Service placement and request scheduling for data-intensive applications in edge clouds

Keyphrases

• Service Placement 100%
• Service Request 100%
• Edge Cloud 100%
• Data-intensive Applications 100%
• Request Scheduling 100%
• Polynomial Time 66%
• Data Placement 66%
• Code Placement 66%
• Wireless 33%
• Optimal Performance 33%
• System Stability 33%
• Trace-driven Simulation 33%
• Storage Constraints 33%
• Network Bandwidth 33%
• Cloud Computing 33%
• Computational Resources 33%
• Budget Constraint 33%
• Storage Resources 33%
• Communication Delay 33%
• Resource Demand 33%
• Scheduling Algorithm 33%
• Time Service 33%
• Resource Constraints 33%
• Video Analytics 33%
• Operation Cost 33%
• Two-time Scale 33%
• Maximum Flow 33%
• System Operation 33%
• Communication Constraints 33%
• Constant-factor Approximation Algorithm 33%
• Placement Algorithm 33%
• Time-varying Demand 33%
• Auxiliary Graph 33%
• Set-valued Optimization Problem 33%
• Machine Learning Tasks 33%
• Data Bandwidth 33%
• Mobile Edge Computing 33%

Computer Science

• Polynomial Time 100%
• Data Placement 100%
• data-intensive application 100%
• Approximation (Algorithm) 50%
• Optimal Performance 50%
• System Operation 50%
• Network Bandwidth 50%
• Storage Resource 50%
• Communication Delay 50%
• Scheduling Algorithm 50%
• Resource Constraint 50%
• Video Analytics 50%
• Budget Constraint 50%
• Constant Factor 50%
• Systems Stability 50%
• Learning System 50%
• Machine Learning 50%
• Cloud Computing 50%
• Resource Demand 50%
• Placement Algorithm 50%
• Multi-Access Edge Computing 50%