Contents Telektronikk - Telenor

78
with two to four hours read-out, can be
proper. The dimensioning can then follow
Moe’s principle.
Many of the overflow networks are very
complicated, with lots of alternatives.
The complexity of the network may be
limited by the risk of jeopardising its
manageability, the traffic control and the
means of measuring. If these are exceeded,
the complication can become
problematic.
One may ask if these observations and
conclusions, mainly dating from the
1980s, are pertinent in the future network
services: now the components are cheap
and capacity costs almost nothing. A few
comments will be given.
Service quality of a network depends on
some bottlenecks in the network. These
impair the service when the load limit is
reached. The bottlenecks are probably
not in transmission routes any more, but
in signalling, data transmission channels
or processors, getting blocked first.
These limits must be identified by the
operator, who has to know how near the
calculated limits the actual loads are.
There, the peak-hour or other dimensioning
period intensities with their models
will be needed for capacity calculations,
even in the future. Some of the load variations
follow these, as described above,
some are of new types. Measurements
clear the traffical facts – models just help
in thinking. The augmentations can then
be prepared in time. Otherwise, the operator
will be in for a surprise.
Network economy becomes more complicated
when, instead of circuit-groups, the
dimensioning objects are clusters, networks,
and groups of competing operators’
networks, serving clients of various
services. This higher level of traffic
dimensioning and optimising is not easy
to manage without knowledge of the
simple components’ traffical relations.
Or what is even worse, if the complicated
network is still controlled on the basis of
obsolete elementary conceptions.
Traffic modelling traditionally concentrates
on Poissonian distribution inside
the hour and regular variations between
the hours, days and seasons. The above
described measurements do not support
this concept: traffic variations usually
exceed the expected. Rather some grade
of self-similarity, known in mathematics
of fractions, can be found, which opens
ways to very different thinking in the
future.
13 Acknowledgements
The above described measurement have
been made during several years, partly to
answer some questions raised by the
CCITT Study Group 2, partly arisen from
local interest. I owe my warm thanks to
the following specialists and colleagues
at Helsinki Telephone Company: Dr.
Pekka Lehtinen programmed the
AUTRAX equipment to produce several
traffic data simultaneously and continuously,
and analysed traffic variations.
MSc Matti Mäkelä and BSc Kari Laaksonen
with their staff carried out the traffic
measurements in practice. MSc Yrjö
Viinikka of Oy Comptel Ab took care of
the data handling.
14 Documentation
The above referred studies about optimising
and the traffic measurements in
Helsinki, have been published in full in
the following papers:
1 Ahlstedt, B V M. Load variance and
blocking in automatic telephone traffic:
load duration, a basis for dimensioning
: blocking duration, a yardstick
for traffic quality. I: 5th international
teletraffic congress, ITC 5,
524–530, New York, 1967.
2 Lehtinen, P I. Extreme value control
and additive seasonal moving average
model for the evaluation of daily
hour traffic data. I: 9th international
teletraffic congress, ITC 9, Torremolinos,
1979.
3 Parviala, A. The suboptimal alternate
routing practice with non-coincident
busy hours. I: 10th international teletraffic
congress, ITC 10, Montreal,
1983.
4 Parviala, A. The dimensioning of
alternate routing by a simple algorithm,
taking into account the nonideal
parameters. I: 5th Nordic teletraffic
seminar, NTS 5, Trondheim,
1984.
5 Parviala, A. The stability of telephone
traffic intensity profiles and its
influence on measurement schedules
and dimensioning. I: 11th international
teletraffic congress, ITC 11,
Kyoto, 1985.
6 Parviala, A. The stability of daily
telephone traffic intensity profiles
and its influence on measurement
routines. I: 6th Nordic teletraffic
seminar, NTS 6, Copenhagen, 1986,
and Sähkö 60, 26–30, 1987.
7 Parviala, A. Peak-hour and other
peaks of day. I: 8th Nordic teletraffic
seminar, NTS 8, Espoo, 1987.
8 Parviala, A. The stability of the daily
intensity profiles and its influence on
the choice of measurement routines
in telephone traffic in single lowcongestion
circuit-groups or overflow
clusters. I: 12th international
teletraffic congress, ITC 12, Torino,
1988.
9 Parviala, A. The reality of busy hour
in history and in measurements. I:
9th Nordic teletraffic seminar, NTS
9, Kjeller, 1990, and I: 13th international
teletraffic congress, ITC13,
Copenhagen, 1991, WS History.
10 Parviala, A. The year’s highest vs.
consecutive days. I: 10th Nordic teletraffic
seminar, NTS 10, Aarhus,
1992.
11 Parviala, A. Traffic reference period.
I: 11th Nordic teletraffic seminar,
NTS 11, Stockholm, 1993, and I:
14th international teletraffic congress,
ITC 14, Antibes, 1994. Spec.
Traffic Measurements.