A survey of design techniques for system-level dynamic power management
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special section on low-power electronics and design
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Wireless sensor networks for habitat monitoring
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Hardware/software partitioning of software binaries
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Dynamic hardware/software partitioning: a first approach
Proceedings of the 40th annual Design Automation Conference
The Chimaera reconfigurable functional unit
FCCM '97 Proceedings of the 5th IEEE Symposium on FPGA-Based Custom Computing Machines
Smart Sensor Architecture Customized for Image Processing Applications
RTAS '04 Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Design Space Exploration for Dynamically Reconfigurable Architectures
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
An Iterative Algorithm for Battery-Aware Task Scheduling on Portable Computing Platforms
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Stochastic modeling of a power-managed system-construction and optimization
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Online energy-saving algorithm for sensor networks in dynamic changing environments
Journal of Embedded Computing
HPCC'07 Proceedings of the Third international conference on High Performance Computing and Communications
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Sensor network applications face continuously changing environments, which impose varying processing loads on the sensor node. This paper presents an online control method which adapts the architecture to minimize energy consumption while satisfying varying latency constraints. The method predicts processing load requirements over a finite time window and accordingly adapts the architecture. The behaviour of the hardware modules over time has been approximated with a Continuous Time Markov Process. Adaptive image processing for vehicle tracking was used as a case study for this approach.