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Challenges and Opportunities in Performance Evaluation: A Future Outlook

Explore future research directions in performance evaluation, focusing on problem-solving methodologies, implications, education needs, and interdisciplinary approaches. Address challenges in resource allocation, optimization, control theory, and signal processing. Discuss the confluence of information theory with performance evaluation, emphasizing minimizing communication resources in sensor networks. Delve into query processing, resource consumption minimization, and optimization problems in sensor data networks. Highlight the importance of multiple controllers in network control scenarios, emphasizing controller interactions and training needs for performance evaluation practitioners.

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Challenges and Opportunities in Performance Evaluation: A Future Outlook

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  1. Some Future Research Directions SIGMETRICS 2007 Don Towsley UMass-Amherst

  2. Overview • PE concerned with solving problems • implications? • some challenges • education for the system

  3. PE confluence of many areas PE  problem solving nail -> hammer screw -> screw driver nut -> wrench design exploration -> stochastic models measurements -> statistics resource allocation -> optimization theory dynamic rsrc alloc -> control theory

  4. game theory machine learning optimization PE statistics stochastic processes control theory signal processing information theory

  5. Information theory and PE • IT concerned with minimizing communication resources • entropy – communication usage bound • sensor networks characterized by • severe resource constraints • highly correlated data streams • network monitoring, radar networks, habitat sensor nets, …

  6. Query processing in data sensor networks Challenge: given set of queries, minimize resource consumption to satisfy query result metric Resources: bandwidth, power, processing, storage Metrics: error in result (rate distortion), power consumption, … Issues: complexity, resource constraints Tools: traditional PE, information theory, control theory, ML, …

  7. PE, control optimization, game theory Many PE problems are optimization problems • storage management • call admission • congestion/flow control Often between competing parties Need to address entire problem – not just evaluate performance of one instance

  8. Control Control Control Multiple controllers • network control • routing, congestion control, call admission • add an overlay • and another

  9. Control Control Multiple controllers • network control • routing, congestion control, call admission • add an overlay • and another • or an application Result? • controller mismatch? • well-tuned machine? • performance implications?

  10. Multiple controllers Issues: complex interactions among self-interested players Tools: traditional PE, control theory, game theory, economic theory

  11. Training for PE • background in • probability theory, stochastic processes, statistics • course(s) in performance evaluation • how to handle real world problems • right questions? assumptions • iterative modeling/validation process • combining analysis, simulation, measurements  use good case studies • exposure to (some of) • ML, information theory, convex optimization, differential equations, game theory, control theory, …

  12. Thanks!Questions?

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