TAG: a Tiny AGgregation service for ad-hoc sensor networks
ACM SIGOPS Operating Systems Review - OSDI '02: Proceedings of the 5th symposium on Operating systems design and implementation
Power-Aware Scheduling for Periodic Real-Time Tasks
IEEE Transactions on Computers
Real-Time Scheduling with Regenerative Energy
ECRTS '06 Proceedings of the 18th Euromicro Conference on Real-Time Systems
Distributed power-management techniques for wireless network video systems
Proceedings of the conference on Design, automation and test in Europe
Power management in energy harvesting sensor networks
ACM Transactions on Embedded Computing Systems (TECS) - Special Section LCTES'05
Robust and low complexity rate control for solar powered sensors
Proceedings of the conference on Design, automation and test in Europe
Energy aware dynamic voltage and frequency selection for real-time systems with energy harvesting
Proceedings of the conference on Design, automation and test in Europe
End-to-End Energy Management in Networked Real-Time Embedded Systems
IEEE Transactions on Parallel and Distributed Systems
Power Management Using ZigBee Wireless Sensor Network
ICETET '08 Proceedings of the 2008 First International Conference on Emerging Trends in Engineering and Technology
Minimum Variance Energy Allocation for a Solar-Powered Sensor System
DCOSS '09 Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Maximum utility rate allocation for energy harvesting wireless sensor networks
Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
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As Cyber-Physical Systems (CPSs) evolve they will be increasingly relied on to support time-critical monitoring and control activities. Further, many CPSs that utilize Wireless Sensor Networking (WSN) technologies require energy harvesting methods to extend their lifetimes. For this important system class, there are currently no effective approaches that balance system lifetime with system performance under both normal and emergency situations. To address this problem, we present a set of Harvesting Aware Speed Selection (HASS) algorithms. We use an epoch-based architecture to dynamically adjust CPU frequencies and radio transmit speeds of sensor nodes, hence regulate their power consumption. The objective is to maximize the minimum energy reserve over any node in the network, while meeting application's end-to-end deadlines. Through this objective we ensures highly resilient performance under emergency or fault-driven situation. Through extensive simulations, we show that our algorithms yield significantly higher energy reserves than the approaches without speed and power control.