Using machine learning to provide reliable differentiated services for iot in sdn-like publish/subscribe middleware †

Keyphrases

• Machine Learning 100%
• Software-defined Networking 100%
• Differentiated Services 100%
• Publish-subscribe Middleware 100%
• Quality of Service 50%
• Programmability 50%
• Queuing Delay 50%
• Machine Learning Techniques 25%
• Two-layer 25%
• Delay Constraint 25%
• Quality of Service Guarantee 25%
• Service Scenario 25%
• Priority Queue 25%
• Management Mechanism 25%
• Internet of Things Services 25%
• Queue Management 25%
• Packet Loss Rate 25%
• OpenFlow Switch 25%
• Middleware Architecture 25%
• Real World Internet 25%
• Service Guarantee 25%
• Equal Quality 25%
• Flow Entry 25%
• Guarantee Mechanism 25%
• Extreme Gradient Boosting(XGBoost) 25%
• XGBoost Model 25%
• XGBoost Method 25%

Computer Science

• Software-Defined Networking 100%
• Differentiated Service 100%
• Machine Learning 100%
• Learning System 100%
• Quality of Service 75%
• Extreme Gradient Boosting 75%
• Programmability 50%
• Queueing Delay 50%
• Service Guarantee 25%
• End-to-End Delay 25%
• Packet Loss Rate 25%
• Openflow Switch 25%
• Service Requirement 25%
• Internet-Of-Things 25%