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  1. Proceedings of the 6th ACM Workshop on Real World Wireless Sensor Networks (RealWSN '15)
  2. Optimising Low Power Dual Prediction Systems
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Real-world Drone Sensor Networks: A Multi-disciplinary Challenge
Paint it Black: Increase WSN Energy Efficiency with the Right Housing
IEEE 802.15.4 Channel Diversity in an Outdoor Environment
Listening to the Giants: Using Elephant Infra-Sound to Solve the Human-Elephant Conflict
Panel: Student Competitions to Motivate Research in Wireless Sensor Networks
Optimising Low Power Dual Prediction Systems
An Architectural Concept for Sensor Cloud QoSaaS Testbed
Monitoring A Large Construction Site Using Wireless Sensor Networks
Minimising the Entry Effort in Experimenting with WSN Testbeds to Perform Heterogeneous Research
SenseFlow: An Experimental Study of People Tracking
ReStructure: A Wireless Sensor Network for Monitoring Temporary Earth Retaining 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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