Review: expected to be implemented
Các keywork để ghép và tìm hướng viết báo.
Super resolution
Robotics
Data transmission
Reduce latency
Diffusion model
Data compression
Data aggregation
Data prediction
satellite communication channels
Anomaly Detection
Investigating the Effectiveness of GNN models
Time series transmission data
A Systematic Review of Literature on AI Methods for Latency Reduction in Satellite Communications
QoS (Quality of service)
QoE (Quality of experience)
feature extraction
A Comparative Analysis
A comparative analysis for data compression using AI models
Bài báo này: Aggregation Tree Based Data Aggregation Algorithm in Wireless Sensor Networks Với bài báo này nữa, nó liên quan đến data aggregation: Minimal Sleep Delay Driven Aggregation Tree Construction in IoT Sensor Networks
Bài báo này liên quan đến việc triển khai DL vào các loại dữ liệu khác nhau, liên quan đến satellite: A framework to classify heterogeneous Internet traffic with Machine Learning and Deep Learning techniques for Satellite Communications
Dữ liệu ở tập dataset tương ứng.
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Voice and Telephony [transmission of voice signals] between user devices or between user devices and landline (thiết bị người dùng hoặc giữa thiết bị người dùng và mạng điện thoại)
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Internet Data: Satellite networks assume a pivotal role in providing internet connectivity to areas where terrestrial networks are not readily accessible. By means of satellite links, a broad spectrum of internet data, encompassing web pages, emails, file downloads, and streaming media, can be effectively transmitted. Consequently, individuals, businesses, and organizations gain access to a vast realm of online resources and services, regardless of their geographical location. Notably, the network traffic data set published in reference [*25] represents a notable example within this domain.
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Video and Television Broadcasting: deliver video and audio signals directly from satellites to user devices
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Data Networks and Virtual Private Networks (VPNs) [*9]: Satellite networks offer robust data connectivity for a multitude of applications, including corporate networks, government networks, and remote site connectivity. Through their utilization, wide-area networks (WANs) and virtual private networks (VPNs) can be established, facilitating secure and private data communication between disparate locations.
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Earth Observation Data: including high-resolution images, weather data, climate data, and other pertinent environmental parameters. Such data finds utility in diverse applications such as weather forecasting, disaster management, agriculture, urban planning, and environmental monitoring.
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Global Navigation Satellite Systems (GNSS) Data: This invaluable data serves as the foundation for precise positioning, navigation, and timing information, thereby enabling a plethora of applications, including navigation systems, geolocation services, and asset or vehicle tracking.
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Sensor Data and Telemetry: Satellites, equipped with sensors or scientific instruments, fulfill a critical role in the collection and transmission of diverse data types for research purposes
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Command and Control Data [*13]: In order to effectively manage and operate satellites, satellite networks necessitate the transmission of command and control data.
How to put title of paper
Biết tên nào thì đặt tên đó trước đi. (các bài nào có thể đặt tên thì đặt trước đi, ít nhất 3 bài cho phù hợp)
A Systematic Review of Literature on AI Methods for Latency Reduction in Satellite Communications
Clone template ở “expected to be implemented” tương ứng ở overleaf.
các key work cho các bài báo:
data aggregation data compression data prediction
give me title for paper with some key: reduce latency, data transmission, robotics throught out satellite, video encoding
Một số tên đề tài:
- Comparative Analysis of Diffusion-Based Super-Resolution Methods for Robotic Vision Enhancement: A Comprehensive Study
- Efficient Network Delay Minimization through Aggregation Tree Based Data Aggregation Algorithm in WSN-Satellite Integrated Networks
- Analysis of intelligent compression methods for traffic transmission in satellite communication channels
- A comparative analysis for data compression using AI models
- A Systematic Review of Literature on AI Methods for Latency Reduction in Satellite Communications
- Efficient Data Aggregation Methods and Advanced Analytics for Wireless Sensor Networks
- A Comparative Study of Time Series Data Compression Techniques: Performance Analysis and Evaluation
- Comparative Analysis of Time Series Data Aggregation Methods: Performance, Efficiency, and Accuracy
- “Federated Learning for Traffic Network Classification: A Decentralized Approach for Enhanced Data Privacy and Accuracy”
- “Efficient Federated Learning for Low-Latency Traffic Network Classification with Data Compression Strategies”
- “Clustered Federated Learning for Low-Latency Traffic Network Classification: A Satellite-Enabled Approach”
- “Enhancing Satellite Image Analytics with a Super-Resolution Based Diffusion Model”
- “Comparative Analysis of Image Prediction using Diffusion Models and GANs”
- “Time Series Data Classification using Graph Neural Networks: An Investigative Study”
- “Comparative Analytics of Deep Learning Approaches for Traffic Network Classification”
- “Comparative Data Processing Methods for Deep Learning-based Traffic Anomaly Network Classification”
- “Latency Reduction in Satellite Data Transmission for Time Series Data Prediction”
- “Intelligent Data Compression for Reduced Latency in Satellite Data Transmission with Time Series Data”
- “Enabling Low-Latency Robotic Operations via Satellite Data Transmission”
- “Enhancing Robotic Operations via Low-Latency Data Transmission and Satellite-Assisted Video Encoding”
Tài liệu tham khảo
Internet
Hết.
