriting Recognition -- 3 System Design -- 3.1 Pre-processing -- 3.2 Character Recognition -- 4 Evaluation -- 4.1 Experimental Setting -- 4.2 Overall Recognition Performance -- 4.3 Impact Factors -- 5 Discussion -- 6 Conclusion -- References -- Reinforcement-Learning-Based 2D Flow Control for Logistics Systems -- 1 Introduction -- 2 Related Works -- 2.1 Logistics System Problems -- 2.2 Reinforcement Learning Theories -- 2.3 Technical Challenges -- 3 Structure of Omniveyor and Model Definition -- 3.1 Structure of the Omniveyor."]
[{"$nulls":4},"3.2 Spatio-Temporal Graph."]
[null,null,null,"Sommario/riassunto","This book constitutes the refereed proceedings of the 17th China Conference on Wireless Sensor Networks, CWSN 2023, which took place in Dalian, China, in October 2023. The 22 full papers presented in this volume were carefully reviewed and selected from 105 submissions, including 38 English papers and 67 Chinese papers. The conference provided an academic exchange of research and a development forum for IoT researchers, developers, enterprises, and users. Exchanging results and experience of research and applications in IoT, and discussing the key challenges and research hotspots, is the main goal of the forum. As a high-level forum for the design, implementation, and application of IoT, the conference promoted the exchange and application of the theories and technologies of IoT-related topics."]