Dynamic Reconfiguration in Mobile Systems
FPL '02 Proceedings of the Reconfigurable Computing Is Going Mainstream, 12th International Conference on Field-Programmable Logic and Applications
A Hardware/Software Reconfigurable Architecture for Adaptive Wireless Image Communication
ASP-DAC '02 Proceedings of the 2002 Asia and South Pacific Design Automation Conference
Ambient intelligence: a computational platform perspective
Ambient intelligence
Performance aware tasking for environmentally powered sensor networks
Proceedings of the joint international conference on Measurement and modeling of computer systems
Energy Scavenging for Mobile and Wireless Electronics
IEEE Pervasive Computing
Improving Power Output for Vibration-Based Energy Scavengers
IEEE Pervasive Computing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 3 - Volume 04
A framework for mapping scalable networked applications on run-time reconfigurable platforms
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Multi-version scheduling in rechargeable energy-aware real-time systems
Journal of Embedded Computing - Real-Time Systems (Euromicro RTS-03)
Dynamic reconfiguration in sensor networks with regenerative energy sources
Proceedings of the conference on Design, automation and test in Europe
Comparison of energy intake prediction algorithms for systems powered by photovoltaic harvesters
Microelectronics Journal
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Environmental energy is becoming a feasible alternative to traditional energy sources for ultra low-power devices such as sensor nodes and smart watches. Moreover, the increasing need for flexibility and reconfigurability of such devices makes its energy management even more challenging. As a result, to efficiently exploit the potentially unlimited environmental energy, new adaptation strategies are required. In this paper we present a novel system reconfiguration strategy that exploits the intrinsic unpredictability of environmental energy to opportunistically reconfigure the device. To assess the effectiveness of the proposed reconfiguration strategy we first perform a theoretical evaluation using statistical energy profile distribution and then we evaluate its energy efficiency on a prototype device in the presence of bursty energy profiles that we emulated using a programmable energy source.