Useful Links
Computer Science
Cloud Computing
Edge Computing
1. Introduction to Edge Computing
2. Foundational Concepts and Architecture Models
3. Enabling Technologies and Infrastructure
4. Data Management and Processing
5. Security and Privacy
6. Management and Orchestration
7. Use Cases and Applications
8. Challenges and Limitations
9. Advanced Topics and Future Trends
Data Management and Processing
Data Ingestion and Collection
Data Acquisition Methods
Sensor Data Collection
Stream Processing
Batch Processing
Data Ingestion Protocols
MQTT
CoAP
HTTP/HTTPS
WebSocket
Data Quality Management
Data Validation
Error Detection
Data Cleansing
Edge Data Processing
Real-Time Analytics
Stream Processing Frameworks
Apache Kafka
Apache Storm
Apache Flink
Complex Event Processing
Pattern Recognition
Data Filtering and Preprocessing
Noise Reduction
Data Normalization
Feature Extraction
Data Transformation
Edge Analytics
Statistical Analysis
Time Series Analysis
Anomaly Detection
Predictive Analytics
Data Storage at the Edge
Storage Types
Transient Storage
Persistent Storage
Distributed Storage
Database Technologies
Embedded Databases
SQLite
Berkeley DB
LevelDB
Time-Series Databases
InfluxDB
TimescaleDB
OpenTSDB
NoSQL Databases
MongoDB
Cassandra
Redis
Data Retention Policies
Lifecycle Management
Archival Strategies
Compliance Requirements
Data Synchronization and Integration
Cloud Synchronization
Synchronization Protocols
Conflict Resolution
Data Consistency Models
Edge-to-Edge Communication
Peer-to-Peer Synchronization
Mesh Data Sharing
Distributed Consensus
Data Integration Patterns
ETL Processes
Data Pipelines
API Integration
Previous
3. Enabling Technologies and Infrastructure
Go to top
Next
5. Security and Privacy