Collaborative Computing: Networking, Applications and Worksharing

Name: Collaborative Computing: Networking, Applications and Worksharing | 17th EAI International Conference, CollaborateCom 2021, Virtual Event, October 16-18, 2021, Proceedings, Part I
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17th EAI International Conference, CollaborateCom 2021, Virtual Event, October 16-18, 2021, Proceedings, Part I

Honghao Gao Xinheng Wang(Editor)

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Published on 1. January 2022

XIX, 752 pages

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Content

Intro
Preface
Organization
Contents - Part I
Contents - Part II
Optimization for Collaborate System (Workshop Papers)
Chinese Named Entity Recognition Based on Dynamically Adjusting Feature Weights
1 Introduction
2 Model Approach
2.1 BERT
2.2 CNN
2.3 BILSTM
2.4 CRF
3 BERT+EL-LGWF+CRF
3.1 Weighted Fusion According to CNN and BILSTM
3.2 EL
3.3 Loss Function
4 Experiment and Analysis
4.1 Dataset
4.2 Evaluation Indices
4.3 Experimental Results and Analysis
5 Summary
References
Location Differential Privacy Protection in Task Allocation for Mobile Crowdsensing Over Road Networks
Abstract
1 Introduction
2 Preliminary
2.1 Privacy Model
2.2 Adversary Model
3 PPTA Framework
3.1 Location Obfuscation
3.2 Task Allocation Based on Obfuscated Locations
3.3 Speed-Up with d-Spanner Graph
4 Evaluation
4.1 Experiment Configurations
4.2 Experimental Results
5 Related Work
6 Conclusion
Acknowledgments
References
"Failure" Service Pattern Mining for Exploratory Service Composition
Abstract
1 Introduction
2 Related Work
2.1 Log-Based Service Pattern Mining
2.2 Process-Based Service Pattern Mining
3 Model Definition
3.1 Exploratory Service Composition Instance Model
3.2 Service Pattern Model
4 FSPMA
5 Prototype Implementation
6 Experiment
6.1 Dataset and Environment
6.2 Experimental Verification
7 Application
7.1 Service Recommendation Using "Failure" Service Patterns
7.2 An Example
8 Conclusion
Acknowledgements
References
Optimal Control and Reinforcement Learning for Robot: A Survey
1 Introduction
2 Optimal Control Problem Statement
3 Solutions of Optimal Control for Robot
3.1 Overview the Related Approaches
3.2 Improve Precision and System Complexity
3.3 Overcome Model Bias
3.4 Reduce Computation
4 Future Prospects and Discussion
5 Summary and Conclusions
References
KTOBS: An Approach of Bayesian Network Learning Based on K-tree Optimizing Ordering-Based Search
Abstract
1 Introduction
2 Bayesian Network and k-tree
2.1 Bayesian Network
2.2 Tree Width and k-tree
3 BN Learning Based on K-tree Optimizing Ordering-Based Search
3.1 Obtaining Candidate Parent Set
3.2 Initial Network Construction
3.3 Optimizing Network Using Ordering-Based Search
4 Experiment
4.1 Dataset and Evaluation Method
4.2 Experiment Results and Analysis
5 Conclusions
Acknowledgement
References
Recommendation Model Based on Social Homogeneity Factor and Social Influence Factor
Abstract
1 Introduction
2 Related Work
3 Preliminary and Problem Definition
3.1 Novel Graph Attention Network
3.2 Notations
3.3 Problem Definition
4 The Proposed Model
4.1 Model Details
4.1.1 Original Input and Similar Item Network
4.1.2 Embedding Layer
4.1.3 NGAT Layer
4.1.4 Pairwise Neural Interaction Layer
4.1.5 Policy-Based Fusion Layer
4.1.6 Output Layer and Loss Function
4.2 Model Training
4.2.1 Mini-Batch Training
4.2.2 Alleviate Overfitting
5 Experiments
5.1 Dataset Introduction
5.2 Experimental Setup
5.2.1 Experimental Environment Setting
5.2.2 Evaluation Metrics
5.2.3 Compare Models
5.3 Comparative Experiments: RQ1
5.4 Ablation Experiments: RQ2
5.5 Parameter Sensitivity Experiments: RQ3
6 Conclusion
References
Attention Based Spatial-Temporal Graph Convolutional Networks for RSU Communication Load Forecasting
1 Introduction
2 Related Works
3 System Model
4 Communication Load Evaluation
5 The Communication Load Prediction Model
5.1 Temporal Attention
5.2 Spatial Attention
5.3 Graph Convolution in Spatial Dimension
5.4 Convolution in Temporal Dimension
5.5 Fully Connected Layer
6 Simulation and Analysis
6.1 Dataset
6.2 Model Parameters
6.3 Comparison and Result Analysis
7 Conclusion
References
UVA and Traffic System
Mobile Encrypted Traffic Classification Based on Message Type Inference
1 Introduction
2 Related Work
2.1 Traditional Unencrypted Traffic Classification
2.2 Sequence Feature-Based Encrypted Traffic Classification
2.3 Attribute Feature-Based Encrypted Traffic Classification
3 System Introduction
3.1 System Overview
3.2 Data Preprocessing
3.3 Message Type Inference
3.4 Machine Learning
4 Evaluation
4.1 Preliminary
4.2 Analysis of the Message Type Inference
4.3 Analysis of Adopted Features
4.4 Comparisons with Existing Approaches
5 Discussion and Conclusion
References
Fine-Grained Spatial-Temporal Representation Learning with Missing Data Completion for Traffic Flow Prediction
1 Introduction
2 Related Work
3 Methodology
3.1 Feature Extractors
3.2 Data Completer
4 Experiments and Analysis
4.1 Experimental Settings
4.2 Performance of Traffic Flow Prediction
4.3 Effect of Data Completer
5 Conclusion and Future Work
References
Underwater Information Sensing Method Based on Improved Dual-Coupled Duffing Oscillator Under Lévy Noise Description
Abstract
1 Introduction
2 Related Work
2.1 Lévy Noise Model
2.2 Chaotic Oscillator Signal Sensing System
3 Approach
3.1 Lévy Noise Model Describes Underwater Natural Environment Interference
3.2 Improved Signal Sensing Method of Dual Coupling Duffing Oscillator
4 Experiment and Analysis
4.1 Experiment Deployment
4.2 Performance
5 Conclusion
Acknowledgement
References
Unpaired Learning of Roadway-Level Traffic Paths from Trajectories
1 Introduction
2 Related Work
3 Preliminary Concepts
4 Overview
4.1 Definition
4.2 Problem Analysis and Approach Overview
5 Trajectory Data Transition
5.1 Feature Extraction
5.2 Orientation Converted to Color Information
6 Training Model
7 Experiment and Analysis
7.1 Dataset and Experimental Environment
7.2 Parameter Setting and Data Division
7.3 Results and Performance Comparison
8 Conclusion
References
Multi-UAV Cooperative Exploring for the Unknown Indoor Environment Based on Dynamic Target Tracking
1 Introduction
2 Related Work and Scenario Description
2.1 Related Work
2.2 Scenario Description
3 Method
3.1 Wall-Around Algorithm
3.2 Tracking-D*Lite
4 Experiments
4.1 Tracking-D*Lite Algorithm Experiment
4.2 Simulation Experiment
5 Conclusion
References
Recommendation System
MR-FI: Mobile Application Recommendation Based on Feature Importance and Bilinear Feature Interaction
Abstract
1 Introduction
2 Related Work
3 Proposed Method
3.1 Embedding Layer
3.2 SENET Layer
3.3 Bilinear-Interaction Layer
3.4 Connectivity Layer
3.5 Deep Network
3.6 Prediction Layer
4 Experimental Result and Analysis
4.1 Data Set and Experiment Setup
4.2 Evaluation Metrics
4.3 Baseline Methods
4.4 Experimental Performance
4.5 Hyperparameters Analysis
5 Conclusion and Future Work
Acknowledgement
References
Dual-Channel Graph Contextual Self-Attention Network for Session-Based Recommendation
Abstract
1 Introduction
2 Related Work
2.1 Neural Network Model
2.2 Attention Mechanism
3 Proposed Method
3.1 Problem Statement
3.2 Model Overview
3.3 Session Graph Construction
3.4 Item Embedding Learning
3.5 Self-attention Network
3.6 Prediction Layer
4 Experiments and Analyses
4.1 Datasets
4.2 Evaluation Metric
4.3 Experiment Settings
4.4 Comparison with Baseline Methods
4.5 The Influence of Model Parameters on Experimental Results
5 Conclusions
References
Context-aware Graph Collaborative Recommendation Without Feature Entanglement
1 Introduction
2 Problem Formulation
3 Methodology
3.1 General Framework
3.2 Optimization
3.3 Time Complexity Analysis of CGCR
4 Experiments
4.1 Dataset Description
4.2 Experimental Settings
4.3 RQ1: Does the Proposed Method Perform Better Than Other Comparison Methods?
4.4 RQ2: Does the Proposed Method Elucidate the Meanings of Each Dimension of the Embedding?
4.5 RQ3: How Does Number of Graph Convolution Layer Impact?
4.6 RQ4: How Does Non-sampling Strategy Impact?
5 Related Work
5.1 Collaborative Filtering
5.2 Non-sampling Learning for Top-K Recommendation
6 Conclusion and Future Work
References
Improving Recommender System via Personalized Reconstruction of Reviews
1 Introduction
2 Related Work
2.1 Review-based Recommendation with Topic Modeling
2.2 Document-Level Recommendation
2.3 Review-Level Recommendation
3 Methodology
3.1 Probem Definition
3.2 Overall Framework of PPRR
3.3 Review Document Reconstruction Network (Re-Doc-Net)
3.4 Document-Level Encode Network(Doc-Net)
3.5 Review-Level Encode Network(Review-Net)
3.6 Rating Score Prediction Layer
4 Experiments and Analysis
4.1 DataSets and Experiments Settings
4.2 Performance Evaluation
4.3 Discussion
4.4 Hyper-Parameters Analyses
5 Conclusion
References
Recommendation System and Network and Security
Dynamic Traffic Network Based Multi-Modal Travel Mode Fusion Recommendation
Abstract
1 Introduction
2 Concepts Used in the Paper
2.1 Definition of the Fusion Recommendation Problem
2.2 Heterogeneous Transport Travel Networks
2.3 Meta-paths Extraction Based on User Trajectory
2.4 Meta-path Guided Neighbors
3 Heterogeneous Transport Travel Network Recommendation Model
3.1 Initial Embedding
3.2 Practice of Meta-path
3.3 Meta-path Aggregation Functions
3.4 Semantic Aggregation
3.5 Evaluation Prediction
4 Experiments and Analysis
4.1 Dataset
4.2 Experimental Setup
4.3 Result Analysis
4.4 Result Analysis
4.5 Effect of Aggregation Functions on Recommended Performance
4.6 Performance of the Model on Specific Datasets
5 Conclusion
Acknowledgment
References
Improving Personalized Project Recommendation on GitHub Based on Deep Matrix Factorization
1 Introduction
2 Related Work
2.1 GitHub Project Recommendations
2.2 Deep Learning in Recommendation Systems
3 Proposed Methods
3.1 Data Collection
3.2 Recommender System
3.3 Result and Evaluation
4 Experimental Setup
4.1 Datasets
4.2 Evaluation and Metrics
4.3 Statistic Test
5 Experimental Results
5.1 RQ1:Does the Proposed Method Perform Better Than Other Comparison Methods?
5.2 RQ2:What Is the Effect of the Dimension of the Low-Dimensional Vector and the Number of Recommended Lists on the Performance of the Proposed Method?
6 Threats to Validity
6.1 Internal Validity
6.2 External Validity
7 Conclusions
References
An Intelligent SDN DDoS Detection Framework
1 Introduction
2 Related Works
3 Security-oriented Flow Monitoring and Sampling
3.1 Performance Analysis of Security-Oriented Flow Table Sampling
3.2 Flow Monitoring and Sampling with Low-Latency Based on Optimization Theory
4 Service Flow-Oriented Attack Recognition Model
4.1 Service Flow Features Required by the Model
4.2 DDoS Attack Detection Model Based on Clustering and VAE
4.3 DDoS Attack Defense Based on Recognition Result
5 Simulation and Performance Evaluation
5.1 Simulation Setup
5.2 Network Traffic Sampling Efficiency Evaluation
5.3 Attack Detection Model Evaluation
6 Conclusion
References
Inspector: A Semantics-Driven Approach to Automatic Protocol Reverse Engineering
1 Introduction
2 Related Work
3 System Design
3.1 Overview
3.2 Length Field Inference
3.3 Message Type Field Inference
3.4 Protocol Format Inference
4 Evaluation
4.1 Datasets
4.2 Evaluation Metrics
4.3 Tunable Parameters
4.4 Experimental Results
5 Conclusions
References
MFF-AMD: Multivariate Feature Fusion for Android Malware Detection
1 Introduction
2 Related Work
3 Multivariate Feature Extraction
3.1 Static Feature Extraction
3.2 Dynamic Feature Extraction
3.3 Application Coverage
3.4 Feature Selection
4 Implementation
4.1 Architecture
4.2 Weight Distribution Algorithm
5 Evaluation
5.1 Dataset and Setup
5.2 Results and Analysis
6 Conclusion and Future Work
References
Network and Security
PSG: Local Privacy Preserving Synthetic Social Graph Generation
1 Introduction
2 Related Work
2.1 Social Network Privacy Protection
2.2 Synthetic Graph Generation
3 Preliminaries
3.1 System Overview
3.2 Problem Statement
4 Design Details
4.1 Privacy Protection Mechanism Design
4.2 Privacy Analysis
4.3 Synthetic Network Generation
5 Performance Evaluation
5.1 Datasets and Models
5.2 Evaluation Metrics
5.3 Experimental Results
6 Conclusion
References
Topology Self-optimization for Anti-tracking Network via Nodes Distributed Computing
1 Introduction
2 Related Works
3 Introduction to Convex-Polytope Topology
3.1 Basic Properties
3.2 The Optimum Structure of CPT
4 Topology Self-optimization
4.1 Calculation of Optimum Local Topology
4.2 Topology Self-optimization via Nodes' Collaboration
5 Performance Evaluation
5.1 Evaluation of Network Optimization
5.2 Evaluation of Network Resilience
6 Conclusion
References
An Empirical Study of Model-Agnostic Interpretation Technique for Just-in-Time Software Defect Prediction
1 Introduction
2 Related Work
2.1 Just-in-time Software Defect Prediction
2.2 Explainability in Software Defect Prediction
3 Classifier-Agnostic Interpretation Technique
3.1 LIME
3.2 BreakDown
3.3 SHAP
4 Experimental Setup
4.1 Data Sets
4.2 Building Classification Models
4.3 Evaluation Metrics
5 Experimental Results and Analysis
5.1 Analysis for RQ1
5.2 Analysis for RQ2
6 Conclusion and Future Work
References
Yet Another Traffic Black Hole: Amplifying CDN Fetching Traffic with RangeFragAmp Attacks
1 Introduction
2 Background
2.1 CDN Overview
2.2 HTTP Range Request Mechanism on CDN
2.3 Differences in CDNs Handling Range Requests
2.4 Amplification Attacks
3 RangeFragAmp Attack
3.1 Threat Model
3.2 S-RFA Attack
3.3 O-RFA Attack
4 Real-World Evaluation
4.1 Consideration in Selecting CDN Providers
4.2 S-RFA Attack Evaluation
4.3 O-RFA Attack Evaluation
4.4 Severity Assessment
4.5 CDN Providers Feedback
5 Mitigation
5.1 Root Cause Analysis
5.2 Limitation
5.3 Solutions
6 Related Work
7 Conclusion
References
DCNMF: Dynamic Community Discovery with Improved Convex-NMF in Temporal Networks
1 Introduction
2 Related Work
3 Algorithm
3.1 Notation
3.2 The Unified DCNMF Model Formulation
3.3 Optimization
4 Experiments and Results
4.1 Evaluation Measures
4.2 Synthetic Dataset 1: Dynamic-GN Dataset
4.3 Synthetic Dataset 2: Dynamic-LFR Dataset
4.4 KIT-Email Data
5 Discussion and Conclusion
References
Network and Security and IoT and Social Networks
Loopster++: Termination Analysis for Multi-path Linear Loop
1 Introduction
2 Preliminaries
2.1 Scope of Our Work
2.2 Path Dependency Automaton (PDA)
2.3 The Structure of Loopster
2.4 Termination of Linear Loop Program
3 Methodology
3.1 Path Termination Analysis
3.2 Inter-Path Analysis
3.3 Cycle Analysis
4 Implementation and Evaluation
4.1 Effectiveness of Loopster++
4.2 Performance of Loopster++
5 Relate Work
6 Conclusion
References
A Stepwise Path Selection Scheme Based on Multiple QoS Parameters Evaluation in SDN
1 Introduction
2 Related Work
3 Proposed Scheme: SWQoS
3.1 SWQoS Scheme Architecture
3.2 Path Finding
3.3 QoS Requirements of Services
3.4 Path Selection
4 Experiments and Performance Evaluation
4.1 The Experimental Environment and Topology
4.2 The First Group Experiment: Simulating the Network Status of Selecting the Preferred Paths
4.3 The Second Group Experiment: Simulating the Network Status of Obtaining Satisfied Paths
4.4 The Third Group Experiment: Simulating the Network Status of Obtaining Reluctant Paths
5 Conclusions
References
A Novel Approach to Taxi-GPS-Trace-Aware Bus Network Planning
1 Introduction
2 Related Work
3 Main Steps
3.1 Candidate Bus Stop Identification
3.2 Bus Network Generation
4 Simulations
5 Conclusion
References
Community Influence Maximization Based on Flexible Budget in Social Networks
1 Introduction
2 Related Work
3 System Model and Problem Formulation
3.1 System Model
3.2 Problem Formulation
4 Our Solutions
4.1 General Solution
4.2 FBCIM Algorithm
4.3 FBBCIM Algorithm
5 Performance Evaluation
5.1 Datasets and Parameters Setting
5.2 Comparison of Algorithms and Metrics
5.3 Evaluation Results
6 Conclusion
References
An Online Truthful Auction for IoT Data Trading with Dynamic Data Owners
1 Introduction
2 System Model and Problem Formulation
2.1 System Model
2.2 Data Trading Model Based on an Auction Mechanism
2.3 Problem Formulation
3 Online Data Trading Algorithm
3.1 Online Matching Algorithm Based on a Greedy Strategy
3.2 Computing Trading Prices Based on Critical Data Owners
3.3 Theoretical Analysis
4 Numerical Illustration
4.1 Methodology and Simulation Settings
4.2 Numerical Results
5 Related Work
5.1 Decentralized Data Trading Based on the Blockchain Technology
5.2 Trading Data with Different Levels of Privacy
6 Conclusion
References
IoT and Social Networks and Images Handling and Human Recognition
Exploiting Heterogeneous Information for IoT Device Identification Using Graph Convolutional Network
1 Introduction
2 Preliminaries
2.1 TLS Basics
2.2 Graph Convolutional Networks
2.3 Problem Definition
3 The THG-IoT Framework
3.1 Data Preprocessing
3.2 Graph Generation
3.3 GCN Classifier
4 Experimental Evaluation
4.1 Dataset
4.2 Evaluation Metrics
4.3 Experimental Setting
4.4 Parameter Study
4.5 Comparison Experiments
4.6 Variant of THG-IoT
5 Related Work
6 Conclusions and Future Work
References
Data-Driven Influential Nodes Identification in Dynamic Social Networks
1 Introduction
2 Related Work
3 Data-Driven Model for Influential Nodes Identification in Social Networks
3.1 Multi-scale Comprehensive Metric System
3.2 Data-Driven Weight Optimization Algorithm
3.3 Influential Nodes Identification Based on Data-Driven Weighted TOPSIS
4 Experiments and Analysis
4.1 Experimental Setup
4.2 Performance Comparison
5 Conclusion and Future Work
References
Human Motion Recognition Based on Wi-Fi Imaging
Abstract
1 Introduction
2 Wi-Fi Imaging Algorithm Based on 3D Virtual Array
2.1 Imaging Algorithm Based on Virtual 3D Array
2.2 Description of Improved 3D Decoherence Algorithm
3 Environment Adaptive Human Continuous Motion Recognition
3.1 Continuous Action Segmentation
3.2 Action Feature Extraction
3.3 SVM Classification Based on GA Algorithm Optimization
4 Experiment and Result Analysis
4.1 Experimental Configuration
4.2 Human Imaging and Motion Recognition
4.3 Result Analysis
4.4 Model Test
4.5 Comparison of Different Models
5 Conclusion
Acknowledgment
References
A Pervasive Multi-physiological Signal-Based Emotion Classification with Shapelet Transformation and Decision Fusion
Abstract
1 Introduction
2 Related Works
2.1 Emotion Classification Based on Physiological Signals
2.2 Shapelet-Based Algorithms
3 Methods
3.1 Overview
3.2 Data Preprocessing
3.3 Sub-classification Methods
3.3.1 Shapelet Transformation Algorithm
3.3.2 Feature Extraction
3.3.3 Sub-classifiers
3.4 Decision-Level Fusion Strategy
4 Experimental Results and Analysis
4.1 Database
4.2 Results of Emotion Classification of a Single Physiological Signal
4.3 Results Comparisons
5 Conclusion and Future Work
Acknowledgments
References
A Novel and Efficient Distance Detection Based on Monocular Images for Grasp and Handover
1 Introduction
2 Related Works
2.1 RGB-D-Based Methods
2.2 Analytic-Based Methods
2.3 Model-Based Methods
3 Method
3.1 Distance Detection A
3.2 Distance Detection B
4 Experiments and Results
4.1 Experimental Equipment
4.2 Preliminary Work
4.3 Grasping Tests
4.4 Human-Robot Handover Tests
4.5 Time Cost
4.6 Qualitative Results and Future Work
5 Conclusion
References
Images Handling and Human Recognition and Edge Computing
A Novel Gaze-Point-Driven HRI Framework for Single-Person
1 Introduction
2 Related Work
2.1 Gaze Point Estimation
2.2 Application of Gaze Points in HRI
3 Methods
3.1 Overview
3.2 Object Locations Distribution Obtaining
3.3 Gaze Points Distribution Estimating
3.4 Gaze Target Reasoning and Entity Matching
3.5 Moving and Grabbing
4 Results
4.1 Experimental Equipment and Setup
4.2 Experimental Results
5 Conclusion
References
Semi-automatic Segmentation of Tissue Regions in Digital Histopathological Image
1 Introduction
2 Related Work
2.1 Methods Based on Hand-Crafted Features
2.2 Methods Based on Deep Learning
3 Preliminaries
3.1 Methodology Overview
3.2 Histopathological Images Preprocessing: Staining Normalization
3.3 Pre-segmentation of Tissue Regions
3.4 Automatic Segmentation of Tissue Regions
4 Experiments and Results Analysis
4.1 Experimental Objective
4.2 Dataset
4.3 Experimental Setup
4.4 Experimental Results and Analysis
5 Conclusion and Future Work
References
T-UNet: A Novel TC-Based Point Cloud Super-Resolution Model for Mechanical LiDAR
1 Introduction
2 Related Works
3 Model Architecture
3.1 Point Cloud Projection and Back-Projection
3.2 T-UNet Model
4 Experimental Study
4.1 Datasets
4.2 Implementation Details
4.3 Model Evaluation
5 Conclusion
References
Computation Offloading for Multi-user Sequential Tasks in Heterogeneous Mobile Edge Computing
1 Introduction
2 Related Work
3 MUST Model and Problem Formulation
3.1 System Model
3.2 Problem Formulation
4 Regular Expression Based Algorithm for MUST
5 Performance Evaluation
5.1 Setup
5.2 Results
6 Conclusion
References
Model-Based Evaluation and Optimization of Dependability for Edge Computing Systems
1 Introduction
2 Related Work
3 Dependability Modeling and Analysis of Edge/Cloud Server
3.1 System State Transition Model
3.2 Analysis of Dependability Attributes
4 Dependability Modeling and Analysis of Edge Computing System
4.1 State Aggregation Technique
4.2 Dependability Model of Edge Computing Systems
5 Model and Approach of Dependability Optimization
6 Empirical Evaluation
6.1 Data Set and Experimental Settings
6.2 Experimental Results
7 Conclusion
References
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Collaborative Computing: Networking, Applications and Worksharing

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