Quality of Service inTelecommunication Networks
Åke Arvidsson, Ph.D.Ericsson Core Network Development, Sweden
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-082
Main Message
Traffic theory:– QoS is (partly) about congestion.– Congestion is partly caused by temporary overload.– Temporary overloads can be handled by statistics.– QoS can be controlled by statistics.
Typical issues for regulators:– Is an operator serious about quality of service?– What is the fair price to carry additional traffic?
Typical issues for operators:– How should a network be engineered?– Can I just go for “over-provisioning”!
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-083
Overview
Background and motivation.The significance of variations.Big variations means expenses.
– Relationship to shared networks.
Small variations means savings.– Relationship to shared networks.
Hot topic: Relevance to IP and integrated services.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-084
Background (1)
Voice and data traffic exhibit significant variations.Variable demand but fixed resources.
– Traffic may be lost.– Traffic may be delayed.– Traffic may be subject to other impairments.
Mathematically tractable by traffic theory.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-085
Background (2)
Can be used to control quality of service.Essential part of competition.
– Competitive advantage.– Add value to services.
Essential part of regulation/competition.– Fair treatment of new players by former monopolies.– Fair criteria for customers to choose service provider.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-086
Background (3)
Significance:– Society: Reliable services.– Operators: Stable systems, fair competition.– Users: Value for money.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-087
Background (4)
Requirements:– Prerequisite: The busy hour concept.– Delays: dialing tone, through connection, speech, ...
ITU-T, ETSI and others.– Blocking: lost traffic, ...
Typically operator dependent.– The above apply to voice services.
Data services specified but less used.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-088
Variations
The “problem” lies in variations:– Ideal: Fixed inter-arrival times and fixed service times:
Time
– Real: Variable inter-arrival times (and variable service times):
Time
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-089
Traffic Theory
Statistical analysis of service systems:– Waiting times.
Example: Dialing tone delay in a switch.– Congestion probabilities.
Example: Traffic rejected from a trunk.– Utilisations.
Example: Load on a processor or link.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0810
Quality of service vs. supply
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Capacity/Demand
Prob
abili
ty o
f suf
ficie
ncy
Better QoStakes more
capacityOnly0.53
No “over-supply”
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0811
Conclusions (1)
Dimension for average:– Variations unaccounted for.– Related impairments ignored.– No control of QoS!
Traffic theory necessary for QoS.– Correct provisioning aims at targeted QoS.– Over-provisioning is more than that, not just more than the
mean.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0812
Randomness (1)
More randomness means more problems.– More delay, higher blocking, etc.
Examples:– Circuit oriented traffic.
Erlang: Number of parallel connections.– Packet oriented traffic.
Load: A metric between zero and unit.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0813
Blocking and Variations
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Traffic variation (peakedness)
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ckin
g pr
obab
ility
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© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0814
Waiting Time and Variations
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Service time variation
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n w
aitin
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Load 0.5
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© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0815
Conclusions (2)
More randomness means more problems.– Split costs depend on traffic variations.
Simple “dimensioning” based on factors:– Correct answers for (at most) one working point only.
“Over-dimensioning” is not as simple as it may sound.– How much is too much?
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0816
Randomness (2)
Less randomness means less problems.– Less delay, lower blocking, etc.
Examples:– Circuit oriented traffic.
Erlang: Number of parallel connections.– Packet oriented traffic.
Load: A metric between zero and unit.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0817
Circuits per Erlang
Circuit oriented traffic.– How many circuits are needed for one Erlang?– Depends on performance and the scale of the system!
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Traffic
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uits
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erla
ng
High grade of service (0.5%)
Low grade of service (5%)
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0818
Packet Delay
Packet oriented traffic.– What is the delay for a packet/signal?– Depends on the load and the scale of the system!
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ay (s
)
30 parallel 64 kbps links;random/optimal sharing(20 octet packets)One 30×64 kbps link(20 octet packets)
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0819
Conclusions (3)
Less randomness means less problems.– Sharing networks reduces marginal costs.
“The bigger the better”.– One big system is better than many small systems.
Law of large numbers.– The more samples, the less variation.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0820
Classic Traffic Theory
Circuit switched services.– Erlang-B.
Agner Krarup Erlang(1878 – 1929)
KTAS, Copenhagen, 1917.
Pleased tomeet you!
– Wide range of extensions.
Packet switched services.– Signal networks.– Early arpanet community.
How about present IP?– Before: Best effort only.– Now: QoS required.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0821
Quality of Service in IP
Profitability:– Charging on QoS to boost income.
Integration:– Service integration to cut expenses.
Efficiency:– Utilise expensive wireless resources.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0822
Recent Developments (1)
Data (IP) traffic models:– Packets are like calls in telephone traffic.– Poisson process.– “Burstier” processes.
Ethernet (and other) measurements:– High spread (heavy tails).– Slow variations (long range dependence).– Time scale independence (self similarity).
Earlier models far too optimistic!– Forget the old economy, the new economy is here!
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0823
Results (1)
Heaviesttail
Lightesttail
Load≈71%
Queue10,000
Noqueue
Load≈ 50%
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0824
Recent Developments (2)
Objections:– Most data traffic is subject to flow control.
Queues cannot grow without bounds.– TCP applies dynamic flow control to maximise throughput.
Links may operate near (local) saturation.
Earlier diagram based on measured traffic.– Measurements are reality but– the experiments are not real since flow control is “frozen”.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0825
Results (2)
Earlier diagram Active flow control
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0826
Conclusions (4)
“New” discoveries not so dramatic.However, traffic and systems interaction complicates:
– Measurements:What does link load mean to user performance?
– Modeling:Simple steady state Poisson not generally applicable.
– Dimensioning:Traffic and performance mutually dependent.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0827
Recent Developments (3)
Research at Ericsson:– Mathematical methods.
Performance criterion:– Downloading time (useful throughput).
Examples:– Bottleneck identification and removal.– “Peak factor” calculations.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0828
Example: Bottlenecks (1)
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Access ratePacket dropPropagationW
indow sizeFile size
+ %
10 packetsFile size:
4 packetsWindow size:
100 msPropagation:
2 %Packet drop:
256 kbpsAccess rate:
10 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
256 kbpsAccess rate:
10 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
256 kbpsAccess rate:
10 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
256 kbpsAccess rate:
10 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
256 kbpsAccess rate:
94 kbpsThroughput: 130 kbpsThroughput:
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0829
Example: Bottlenecks (2)
05
101520253035404550
Access ratePacket dropPropagationW
indow sizeFile size
10 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
256 kbpsAccess rate:
20 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
256 kbpsAccess rate:+ %
20 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
256 kbpsAccess rate:
20 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
256 kbpsAccess rate:
20 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
256 kbpsAccess rate:
05
101520253035404550
Access ratePacket dropPropagationW
indow sizeFile size
130 kbpsThroughput: 165 kbpsThroughput:
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0830
Example: Bottlenecks (3)
05
101520253035404550
Access ratePacket dropPropagationW
indow sizeFile size
20 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
256 kbpsAccess rate:
20 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
512 kbpsAccess rate:+ %
20 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
512 kbpsAccess rate:
20 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
512 kbpsAccess rate:
20 packetsFile size:
4 packetsWindow size:
50 msPropagation:
2 %Packet drop:
512 kbpsAccess rate:
05
101520253035404550
Access ratePacket dropPropagationW
indow sizeFile size
165 kbpsThroughput: 216 kbpsThroughput:
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0831
Example: “Peak Factor” (1)
Network:– Packet loss probability 1%.– Round trip time 300 ms.
Users:– Access rate: 33% 64/128 kbps; 67% 64/384 kbps.– Packet size: 25% 536 bytes; 75% 1540 bytes.– Window size: 16.384 kbyte.
Traffic:– 170 kbyte/busy hour.– WAP, WWW, MMS, Mail.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0832
Example: “Peak Factor” (2)
Dimension core network:– A connection sees 5 links in tandem end-to-end.– 5% additional RTT acceptable (15 ms means 3 ms per link).– Different links have different load.
One peak factor?– Twice the average (peak factor 2, load 50%).– Is this too much (over-dimensioning)?– Or do we need more (e, π, ...)?
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0833
Example: “Peak Factor” (3)
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Sharing users
Peak
fact
or
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0834
Conclusions (5)
IP (TCP) fractal properties often overrated.– Relationship to variation conceptually the same.
This does not mean that dimensioning is simple:– Traffic and network are mutually dependent.– Traffic exhibits large variations over time.– User perceived performance different from directly
measurable.– A magnitude of parameters means unclear bottlenecks.– High burstiness may still enforce low utilisation.
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0835
Main Message
Traffic theory:– QoS is (partly) about congestion (loss and delay).– Congestion is partly caused by temporary overload
(variations).– Temporary overloads can be handled by statistics (traffic
model).– QoS can be controlled by statistics (queuing theory).
Typical issues:– Is an operator serious about quality of service? Goals!– What is the fair price to carry additional traffic? Depends!– How should a network be engineered? Methods!– Can I trust “over-provisioning”! No!
© Ericsson AB 2005 ÄS/EAB/UKT/T Åke Arvidsson Quality of Service in Telecommunícation Networks 2005-11-0836