NDLI: Optimising Low Power Dual Prediction Systems

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Optimising Low Power Dual Prediction Systems

Content Provider	ACM Digital Library
Author	Brusey, James Kemp, John Gaura, Elena Allen, Michael
Abstract	Abstract Low power protocols and data compression techniques can bring the average energy requirements for a WSN node within the capability of energy harvesting techniques. However, peak energy use may still exceed this capability. In this paper, based on our experience implementing a prototype WSN for an aerospace application, we identify two practical approaches that in combination significantly reduce energy use for sensor nodes using the Z-Stack network stack. While these solutions are necessarily platform-specific, they are expected to translate to other wireless node platforms. The solutions presented use non-default platform features in order to solve the issues of i) high power consumption on node startup due to network discovery and joining and ii) high power consumption of application level acknowledgements. The startup power consumption was reduced by 94.7%, while the cost of a sense-process-transmit-acknowledge cycle was reduced by 38.6%. This represents a significant reduction in node power consumption and is an important step in enabling the use of power harvesting.
Starting Page	7
Ending Page	10
Page Count	4
File Format	PDF
ISBN	9781450338400
DOI	10.1145/2820990.2820993
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-11-01
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Measurement Algorithms Power consumption Wireless sensing Performance
Content Type	Text
Resource Type	Article

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