Research challenges in wireless networks of biomedical sensors
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Minimizing execution time in MPI programs on an energy-constrained, power-scalable cluster
Proceedings of the eleventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Techniques for Multicore Thermal Management: Classification and New Exploration
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Design of a wireless sensor network platform for detecting rare, random, and ephemeral events
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Composition of Cyber-Physical Systems
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Verifying Noninterference in a Cyber-Physical System The Advanced Electric Power Grid
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IEEE Transactions on Parallel and Distributed Systems
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Task Scheduling for Control Oriented Requirements for Cyber-Physical Systems
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Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
A Component Model for Control-Intensive Distributed Embedded Systems
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Energy-Saving Service Scheduling for Low-End Cyber-Physical Systems
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Thermal-aware task scheduling for data centers through minimizing heat recirculation
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Joint Sleep Scheduling and Mode Assignment in Wireless Cyber-Physical Systems
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Spatio-Temporal Event Model for Cyber-Physical Systems
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A unifying specification logic for cyber-physical systems
MED '09 Proceedings of the 2009 17th Mediterranean Conference on Control and Automation
Towards a time-triggered schedule calculation tool to support model-based embedded software design
EMSOFT '09 Proceedings of the seventh ACM international conference on Embedded software
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ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on simulation in complex service systems
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A distributed cyber-physical system (DCPS) may receive and induce energy-based interference to and from its environment. This article presents a model and an associated methodology that can be used to (i) schedule tasks in DCPSs to ensure that the thermal effects of the task execution are within acceptable levels, and (ii) verify that a given schedule meets the constraints. The model uses coarse discretization of space and linearity of interference. The methodology involves characterizing the interference of the task execution and fitting it into the model, then using the fitted model to verify a solution or explore the solution space.