Lossless Compression of Cloud-cover Forecasts for Low-overhead Distribution in Solar-harvesting Sensor Networks

Christian Renner, Phu Anh Tuan Nguyen

Abstract

Combining local harvest patterns and global weather forecasts, e.g., cloud-cover forecasts, makes solar harvest predictions and online duty cycle adaptation more reliable. For this purpose, an energy and bandwidth efficient network-wide distribution of those forecasts is required. To meet this end, we propose compression methods for cloud-cover forecasts, so that they can be piggy-backed on regular network packets. We evaluate compression performance based on data collected from an online weather service for more than 14 months. We find that (i) cloud-cover forecasts can be compressed by up to 76%, (ii) fit into an average of 5 B for a one-day and 21 B for a seven-day forecast horizon, so that (iii) network-wide distribution leveraging, e.g., software acknowledgments used by prominent low-power data collection algorithms is achievable.
OriginalspracheEnglisch
TitelProceedings of the 2Nd International Workshop on Energy Neutral Sensing Systems
Seitenumfang6
ErscheinungsortNew York, NY, USA
Herausgeber (Verlag)ACM
Erscheinungsdatum06.11.2014
Seiten43-48
ISBN (Print)978-1-4503-3189-0
DOIs
PublikationsstatusVeröffentlicht - 06.11.2014
Veranstaltung2nd International Workshop on Energy Neutral Sensing Systems - Memphis, USA / Vereinigte Staaten
Dauer: 06.11.201406.11.2014
Konferenznummer: 109622

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