Task runtime prediction in scientific workflows using an online incremental learning approach

Keyphrases

• Cloud Resources 33%
• CPU Utilization 33%
• Data-centric 33%
• Learning Approaches 100%
• Mean Standard Deviation 33%
• Memory Consumption 33%
• Monitoring Data 66%
• Multi-tenant 33%
• Online Incremental Learning 100%
• Performance Estimation 33%
• Performance Variability 33%
• Profilers 33%
• Proposed Strategy 33%
• Realistic Scenario 33%
• Regression Machine Learning 33%
• Regression Techniques 33%
• Resource Monitoring 66%
• Resource Provisioning 33%
• Runoff Prediction 100%
• Scheduling Plan 33%
• Scientific Workflows 100%
• Service Platform 33%
• Service Workflow 33%
• Statistical Description 33%
• Task Execution 66%
• Time-series Records 33%
• Unique Characteristics 33%
• Workflow Management System 33%
• Workflow Scheduling 33%
• Workflow Tasks 33%

Computer Science

• Estimation Performance 33%
• Input/Output 33%
• Learning Approach 100%
• Machine Learning Technique 33%
• Memory Utilization 33%
• Monitoring Data 66%
• Resource Provisioning 33%
• Scientific Workflow 100%
• Service Platform 33%
• Task Execution 66%
• Workflow Management System 33%
• Workflow-as-a- Service 33%