All drawings appearing in this Recommendation have been done in Autocad.
Recommendation E.500
TRAFFIC INTENSITY MEASUREMENT PRINCIPLES
1 Introduction
1.1 Traffic measurements provide the data base from which the planning,
operation, management and, in some cases, accounting for transit considerations
of the telephone network are carried out. Different applications may exist for
the same traffic measurement.
1.2 This Recommendation gives the principles for measuring carried traffic and
bids on circuit groups and exchanges. The number of bids and preferably also
carried traffic intensity should also be determined by individual relations
(destinations). Data so obtained are applied both for operation and planning.
Recommendation E.501 gives methods for estimating offered traffic from carried
traffic measurements. Recommendation E.502 describes exchange requirements for
traffic measurements both in national and international exchanges. Recommendation
E.525 describes the traffic data analysis. Recommendation E.506 gives methods for
forecasting future traffic requirements. The remainder of the E.500 Series of
Recommendations describes how to utilize this data base in the operation and
planning of telephone networks.
The measurements required for network management as described in the E.410
Series are generally similar to those described in this Recommendation. They will
usually require a variable and shorter reporting interval.
2 Definitions
A measurement of the amount of traffic carried is the average Erlang value
during a certain period of time (e.g. 15 min., 1 hour).
A measurement of the number of bids is a count of this entity during a
certain period of time.
Measurements are taken continuously during the day or with exclusion of
known low traffic periods. The set of days at which measurement has been taken is
called the measurement days.
In the yearly continuous measurement the measurement days are
post-selected from a base period with a length of the whole year. The
post-selected days include the peak intensity values measured during the base
period.
In the yearly non-continuous measurement the measurement days are
scheduled (pre-selected) from a base period of a few months. The pre-selected
days include the high load days of expectation or of earlier observations.
A traffic profile is defined to be stable when the individual daily
traffic profiles differ only little in shape and traffic volume between each
other.
A traffic profile is defined to be unstable when the individual daily
traffic profiles differ in shape or traffic volume between each other.
3 Overview
Circuit group dimensioning is based on a congestion objective, on the
traffic intensity values at high load time and on the forecast value of intensity
until the next augmentation of circuits. Intensity is measured during a daily
busy hour and averaged over a number of days, to avoid exceptional values.
If traffic measurements are taken every day of the year (yearly continuous
measurements), the required averages can be calculated directly as described in S
4. If traffic measurements are taken only during a limited number of days in the
year (yearly non-continuous measurements), the equivalent traffic loads may be
estimated using the procedures given in S 5.
The busy hour concept is an important aspect of teletraffic engineering
and may be applied in a number of ways. In the E.500 Series of Recommendations
the busy hour traffic used is an average of several days with, in some cases, an
allowance for day to day variations (Recommendation E.521).
Within the busy hour, traffic is considered to be stationary and thus the
recorded intensity is the mean value during the busy hour.
The recommended standard method of calculating the daily average requires
continuously measuring all quarter hours for all days concerned and selecting the
busiest hour in the average profile for all days. This method is called the
Time-Consistent Busy Hour (TCBH) and is described in detail in S 6. This method
is most valuable in situations of stable traffic profiles. The daily continuous
measurements provide the data necessary for confirming profile stability.
Another method of arriving at the representative average busy hour also
Fascicle II.3 - Rec. E.500 PAGE1
involves continuously measuring all quarter hours, but only the busiest hour of
each day is retained for averaging. This method is called the Average Daily Peak
Hour (ADPH) and is described in detail in S 6 together with the relation of ADPH
results to TCBH results.
The advantages of ADPH are that it requires less data storage and
manipulation than TCBH and that it gives a more representative value in the
situation of unstable traffic profiles.
In some situations Administrations do not measure traffic continuously
over the day, but only for the hour or few hours expected to be busiest. This
method is called the Fixed Daily Measurement Period (FDMP) or Fixed Daily
Measurement Hour (FDMH) and is described in detail in S 7 together with the
relation of FDMP results to TCBH results.
The advantage of FDMP is that it requires less measurement resources than
TCBH or ADPH. The disadvantage is that in individual situations the difference
between FDMP and TCBH results may vary widely.
In some network situations significant savings can be made by multihour
dimensioning (e.g. cluster engineering, time zone differences). This requires
daily continuous measurements.
4 Yearly continuous measurements
Traffic statistics should be measured for the significant period of each
day of the whole year. The significant period may in principle be 24 hours of the
day.
The measurements for computing normal traffic load should be the 30
highest days in a fixed 12-month period. Normally these will be working days, but
in some cases separate weekend or tariff-related period measurements should be
examined so that Administrations can agree bilaterally on appropriate measures to
maintain a reasonable grade of service (GOS) for weekends and tariff-related
periods. Recurring exceptional days (e.g. Christmas, Mother's Day, etc.) should
be excluded for network dimensioning purposes although the data should be
collected for network management purposes (Recommendation E.410). This method
gives traffic information of relatively high accuracy and is suitable for
circuits groups operated automatically or semiautomatically.
4.1 Normal and high load levels
Teletraffic performance objectives and dimensioning practices generally
set objectives for two sets of traffic load conditions.
A normal traffic load can be considered the typical operating condition of
a network for which subscribers service expectations should be met.
A high traffic load can be considered a less frequently encountered
operating condition of a network for which normal subscriber expectations would
not be met but for which a reduced level of performance should be achieved to
prevent excessive repeat calling and spread of network congestion.
In order to estimate normal and high load levels, offered traffic
intensity values should, where necessary, be estimated from daily carried traffic
measurements. Estimation procedures are presented in Recommendation E.501.
Normal and high loads are defined in Table 1/E.500.
TABLE 1/E.500
Circuit groups
Parameter Normal load High load
Carried traffic Mean of the 30 highest working Mean of the five highest days
intensity days during a 12-month period. in the same period as normal
load.
Number of bids Mean of the same 30 days on Mean of same five days on
which the offered traffic which the offered traffic
intensities are highest. intensities are the highest.
Exchanges
Parameter Normal load High load
Carried traffic Mean of the ten highest days Mean of the five highest days
intensity during a 12-month period. in the same period as normal
load.
Number of bids Mean of the same ten highest Mean of the five highest days
days (not necessarily the same (not necessarily the same as
as the highest offered traffic the highest offered traffic
days) during a 12-month days) in the same period as
period. normal load.
PAGE12 Fascicle II.3 - Rec. E.500
5 Yearly non-continuous measurements
5.1 Introduction
This method consists in taking measurements on a limited sample of days in
each year. Limited sample measurements will normally be taken on working days,
but Administrations may agree bilaterally to measure weekend or reduced tariff
periods separately.
Any Administration proposing to use a yearly non-continuous measurement
procedure is advised to confer with other end Administrations to ensure that the
maximum information is available to assist in the choice of measurement days. For
example, if the other end Administration has continuous measurement capability it
may be possible to identify busy seasons or consistent low-traffic days.
Table 2/E.500 shows the results of a study carried out on circuit groups
within a large metropolitan network [1]. The errors shown are the under-estimates
resulting if average busy hour carried traffic intensity is measured over a
pre-defined two-week period of the year, rather than the actual busiest two-week
period. (The pre-defined period was, in fact, the peak period of the preceding
year.)
The error averages 7.6% more or less, depending on circuit group size. Had
an Administration wished to estimate the true peak two-week intensity with 90%
confidence, starting with the pre-defined two-week measurements, the latter would
have had to be increased by amounts ranging from about 14% for large circuit
groups, up to about 31% for small ones. (The magnitude of these corrections
indicates how inadequate a two-week sample can be as a basis for network
planning.)
TABLE 2/E.500
Weighted mean error and the upper limit of the intensity error class for a cumulative
proportion of circuit groups, categorized according to traffic intensity
Total Low Medium High
< 10 Erl 10-100 > 100 Erl
Erl
Circuit groups 2728 1056 1564 110
Weighted mean error 7.6% 13.7% 7.8% 5.2%
of the intensity
value
Cumulative proportion
of circuit groups
50% 7.9% 12.9% 6.9% 3.9%
80% 16.9% 22.9% 17.9% 7.9%
Fascicle II.3 - Rec. E.500 PAGE1
90% 23.9% 30.9% 23.9% 13.9%
95% 31.9% 37.9% 34.9% 17.9%
98% 41.9% 47.9% 40.9% 26.9%
5.2 Estimation method
An approximate statistical method for estimating normal and high load
levels from limited sample measurements is provided below.
5.2.1 Principle of estimation method
Measurements are taken on a limited sample of days, and the mean (M) and
standard deviation (S) of the daily busy hour traffic loads are calculated.
Normal and high load level estimates (L) are given by:
L = M + k . S
different values of the factor k being used for normal and high load levels.
S = eq \b\bc\[ (\f( 1,n-1) ni=1 (Xi - M)2)1/2
where
Xi is the time-consistent busy hour traffic measured on the ith day,
M =eq \f( 1,n) \i\su(i=1,n,) Xi is the sample mean, and
n is the number of measurement days.
If the measurement period is less than 30 days then the estimate will not
be very reliable. In this case Administrations should, if possible, carry out
special measurement studies to determine typical values of the standard deviation
(e.g. as a function of the sample mean).
5.2.2 Base period for measurements
It is important to determine the "base period" since the length of this
period influences the values assigned to the multiplication factors k.
The base period is the set of valid days in each year from which
measurement days are preselected. This period should include all days which are
potential candidates for being among the 30 highest days (but excluding recurring
exceptional days - see S 4).
The base period may be restricted to a busy season (which need not
necessarily comprise a set of consecutive weeks) provided that the traffic is
known to be consistently higher during this period than during the remainder of
the year.
The base period may be the whole year, but Administrations may also decide
to exclude known low-traffic days.
5.2.3 Selection of measurement days
Measurement days should be distributed reasonably evenly throughout the
base period. If the base period extends over the whole year then the measurement
sample should include some days from the busiest part of the year, if these are
known. The limited sample should comprise at least 30 days to ensure reliable
estimates. If this is not possible, then a minimum of 10 measurement days may be
used. In this case the reliability of the estimate is poor.
5.2.4 Multiplication factors
Multiplication factors k for 5-day, 10-day, and 30-day load levels are
given by the curves in Figure 1/E.500, as a function of the number of days in the
base period. These factors are derived from tables of order statistics from the
normal distribution [2].
When the base period extends over the whole year these factors may not
always be reliable because of the effects of differing seasonal patterns.
Individual Administrations may then prefer to use different values for the
factors, if they have obtained more precise information from special measurement
studies.
Figure 1/E.500 - CCITT64220
5.2.5 Example
The following data illustrate the application of this procedure to the
estimation of normal and high load levels from non-continuous measurements on a
circuit group over a 1-year period.
After excluding holidays and other known low traffic periods the base
period which is available for measurement purposes is determined to be 220 days.
The k-factors to be used are therefore (from Figure 1/E.500):
Normal (30-day) load level: k = 1.6
High ( 5-day) load level: k = 2.3
Measurements are taken on 50 days within the base period. The daily
measured busy-hour traffic values, in Erlangs, are as follows:
21.5
PAGE12 Fascicle II.3 - Rec. E.500
20.5
18.7 15.0 18.4 21.6 18.1 24.2 26.7 22.1
21.8 17.8 17.2 19.8 15.2 20.4 16.7 20.6 23.1 23.5
19.6 18.1 21.3 15.9 15.9 17.8 17.4 20.9 25.9 20.6
20.9 19.2 17.6
Fascicle II.3 - Rec. E.500 PAGE1
12.9
14.2 18.1 16.9 24.2 22.2 26.8
22.5 22.8 19.3 19.1 18.7 19.8 18.0 26.0 22.5 27.5
The sample mean and standard deviation are:
M = 20.11
S = 3.37
The normal and high load level estimates are then calculated from L = M +
k . S to give:
Normal load = 25.5 Erlangs
High load = 27.9 Erlangs
5.2.6 High to normal traffic ratios
In some circumstances, actual values of high day loads are not available.
In such cases, various Administrations use standard ratios of high to normal load
for forecasting for design or planning purposes.
For example, as a general order of magnitude, the following ratios of high
to normal load may be used as a guide for a healthy network:
Parameter Circuit groups Exchanges
Offered traffic 1.2 1.1
intensity
Number of call 1.4 1.2
attempts
PAGE12 Fascicle II.3 - Rec. E.500
6 Daily continuous measurements
6.1 Measurement
It is recommended that Administrations take traffic measurements
continuously over the day throughout the measurement period.
Depending on the application, a busy hour value for dimensioning should be
calculated as the peak value of the mean day profile or the average of daily peak
values.
6.2 Time-consistent busy hour (TCBH)-intensity (post-selected)
For a number of days, carried traffic values for each quarter hour for
each day are recorded. The values for the same quarter hour each day are
averaged.
The four consecutive quarter-hours in this average day which together give
the largest sum of observed values form the TCBH with its TCBH-intensity. This is
sometimes referred to as post-selected TCBH.
In the case where a stable traffic profile exists, the TCBH-intensity is
used as a base method for dimensioning; if measurement methods yielding
systematically lower or higher intensity values than the TCBH-method are used,
adjustments to the calculations are needed.
6.3 Average of the daily peak hours traffic, defined n quarter
hour or on full hour basis
To find the average of daily peak quarterly defined hour (ADPQH)
intensity, the traffic intensity is measured continuously over a day in
quarter-hour periods. The intensity values are processed daily to find out the
four consecutive quarter hours with the highest intensity value sum. Only this
daily peak hour traffic intensity value is registered. The average is taken over
a number of working days peak intensities. The timing of peak intensity normally
varies from day to day.
To find the average of daily peak full hour (ADPFH) intensity, the traffic
intensity is measured continuously over a day in full-hour periods. Only the
highest of these intensity values is registered. The average is taken over a
number of days peak intensities.
The comparative measurements have shown that the traffic intensity values
measured by the ADPFH-method, are very consistent with the values measured by the
TCBH-method, whereas the ADPQH-method yields slightly (a few percent) higher
values. (See Annex A.) ADPH has an advantage over TCBH when traffic profiles are
unstable.
6.4 Alternate routing networks
When alternate routing is used, the dimensioning methods in Recommendation
E.522 should be applied (multi-hour dimensioning technique). In general this
requires the continuous measurement of a 24-hour profile for each traffic
quantity in the alternative routing cluster.
In Annex A the differences in results between busy hours defined for
individual circuit groups and for clusters indicate the advantage of continuous
measurements and multi-hour dimensioning for alternative routing networks.
In circumstances where the traffic profiles are stable and similar in the
whole cluster, the multi-hour dimensioning may be applied on a few selected hours
of significance to the entire cluster. The stability of traffic profiles must be
confirmed.
7 Daily non-continuous measurements
7.1 Measurement
Some Administrations may find it necessary or economically attractive to
restrict measurements to a few hours or only one hour per day. Such measurements
will always be less accurate than continuous measurements. The resulting busy
hour values will always be less than or equal to TCBH.
The time of fixed daily measurements should be confirmed several times a
year by measurement of the full daily traffic profile for every circuit group.
The measurement can cover several periods daily, as well.
7.2 Fixed daily measurement period (FDMP)
With this method measurements are taken within a fixed period (e.g. of 3
hours) each day. This period should correspond to the highest part of the traffic
profile, which is expected to include the TCBH. Measurement values are
accumulated separately for each quarter-hour, and the busiest hour is determined
at the end of the measurement period, as for the TCBH. This method will normally
give results which are about 95% of the TCBH traffic level, when the time of
fixed daily measurement is defined for every single circuit group, although major
Fascicle II.3 - Rec. E.500 PAGE1
changes in the traffic profile could lead to larger errors.
In alternate routing networks with traffic profiles that are similar and
stable in the whole cluster, FDMP may be used to produce measurements for
multi-hour dimensioning applied on a few selected hours of significance. The
stability of traffic profiles should be confirmed several times a year.
PAGE12 Fascicle II.3 - Rec. E.500
7.3 Fixed daily measurement hour (FDMH)
If the fixed daily measurement period is reduced to 1 hour, then it is
only necessary to accumulate a single measured value from each day. This is the
simplest measurement method, and it will normally give results which are about
90% of the TCBH traffic value, when the time of the fixed daily measurement is
defined for single circuit groups individually. However, the variations around
the average are large.
8 Flow chart for the application of the different calculation methods
The decisions represented in Figure 2/E.500 compare measurement and
analysis costs to variations in the results for a single circuit group or
cluster. The costs are particular to each Administration.
The preceding sections of this Recommendation indicate the amount of
measurement variance that can occur in typical situations which can result in
overprovisioning or a risk of poor grade of service.
In cluster engineering for alternative routing networks, measurements
outside the busy hour are normally needed if the traffic profile is unstable. In
situations of stable traffic load the significant traffic hours can be predicted
accurately, allowing use of a FDMP method.
Figure 2/E.500 - T0200810-87
ANNEX A
(to Recommendation E.500)
Example of influence of different busy hour definitions on
measured traffic intensity
A.1 Introduction
The influence of different busy hour definitions on measured traffic
intensity has been investigated by means of measurements on real traffic outgoing
from an international exchange.
Three clusters with a total of 15 circuit groups have been studied. One of
the clusters (Cluster 1) carries traffic between different time zones.
Traffic per quarter of an hour was measured during the whole day in 5
two-week periods (10 consecutive working days). The total elapsed time covered 9
months.
From the results of the first two-week period of daily continuous
measurements the times of FDMH and FDMP have been determined:
- for each circuit group individually (ind),
- per cluster (clu), and
- for all three clusters commonly (com).
The time of FDMH is equal to the time of TCBH in the first two-week
period. FDMP includes FDMH and the hour before and the hour after.
A.2 Results of measurements
The results of the measurements undertaken are summarized in Figures
A-1/E.500 to A-5/E.500.
Figure A-1/E.500 shows how the starting time of TCBH varies between the
five measurement periods:
- for each cluster, and
- for individual circuit groups in each cluster.
The following observations on the starting time of TCBH can be made:
- the starting time of TCBH is the same in not more than 2 periods. This
refers to both circuit groups and clusters;
- 5 circuit groups and 1 cluster have different TCBH in all periods;
- 8 circuit groups and 2 clusters have TCBH within the same part of the
day (morning or evening) in all periods;
- TCBH common to all clusters is in the evening in all periods. Only 2
periods have the same common TCBH.
In Figures A-2/E.500 to A-5/E.500 traffic intensities according to
different busy hour definitions have been compared. Traffic intensity according
to the TCBH definition has been used as reference value (corresponding to 100% in
the figures).
Figure A-2/E.500 shows the results of comparisons on a cluster level, and
Figures A-3/E.500 to A-5/E.500 on a circuit group level.
Means and variations of traffic intensities are given as:
- an average of all five periods (ADPQH and ADPFH), and
- an average of measurement periods 2, 3, 4 and 5 compared with period 1
(FDMH and FDMP).
Fascicle II.3 - Rec. E.500 PAGE1
A.3 Results on cluster level (Figure A-2/E.500)
ADPQH intensities over 100%, mean = 102%.
ADPFH intensities around 100%, mean = 100%.
FDMPclu intensities from 95 to 100%, mean = 99%.
FDMHclu intensities from 90 to 98%, mean = 94%.
FDMPcom intensities from 42 to 100%, mean = 89%.
FDMHcom intensities from 35 to 93%, mean = 83%.
A.4 Results on circuit group level (Figures A-3/E.500 to A-5/E.500)
ADPQH intensities over 100%, mean = 104%.
ADPFH intensities around 100%, mean = 100%.
FDMPind intensities from 88 to 100%, mean = 99%.
FDMHind intensities from 80 to 100%, mean = 93%.
FDMPclu intensities from 51 to 100%, mean = 98%.
FDMHclu intensities from 45 to 99%, mean = 91%.
FDMPcom intensities from 24 to 100%, mean = 89%.
FDMHcom intensities from 14 to 99%, mean = 81%.
Figure A-1/E.500 - T0200820-87
Figure A-2/E.500 - T0200830-87
Figure A-3/E.500 - T0200840-87
Figure A-4/E.500 - T0200850-87
Figure A-5/E.500 - T0200860-87
References
[1] PARVIALA (A.): The stability of telephone traffic intensity profiles and
its influence on measurement schedules and dimensioning (with Appendix).
11th International Teletraffic Congress, Kyoto 1985.
[2] Biometrika Tables for Statisticians, Table 9, Vol. 2. Cambridge University
Press, 1972.
PAGE12 Fascicle II.3 - Rec. E.500