Service of traffic demand
description
Transcript of Service of traffic demand
![Page 1: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/1.jpg)
Tájékoztatáshttp://digitus.itk.ppke.hu/~gosztony/
2.1 Loss systems2.2 Network traffic management
Highway tunnel
Infocomm networks’ planningtraffic aspects
PPKE ITK
2011/12tanév
ŐsziFélév
![Page 2: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/2.jpg)
2
Service of traffic demandIncoming demands (intensity, holding time)
over
flow
no free resourceservice principle:
loss limited delay delay
redirection loss
free waiting place
no waitingplace
waiting
Simplified scheme:human factors,
queue management, etc.
are missing.
Infocomm networks' planning - traffic aspects - 2011.09.21
no o
verfl
ow
![Page 3: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/3.jpg)
3
2.1-1
Erlang’s formula and its’ calculation
(The intensity of incoming demands is constant)
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 4: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/4.jpg)
4
• Structure: n identical channels (servers, trunks, slots) – homogeneous group
• Strategy: full accessibility, one demand – one channel if all channels are busy the demand is lost
without any after effect (lost calls cleared) Erlang’s loss model – Lost Calls Cleared (LCC
model)• Traffic:
exp. holding time distribution. μ intensity (1/μ mean value, „holding time”)
arrival rate: intensity (Poisson process) pure birth and death process Pure Chance
Traffic type One PCT-1
Erlang’s model –1.
Infocomm networks' planning - traffic aspects - 2011.09.21See the Textbook: Chapter 4
![Page 5: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/5.jpg)
5
• Offered traffic: offered traffic = carried traffic, if n∞
• Considered cases: (n = ∞ Poisson distribution) n < ∞ truncated Poisson distribution
• Performance measures E (time congestion) B (call congestion) C (traffic congestion)The model is insensitive to the
holding time distribution
that is: mean arrival rate x mean holding time
Infocomm networks' planning - traffic aspects - 2011.09.21
Erlang’s model –2.
![Page 6: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/6.jpg)
6
Insensitivity:
A system is insensitive to the holding time distribution
if the state probabilities of the system only depend on the
mean value of the holding time.
Infocomm networks' planning - traffic aspects - 2011.09.21
The model is insensitive to the holding time distribution
Erlang’s model –3.
![Page 7: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/7.jpg)
7
Erlang’s distribution -1.Traffic: PCT-1
Erlang’s distribution (truncated Poisson)
[conditional Poisson p(i i n) – see: Textbook]
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 8: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/8.jpg)
8
Time congestionAll n channels are occupied in a random point of time
Call congestionRejection of a random demand
Erlang B formula
Infocomm networks' planning - traffic aspects - 2011.09.21
Erlang’s distribution -2.
![Page 9: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/9.jpg)
9
Carried trafficMean value or expectation
Lost traffic
Traffic congestionE = B = Csince the intensity of demands is state independent
PASTA – Poisson arrivals see time averages
Infocomm networks' planning - traffic aspects - 2011.09.21
Erlang’s distribution -3.
![Page 10: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/10.jpg)
10
Tabular calculation aid:GG Honlap, GyakorlatokErlang B táblázat
A (traffic), from anyN (number of channels two theErlang B (congestion) third
Infocomm networks' planning - traffic aspects - 2011.09.21
Erlang’s distribution - 4.
![Page 11: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/11.jpg)
11
Generalisation of Erlang B• It is valid for any holding time distribution
(formulas depend only on the average holding time which is included in A, the offered traffic).
• The deduction assumed a Poisson arrival process. According to Palm’s theorem this is fulfilled, if the traffic is offered by many indpendent sources.
• Mathematical generalization is possible for fractional number of channels.
Erlang B formula is robust
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 12: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/12.jpg)
12
Evaluation of Erlang’s B formula - 1.
For large state spaces numerical difficulties may occur in calculating state probabilities.
Easily applicable methods and recursion formulas are available.[See: Textbook, Chapter 4.5)
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 13: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/13.jpg)
13
Not easy to handlesince n! and An increase rapidly
Useful recursion formula:
and
where:
Infocomm networks' planning - traffic aspects - 2011.09.21
Evaluation of Erlang’s B formula - 2.
![Page 14: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/14.jpg)
14
2.1-2
Infocomm networks' planning - traffic aspects - 2011.09.21
BPP-traffic models
(Generalization of Erlang’s classical loss system)
![Page 15: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/15.jpg)
15
BPP-traffic models -1.
Infocomm networks' planning - traffic aspects - 2011.09.21
BPPThese models are all insensitive to the service time distribution. Engset and Pascal models are even insensitive to the distribution of the idle time of sources. It is important always to use traffic congestion as the most important performance metric.
See the Textbook: Chapter 5
For these models the relationship between E, B and C congestion values and Z peakedness is well defined.
![Page 16: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/16.jpg)
16
BPP-traffic models -2.
Infocomm networks' planning - traffic aspects - 2011.09.21
See the Textbook: Chapter 5
Erlang distribution
n=number of channels
Arrival intensity: λ
![Page 17: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/17.jpg)
17
BPP-traffic models -3.
Infocomm networks' planning - traffic aspects - 2011.09.21
See the Textbook: Chapter 5
n=number of channels
Engset distribution
Arrival intensity: (S-i)
![Page 18: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/18.jpg)
18
BPP-traffic models -4.
Infocomm networks' planning - traffic aspects - 2011.09.21
See the Textbook: Chapter 5
Arrival intensity: (S+i)
n=number of channels
![Page 19: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/19.jpg)
19
Z, peakedness Peakedness (Z) The peakedness has dimension: [number of channels]
Poissondistribution:
Erlangdistribution:
„Number representation” Index of Dispersion for Counts – IDC= peakedness
1
2
m
Gives a characterization for the probability distribution of occupiedservers (lines, channels).
Binomial and Engsetdistribution:
In the case of binomial and Engset distribution β (offered traffic of free traffic sources), takes congestion already into account.
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 20: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/20.jpg)
20
For applications the traffic congestion C is the most important, as it is almost a linear function of the peakedness.
Infocomm networks' planning - traffic aspects - 2011.09.21
Textbook:Fig. 5.7
BPP-traffic models -5.
![Page 21: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/21.jpg)
21
2.1-3
Infocomm networks' planning - traffic aspects - 2011.09.21
Engset’s formula and its’ calculation
(The intensity of incoming demands depends on
the number of occupied traffic sources)
![Page 22: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/22.jpg)
22
Engset’s model -1.
Infocomm networks' planning - traffic aspects - 2011.09.21
• Structure: n identical channels (servers, trunks, slots) – homogeneous group
• Strategy: full accessibility, one demand – one channel if all channels are busy the demand is lost without
any after effect – LCC (lost calls cleared) model• Traffic:
exp. holding time distribution. μ intensity (1/μ mean value, „holding time”)
offered traffic, A = carried traffic, if the number of channels is not limited (independent of the number of channels)
pure birth and death process Pure Chance Traffic type Two PCT-2
Results are independent from the holding time distribution they depend on its’ average value.
![Page 23: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/23.jpg)
23
S traffic sources offer demands to n fully available channels. The arrival intensity of new demands is: (S-i)
Infocomm networks' planning - traffic aspects - 2011.09.21
Engset’s model -2.
![Page 24: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/24.jpg)
24
exponentially distributedtime intervals(assumption required for themathematical deduction)
Possiblestates of atraffic source
Infocomm networks' planning - traffic aspects - 2011.09.21
The traffic source
Engset’s model -3.
![Page 25: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/25.jpg)
25
Engset distribution - 1.
S > n
Cut equations exist for 0 ≤ i ≤ n .
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 26: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/26.jpg)
26
(See: Textbook Chapter 5.3) Normalization:
Distribution:(truncatedbinomial)
Engset, 1918 !!
offered trafficof free trafficsource
Infocomm networks' planning - traffic aspects - 2011.09.21
Engset distribution - 2.
![Page 27: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/27.jpg)
27
Time congestion
Call congestion
After some transformations:
Infocomm networks' planning - traffic aspects - 2011.09.21
Engset distribution - 3.
![Page 28: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/28.jpg)
28
As if the remaining S-1 traffic sources had occupiedall channels.
When S increases E is increasing too, therefore:
Interpretation:
Infocomm networks' planning - traffic aspects - 2011.09.21
Engset distribution - 4.
![Page 29: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/29.jpg)
29
Carriedtraffic:
transformation withcut equations
Infocomm networks' planning - traffic aspects - 2011.09.21
Engset distribution - 5.
![Page 30: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/30.jpg)
30
Traffic congestion:designation:
Number of calls (traffic demands) per time unit
(S – Y) the number of free traffic sources
SaArelationshipwas applied
Infocomm networks' planning - traffic aspects - 2011.09.21
Engset distribution - 6.
![Page 31: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/31.jpg)
31
Lost traffic:
Duration of state [i]
Improvement function
Infocomm networks' planning - traffic aspects - 2011.09.21
Engset distribution - 7.
![Page 32: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/32.jpg)
32
Relations between E, B and CDesignation:
Alreadyderived
Infocomm networks' planning - traffic aspects - 2011.09.21
Engset distribution - 8.
![Page 33: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/33.jpg)
33
There are numerical problems for large values of S and n. Various numerically stable recursive formulae have been elaborated.
Infocomm networks' planning - traffic aspects - 2011.09.21
Evaluation of Engset’s formula - 1.
recursion according n:
![Page 34: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/34.jpg)
34
recursion according S :
(See details in Chapter 5.5 of the Textbook)
Infocomm networks' planning - traffic aspects - 2011.09.21
Evaluation of Engset’s formula - 2.
Tabular calculation aid:GG Honlap, GyakorlatokEngset táblázat
S (number of sources), n (number of channels γ (call intesity)μ (release intensíty)
Engset E, B, CAA-Y
![Page 35: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/35.jpg)
35
recursion according n and S :
Based on the previous calculations
Evaluation: If the parameter is increasing recursions by n and by n and S are both good, but not acceptable for decreasing parameters. Recursion by decreasing S is however acceptable.
Infocomm networks' planning - traffic aspects - 2011.09.21
Evaluation of Engset’s formula - 3.
(See details in Chapter 5.5 of the Textbook)
![Page 36: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/36.jpg)
36
2.1-4
Overflow traffic
PeakednessSmooth and bursty traffic
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 37: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/37.jpg)
37
Overflow traffic - model Basic problem: traffic from node A to nodes B or C are directed on different „first choice” routes and if these are fully occupied the overflow traffic might use the „overflow” route
Nowadays these type of arrangements are used only in networks.
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 38: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/38.jpg)
38
Overflow traffic – Example 1a.
……10 erlPCT-I
16
8 81. 10 erl, 16 channels, E16=2,23%, lost traffic 0,223 erl.
8 8
PCT-ICould this be calculated in two steps ??
If yes,how ?
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 39: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/39.jpg)
39
8 8
PCT-I ??
2. 10 erl, 8 channels, E8 =33,832%, Alost = 3,3832 erl A’ =3,3832 erl, 8 channels, E8’=0,1457 A’lost= 3,3832 x 0,1457 = 0,0483 erl. 0,223 erl = 0,0483 erl What is the reason ???
Overflow traffic does not have PCT-I/PCT-II character
Infocomm networks' planning - traffic aspects - 2011.09.21
Overflow traffic – Example 1b.
![Page 40: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/40.jpg)
40
1. Peakedness Z is a good indicator for the relative loss probabilities of traffics with the same average value (A).
2. For a given A traffic Z has a maximum as a function of n, the number of channels.
3. For PCT-I Z = 1.4. If Z < 1, the traffic is smooth.5. If Z > 1, tha traffic is bursty.6. Congestion: smooth < PCT-I < bursty.
Overflow traffic - peakedness –1.
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 41: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/41.jpg)
41
Peakedness Z of overflow traffic as a function of the offered PCT-1 traffic (A) and the number of channels (n)
Infocomm networks' planning - traffic aspects - 2011.09.21
Overflow traffic - peakedness –2.
Textbook:Fig. 6.8
![Page 42: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/42.jpg)
42
IPP principleIPP = Interrupted Poisson Process
Principle: the process is in theoff state, if there are free channels in the primary route;if there isn’t any free channel it is in the in state.
For practical applications of the method one has to determine the actual values of the parameters involved.
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 43: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/43.jpg)
43
Dimensioning overflow systems
ERT (Equivalent Random Theory)• an equivalent random traffic is applied which is derived
from the average value (expected value) and the variance of the overflow traffic
Modified ERT• calculation is based on a Z peakedness value which is
derived from the average value (expected value) and the variance of the overflow traffic
IPP (Interrupted Poisson Process)• If the primary route is occupied, a random (Poisson)
traffic appears temporarily (in an interrupted way) on the secondary route.
Infocomm networks' planning - traffic aspects - 2011.09.21
Textbook: Chapter 6.
![Page 44: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/44.jpg)
44
2.1-5
Multi-dimensional loss systems
Example:multi-dimensional Erlang-B loss formula
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 45: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/45.jpg)
45
• Structure: n uniform channels (trunks, slots) – homogenous group• Strategy:
full accessibility LCC - lost calls cleared
• Input process: two independent PCT-I traffic streams with 1 and 2 intensity holding times: exp. distribution. μ1 and μ2 intensity
• Offered traffic A1= 1/μ1 and A2 = 2/μ2
Model – 1.
Infocomm networks' planning - traffic aspects - 2011.09.21
Textbook: Chapter 7.
![Page 46: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/46.jpg)
46
In state (i,j) i channels are occupied by the first,j channels are occupied by the secondtraffic stream.
Restrictions:
Statistical equilibrium, (n+1)(n+2)/2 node equations.
Infocomm networks' planning - traffic aspects - 2011.09.21
Model – 2.
One demand occupies one channel.
![Page 47: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/47.jpg)
47
Number of states:(n+1)(n+2)/2
Example of node equation:
p(0,1)[1+2+μ2]=p(0,0) 2 +p(1,1) μ1 +p(0,2)2μ2
Infocomm networks' planning - traffic aspects - 2011.09.21
Model – 3.
![Page 48: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/48.jpg)
48
Multi dimensional Erlang distr. – 1.The state space diagram depicts a reversible Markov process with local balance and with product form solution.
It can be shown that the solution is: where: p(i) and p(j) are one dimensional, truncated Poisson distributions and Q is the normalisation constant
Poisson Arrivals See Time Averages – PASTA !!
Időtorlódás Hivástorlódás P(i+j=n)Forgalmi torlódás
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 49: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/49.jpg)
49
2
0
)(21
2
0
212
0 )!()(
!!)()(
ji
ji
ji
ji
ji jiAAQ
jiAAQjpip
2
0
21
22
21
21
21
22
21
2121
2
0
!)(
)22
()(1
)22
1(
)2,0()0,2()1,1()1,0()0,1()0,0()()(
x
x
ji
xAAQ
AAAAAAQ
AAAAAAQ
ppppppjpip
n22n1nnn bnn
...ba2n
ba1n
a0n
)ba(
Generalization by
Newton’s binomiallaw
Infocomm networks' planning - traffic aspects - 2011.09.21
Multi dimensional Erlang distr. – 2.
![Page 50: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/50.jpg)
50
It can be found, that:
This is a truncated Poisson distribution, with offer traffic
Infocomm networks' planning - traffic aspects - 2011.09.21
Multi dimensional Erlang distr. – 3.
![Page 51: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/51.jpg)
51
Generalization for N traffic streams:
Course of calculation:
Time congestion, etc.
PASTA !
q(x) relativ state probabilityp(x) absolute state probability
Infocomm networks' planning - traffic aspects - 2011.09.21
Multi dimensional Erlang distr. – 4.
![Page 52: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/52.jpg)
52
2.2
TTE – in networks
Network traffic management
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 53: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/53.jpg)
53
TTE in networks – 1.
Traffic engineering functions
ITU-T Rec. E.360.1 (02/05) – Framework for QoS routing and related traffic engineering methods for IP ......
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 54: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/54.jpg)
54
regulates the service provided by the network through capacity and routing adjustments.
Input
„noisy”traffic load
unkownforecast
error
predicted average demand instantaneoushour-to-hourday-to-day
week-to weekseasonal
load variations
Feedback
the time constants of the feedback controls are matched to the load variations
ITU-T Rec. E.360.1 (02.05) – Framework for QoS routing and related traffic engineering methods for IP ......
Infocomm networks' planning - traffic aspects - 2011.09.21
TTE in networks – 2.
![Page 55: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/55.jpg)
55
Traffic engineering functions include:
traffic management, capacity management, and network planning. Traffic management ensures that network performance is maximized under all conditions, including load shifts and failures.
Capacity management ensures that the network is designed and provisioned to meet performance objectives for network demands at minimum cost.
Network planning ensures that node and transport capacity is planned and deployed in advance of forecasted traffic growth. Figure 1 illustrates traffic management, capacity management, and network planning as three interacting feedback loops around the network.
ITU-T Rec. E.360.1 (02.05) – Framework for QoS routing and related traffic engineering methods for IP ......
Infocomm networks' planning - traffic aspects - 2011.09.21
TTE in networks – 3.
![Page 56: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/56.jpg)
56
3.35 traffic engineering: Encompasses traffic management, capacity management, traffic measurement and modelling, network modelling, and performance analysis.
3.36 traffic engineering methods: Network functions which support traffic engineering and include call routing; connection routing, QoS resource management, routing table management, and capacity management.
3.37 traffic stream: A class of connection requests with thesame traffic characteristics
ITU-T Rec. E.360.1 (02.05) – Framework for QoS routing and related traffic engineering methods for IP ......
Infocomm networks' planning - traffic aspects - 2011.09.21
TTE in networks – 4.
![Page 57: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/57.jpg)
57
3.27 QoS (Quality of Service): A set of service requirements to be met by the network while transporting a Connection or flow; the collective effect of service performance which determine the Degree of satisfaction of a user of the service.
3.28 QoS resource management: Network functions which include class-of-service identification, routing table; derivation, connection admission, bandwidth allocation, bandwidth protection, bandwidth reservation, priority routing, and priority queuing.
3.29 QoS routing: See QoS Resource Management.
3.30 QoS variable: Any performance variable (such as congestion, delay, etc.) which is perceivable by a user.
ITU-T Rec. E.360.1 (02.05) – Framework for QoS routing and related traffic engineering methods for IP ......
Infocomm networks' planning - traffic aspects - 2011.09.21
TTE in networks – 5.
![Page 58: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/58.jpg)
58
TTE in IP networks - example a-1. Rec. ITU-T Y.1543 (2007.11.)Measurements in IP networks for inter-domainperformance assessment
The performance attributes that are used to characterize the network performance (inter-domain QoS) of a path are:
• Mean one-way delay.• One-way packet delay variation.• Packet loss ratio.• Path unavailability.
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 59: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/59.jpg)
59
ITU-T Y.1543 (2007.11.) Measurements in IP networks for inter-domain performance assessment
Infocomm networks' planning - traffic aspects - 2011.09.21
TTE in IP networks - example a-2.
![Page 60: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/60.jpg)
60
TTE in NGN networks - example b-1. Recommendation ITU-T Y.2173 (2008.09.)Management of performance measurement for NGN
SummaryThis Recommendation specifies requirements, reference measurement network model, high-level and functional architectures, and procedures for performance measurement management. This Recommendation together with [Recommendation ITU-T Y.1543] provides overall consistency for performance measurement and management of NGN.ScopeThis document specifies the management aspects of performance measurement:- Requirements for management of performance measurement....- A reference measurement network model....- A general and functional architecture for the management of performance measurement....- Management procedures covering various management scenarios.... - Application scenarios for management of performance measurement (MPM)
use cases.....
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 61: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/61.jpg)
61
ABG = Access Border Gateway
IBG = Interconnection Border Gateway
CPNE =Customer Premises Network Edge
Infocomm networks' planning - traffic aspects - 2011.09.21
TTE in NGN networks - example b-2.
Recommendation ITU-T Y.2173 (2008.09.)
![Page 62: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/62.jpg)
62
Traffic routing may be:• fixed
(Fixed Routing –FR)• time-dependent
(Time dependent Routing – TDR)• state dependent
(State Dependent Routing – SDR)• event dependent
(Event Dependent Routing – EDR)ITU-T Rec. E.350 (2000.03.)– Dynamic Routing Interworking(Framework for dynamic routing interworking in circuit-switched PSTN, narrow-band ISDN, and broadband ISDN networks)
Traffic routing (PSTN, ISDN) – 1.
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 63: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/63.jpg)
63
Fixed Routing (FR) In a fixed routing (FR) method, a routing table is
fixed for a traffic stream. Hierarchical or non-hierarchical routing structures may be realized based on fixed routing. In both hierarchical or non-hierarchical structures, the route set and route selection sequence are determined on a preplanned basis and maintained over a long period of time.
ITU-T Rec. E.350 (2000/03.) – Dynamic Routing Interworking
Infocomm networks' planning - traffic aspects - 2011.09.21
Traffic routing (PSTN, ISDN) – 1a.
![Page 64: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/64.jpg)
64
Time-Dependent Routing (TDR) Time-dependent routing (TDR) methods are a type
of dynamic routing in which the routing tables are altered at a fixed point in time during the day or week. TDR routing tables are determined on a preplanned basis and are implemented consistently over a time period. The TDR routing tables are determined considering the time variation of traffic load in the network. Typically, the TDR routing tables used in the network are coordinated by taking advantage of non-coincidence of busy hours among the traffic streams.
ITU-T Rec. E.350 (2000.03.) – Dynamic Routing Interworking
Infocomm networks' planning - traffic aspects - 2011.09.21
Traffic routing (PSTN, ISDN) – 1b.
![Page 65: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/65.jpg)
65
State-Dependent Routing (SDR)
In state-dependent routing (SDR), the routes in the routing tables are altered automatically according to the state of the network. For a given SDR method, the routing table rules are implemented to determine the route choices in response to changing network status, and are used over a relatively short time period. Information on network status may be collected at a central processor or distributed to exchanges in the network. The information exchange may be performed on a periodic or on-demand basis. SDR methods use the principle of routing calls on the best available route on the basis of network state information.
ITU-T Rec. E.350 (2000.03.) – Dynamic Routing Interworking
Infocomm networks' planning - traffic aspects - 2011.09.21
Traffic routing (PSTN, ISDN) – 1c.
![Page 66: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/66.jpg)
66
Event-dependent routing (EDR)
In event-dependent routing (EDR), the routing tables are updated locally on the basis of whether calls succeed or fail on a given route choice. In EDR, for example, a call is offered first to a fixed, preplanned route often encompassing only a direct route, if it exists. If no circuit is available on the preplanned routes, the overflow traffic is offered to a currently selected alternate route. If a call is blocked on the current alternate route choice, another alternate route is selected from a set of available alternate routes for the traffic stream according to the given EDR routing table rules. For example, the current alternate route choice can be updated randomly, cyclically, or by some other means, and may be maintained as long as a call is established successfully on the route.
ITU-T Rec. E.350 (2000.03.) – Dynamic Routing Interworking
Infocomm networks' planning - traffic aspects - 2011.09.21
Traffic routing (PSTN, ISDN) – 1d.
![Page 67: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/67.jpg)
67
Traffic routing - MPLS (IP, ….) - 1 Multiprotocol Label Switching (MPLS) is a mechanism in
high-performance telecommunications networks which directs and carries data from one network node to the next. MPLS makes it easy to create "virtual links" between distant nodes. It can encapsulate packets of various network protocols.
MPLS is a highly scalable, protocol agnostic, data-carrying mechanism. In an MPLS network, data packets are assigned labels. Packet-forwarding decisions are made solely on the contents of this label, without the need to examine the packet itself. This allows one to create end-to-end circuits across any type of transport medium, using any protocol. The primary benefit is to eliminate dependence on a particular Data Link Layer technology, such as ATM, frame relay, SONET or Ethernet, and eliminate the need for multiple Layer 2 networks to satisfy different types of traffic. MPLS belongs to the family of packet-switched networks.
http://en.wikipedia.org/wiki/MPLS - 2011.09. Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 68: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/68.jpg)
68
Traffic routing MPLS (IP, ….) - 2 MPLS operates at an OSI Model layer
that is generally considered to lie between traditional definitions of Layer 2 (Data Link Layer) and Layer 3 (Network Layer), and thus is often referred to as a "Layer 2.5" protocol. It was designed to provide a unified data-carrying service for both circuit-based clients and packet-switching clients which provide a datagram service model. It can be used to carry many different kinds of traffic, including IP packets, as well as native ATM, SONET, and Ethernet frames.
http://en.wikipedia.org/wiki/MPLS - 2011.09.
Infocomm networks' planning - traffic aspects - 2011.09.21
![Page 69: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/69.jpg)
69
Traffic calculationsApproximate end-to-end calculationmethods:
Assumptions:• If trunk groups of the networks are
independent
• If congestion probabilities are small
Multidimensional convolution algorithm(number of dimension equals to the number of trunk groups)
worst case
Infocomm networks' planning - traffic aspects - 2011.09.21
Number of states if state probabilities are applied
Textbook: Chapter 8.
![Page 70: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/70.jpg)
70
Service protection – 1.
For preferential subscribers (priority for e.g. first aid,) Depending from traffic load
• normal load cca. same congestion for all types of demands
• overload preference for some types of demands In digital switches
• call-gapping• priority (e.g. for hand overs in mobile networks)
In networks• trunk reservation• virtual channels protection
Infocomm networks' planning - traffic aspects - 2011.09.21
see next slides
![Page 71: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/71.jpg)
71
Trunk reservation
Infocomm networks' planning - traffic aspects - 2011.09.21
Service protection – 2a.
Textbook: Chapter 8.
![Page 72: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/72.jpg)
72
Trunk reservation
Infocomm networks' planning - traffic aspects - 2011.09.21
Service protection – 2b. previous slide
Textbook: Chapter 8.
![Page 73: Service of traffic demand](https://reader035.fdocuments.net/reader035/viewer/2022062310/568164d8550346895dd71d44/html5/thumbnails/73.jpg)
73
In systems with integrated services all services have to be protected against each other.
This can be obtained by e.g.:• a certain minimum allocation of bandwidht which
ensures a certain minimum service,• a maximum allocation which both allows for the
advantages of statistical multiplexing and ensures that a single service do not dominate.
Virtual channel protection
Infocomm networks' planning - traffic aspects - 2011.09.21
Service protection – 3.