Basics of real-time measurement, control, and communication using IEEE 1588: Part 6
By John C. Eidson, Agilent Technologies
Hopefully, by this point in this series, the reader will have a good
understanding of IEEE 1588 technology and the ways it can be applied.
It should be clear from the discussions of applications in test and
measurement, industrial automation, and telecommunications that this is
a very active field of investigation, involving many companies and
researchers around the world.
However, it is far too early to be sure that IEEE 1588 will achieve widespread
adoption, or that the additional capabilities it brings to time-based
operations will prove sufficiently useful to displace or augment
existing technologies.
It is clear that IEEE 1588 has the potential to make a major
contribution to applications with hard real-time constraints. It is
probably not too much of a stretch to claim that IEEE 1588 will be
successful in the field of industrial automation and motion control.
The area of test and measurement is less certain, and depends as
much on how quickly the distributed architecture and peer-to-peer
communication model exemplified by the LXI specification is accepted,
as it does on the IEEE 1588 standard itself.
Telecommunications applications at this point must be considered
speculative. There are clearly areas within telecommunications where
IEEE 1588 has the potential to make significant contributions, but it
is not at all clear whether it will ultimately be adopted.
Proposed Techniques to Enable IEEE
1588 in Telecommunications
The telecommunication network impairments that degrade the performance
of an IEEE 1588 system are latency fluctuations and asymmetry. If only
frequency alignment is required, then asymmetry and the absolute value
of the latency are of no concern. However, if time transfer—epoch
alignment—is also required, then all impairments must be considered.
Asymmetry. Asymmetry impairments can arise from a variety of causes.
Optical fiber systems supporting two-way communication will have
different path lengths in the two directions as a result of chromatic
dispersion, even if the nominal line lengths are identical. In
practice, companies already correct for this effect by means of
additional fiber on the short path. This is essentially a calibration
process.
Far larger contributions to asymmetry can be expected from queuing
effects in switches. In addition, some network operators use ring
topologies in which traffic flows in only one direction, which leads to
vastly different path lengths for the forward and reverse
communications between two arbitrary points. There are also protocols
that are asymmetric by design, e.g., asymmetric digital subscriber
loops (ADSL).
If these factors can be rendered time-invariant by network
engineering techniques, then the needed corrections can be made by
calibrating the resulting network. This is not very appealing, but may
be the best that can be done.
It remains to be determined how well asymmetry can be controlled in
actual operating environments. Algie estimates that the latency across
a typical metropolitan area network is less than 20 ms. If this is the
case, then asymmetry-induced epoch offsets would be on the order of at
most 10 ms, which is probably not good enough for many of the proposed
telecommunications applications.
As discussed later, early data are discussed indicating that in some
circumstances the latency is substantially less. If it were possible to
transfer time to the edges of the metropolitan networks using existing
equipment, then it may be possible to use current IEEE 1588 techniques,
such as boundary clocks, to distribute time within an enterprise.
The most difficult environment for controlling asymmetry for the
telecommunications examples discussed earlier in this series is the
metropolitan area network, and the backhauls to wireless cell sites. In
building distribution or distribution within equipment racks, the
networks are much more likely to have controlled and stable asymmetry
properties.
Latency Fluctuations
Latency fluctuation impairments arise from a variety of sources. The
most common is queuing fluctuations in switches. These are particularly
troublesome because they are likely to be very traffic-dependent. A
second source of timing fluctuation is the equipment needed to
translate between communication protocols present in the network, e.g.,
the transition between a TDMA and a FDMA protocol, or from a T1 line to
SONET.
On a longer time scale, changes in path routing will also introduce
differences in latency. Furthermore, these fluctuations may not be the
same on the forward and reverse paths, which will further aggravate the
asymmetry problem.
The only practical solution to fluctuation is filtering the offset
and delay values computed by the slave clocks. Simple filtering is not
likely to be effective due to the time and traffic load dependence of
the magnitude and distribution of the delay values.
More sophisticated algorithms could monitor the distributions, and
make use of the holdover properties of the local oscillator to maintain
a stable time scale while the parameters for a new distribution are
computed.
It will probably be necessary to separately monitor the forward and
backward paths, since there is no reason to assume that the effects of
traffic will be uniform in the two directions.
The observation times for these filtering algorithms will be long.
If we assume that the fluctuations are uniformly distributed and have a
magnitude of about 2 ms, then the NTP curve suggests that to achieve an
Allan deviation of 10-8, observation times of about 1 day
will be required.
The early data discussed later indicate that observation times on
the order of a few hours may suffice. Observations times on this order
can be supported by quartz oscillators. If this is not the case, then
more stable oscillators such as rubidium will be required, which will
increase the cost and make the use of IEEE 1588 in these applications
much less attractive.