Process Variations and their Impact on Circuit Operation
DFT '98 Proceedings of the 13th International Symposium on Defect and Fault-Tolerance in VLSI Systems
Parameter variations and impact on circuits and microarchitecture
Proceedings of the 40th annual Design Automation Conference
Design of a wireless sensor network platform for detecting rare, random, and ephemeral events
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Energy optimality and variability in subthreshold design
Proceedings of the 2006 international symposium on Low power electronics and design
CASES '06 Proceedings of the 2006 international conference on Compilers, architecture and synthesis for embedded systems
Distributed power-management techniques for wireless network video systems
Proceedings of the conference on Design, automation and test in Europe
A case for opportunistic embedded sensing in presence of hardware power variability
HotPower'10 Proceedings of the 2010 international conference on Power aware computing and systems
VarEMU: an emulation testbed for variability-aware software
Proceedings of the Ninth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis
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As an emerging technology, sensor networks provide the ability to accurately monitor the characteristics of wide geographical areas over long periods of time. The lifetime of individual nodes in a sensor network depends strongly on the leakage power that the nodes dissipate in the idle state, especially for low-throughput applications. With the introduction of advanced low power design techniques, such as sub-threshold voltage design styles, and the migration of fabrication processes to smaller technology generations, variability in leakage power dissipation of the sensor nodes will lead to increased variability in their lifetimes. In this paper, we analyze how this increased variability in the lifetime of individual sensor nodes affects the performance and lifetime of the network as a whole. We demonstrate how sensor network designers can use the proposed analysis framework to trade-off the cost of a sensor network deployment with the performance it offers. Our results indicate that up to 37% improvement in the critical lifetime of a sensor network (defined as the expected time at which the sensor network becomes disconnected) can be obtained over a baseline design with a 20% increase in the cost of the individual sensor nodes.