ICCPS '12 Proceedings of the 2012 IEEE/ACM Third International Conference on Cyber-Physical Systems
Approach for defining intelligent systems technical performance metrics
Proceedings of the Workshop on Performance Metrics for Intelligent Systems
Pacemaker control of heart rate variability: A cyber physical system perspective
ACM Transactions on Embedded Computing Systems (TECS) - Special section on ESTIMedia'12, LCTES'11, rigorous embedded systems design, and multiprocessor system-on-chip for cyber-physical systems
Online learning of timeout policies for dynamic power management
ACM Transactions on Embedded Computing Systems (TECS)
A cyber-physical system approach to artificial pancreas design
Proceedings of the Ninth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis
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Cyber-physical systems (CPS) represent the information technology quest of the 21-st century for a better, cleaner, safer life by integrating computation, communication, and control with physical processes. Physical processes are ubiquitously non-stationary and require time-dependent models for modeling and understanding their behavior. In contrast, most current computing platforms and their design methodologies lack proper models for the time component and mostly assume stationary (i.e., time independent) behavior. In this paper, we use empirical data to identify the main characteristics (e.g., self-similarity, nonstationarity) of various physical processes which can also be observed in the communication workload of real CPS. Starting from the complex characteristics of CPS workloads, we present a statistical physics inspired model which is used to define a new optimal control problem that not only accounts for the observed self-similarity and nonstationarity properties of the CPS workload, but also allows for accurate predictions on CPS dynamical trajectories during the optimization process.