File: filter.adoc

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= Clock Filter Algorithm
include::include-html.ad[]

The clock filter algorithm processes the offset and delay samples
produced by the on-wire protocol for each peer process separately. It
uses a sliding window of eight samples and picks out the sample with the
least expected error. This page describes the algorithm design
principles along with an example of typical performance.

image::pic/flt5.gif["Wedge Scattergram",align="center"]

Figure 1. Wedge Scattergram

Figure 1 shows a typical _wedge scattergram_ plotting sample points of
offset versus delay collected over a 24 h period. As the delay
increases, the offset variation increases, so the best samples are those
at the lowest delay. There are two limb lines at slope ±0.5,
representing the limits of sample variation. However, it is apparent
that, if a way could be found to determine the sample of lowest delay, it
would have the least offset variation and would be the best candidate to
synchronize the system clock.

The clock filter algorithm works best when the delays are statistically
identical in the reciprocal directions between the server and client.
This is apparent in Figure 1, where the scattergram is symmetric about
the x axis through the apex sample. In configurations where the delays
are not reciprocal, or where the transmission delays on the two
directions are traffic dependent, this may not be the case. A common
case with DSL links is when downloading or uploading a large file.
During the download or upload process, the delays may be significantly
different resulting in large errors. However, these errors can be
largely eliminated using samples near the limb lines, as described on
the link:huffpuff.html[Huff-n'-Puff Filter] page.

In the clock filter algorithm the offset and delay samples from the
on-wire protocol are inserted as the youngest stage of an eight-stage
shift register, thus discarding the oldest stage. Each time an NTP
packet is received from a source, a dispersion sample is initialized as
the sum of the precisions of the server and client. Precision is defined
by the latency to read the system clock and varies from 1000 ns to 100
ns in modern machines. The dispersion sample is inserted in the shift
register along with the associated offset and delay samples.
Subsequently, the dispersion sample in each stage is increased at a
fixed rate of 15 μs/s, representing the worst case error due to skew
between the server and client clock frequencies.

In each peer process the clock filter algorithm selects the stage with
the smallest delay, which generally represents the most accurate data,
and it and the associated offset sample become the peer variables of the
same name. The peer jitter statistic is computed as the root mean square
(RMS) differences between the offset samples and the offset of the
selected stage.

The peer dispersion statistic is determined as a weighted sum of the
dispersion samples in the shift register. Initially, the dispersion of
all shift register stages is set to a large number "infinity" equal to
16 s. The weight factor for each stage, starting from the youngest
numbered _i_ = 1, is 2^-_i_^, which means the peer dispersion is
approximately 16 s.

As samples enter the register, the peer dispersion drops from 16 s to 8
s, 4 s, 2 s, and so forth. In practice, the synchronization distance,
which is equal to one-half the delay plus the dispersion, falls below
the select threshold of 1.5 s in about four updates. This gives some
time for meaningful comparison between sources, if more than one are
available. The dispersion continues to grow at the same rate as the
sample dispersion. For additional information on statistical principles
and performance metrics, see the link:stats.html[Performance Metrics]
page.

As explained elsewhere, when a source becomes unreachable, the poll
process inserts a dummy infinity sample in the shift register for each
poll sent. After eight polls, the register returns to its original
state.

image:pic/flt1.gif["Raw",align="left"] image:pic/flt2.gif["Filtered",align="right"]

Figure 2. Raw (left) and Filtered (right) Offsets

Figure 2 shows the performance of the algorithm for a typical Internet
path over a 24 h period. The graph on the left shows the raw offsets
produced by the on-wired protocol, while the figure on the right shows
the filtered offsets produced by the clock filter algorithm. If we
consider the series formed as the absolute value of the offset samples,
the mean error is defined as the mean of this series. Thus, the mean
error of the raw samples is 0.724 ms, while the mean error of the
filtered series is 0.192 ms. Radio engineers would interpret this as a
processing gain of 11.5 dB.

The reader might notice the somewhat boxy characteristic of the filtered
offsets. Once a sample is selected, it remains selected until a newer
sample with lower delay is available. This commonly occurs when an older
selected sample is discarded from the shift register. The reason for
this is to preserve causality; that is, time always moves forward, never
backward. The result can be the loss of up to seven samples in the shift
register, or -- more to the point -- the output sample rate can never be less
than one in eight input samples. The clock discipline algorithm is
specifically designed to operate at this rate.

'''''

include::includes/footer.adoc[]