Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
162 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Sundial: Using Sunlight to Reconstruct Global Timestamps (1901.09670v1)

Published 28 Jan 2019 in cs.NA, cs.SY, math.NA, and eess.SY

Abstract: This paper investigates postmortem timestamp reconstruction in environmental monitoring networks. In the absence of a time-synchronization protocol, these networks use multiple pairs of (local, global) timestamps to retroactively estimate the motes' clock drift and offset and thus reconstruct the measurement time series. We present Sundial, a novel offline algorithm for reconstructing global timestamps that is robust to unreliable global clock sources. Sundial reconstructs timestamps by correlating annual solar patterns with measurements provided by the motes' inexpensive light sensors. The surprising ability to accurately estimate the length of day using light intensity measurements enables Sundial to be robust to arbitrary mote clock restarts. Experimental results, based on multiple environmental network deployments spanning a period of over 2.5 years, show that Sundial achieves accuracy as high as 10 parts per million (ppm), using solar radiation readings recorded at 20 minute intervals.

Citations (25)

Summary

We haven't generated a summary for this paper yet.