Skewless Network Clock Synchronization Without Discontinuity: Convergence and Performance

TL;DR

This paper introduces a novel skewless network clock synchronization algorithm that guarantees convergence without causing jitter or backward jumps, even in noisy environments and timing loops, outperforming traditional methods like NTP and PTP.

Contribution

The paper presents a new synchronization algorithm that avoids skew estimation and offset jumps, with proven convergence conditions and robustness to noise and timing loops.

Findings

Algorithm converges even with timing loops and noise.

Highly connected networks can outperform individual clients.

Optimized parameters reduce jitter and drift effects.

Abstract

This paper examines synchronization of computer clocks connected via a data network and proposes a skewless algorithm to synchronize them. Unlike existing solutions, which either estimate and compensate the frequency difference (skew) among clocks or introduce offset corrections that can generate jitter and possibly even backward jumps, our solution achieves synchronization without these problems. We first analyze the convergence property of the algorithm and provide explicit necessary and sufficient conditions on the parameters to guarantee synchronization. We then study the effect of noisy measurements (jitter) and frequency drift (wander) on the offsets and synchronization frequency, and further optimize the parameter values to minimize their variance. Our study reveals a few insights, for example, we show that our algorithm can converge even in the presence of timing loops and noise, provided that there is a well defined leader. This marks a clear contrast with current standards such as NTP and PTP, where timing loops are specifically avoided. Furthermore, timing loops can even be beneficial in our scheme as it is demonstrated that highly connected subnetworks can collectively outperform individual clients when the time source has large jitter. The results are supported by experiments running on a cluster of IBM BladeCenter servers with Linux.