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Lossless compression of cloud-cover forecasts for low-overhead distribution in solar-harvesting sensor networks
Publikationstyp
Conference Paper
Date Issued
2014-11-06
Sprache
English
Author(s)
Start Page
43
End Page
48
Citation
2nd International Workshop on Energy Neutral Sensing Systems (ENSsys 2014)
Contribution to Conference
Publisher DOI
Scopus ID
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.
Subjects
Cloud cover
Compression
Harvest prediction
Solar-powered sensor networks