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Traffic Management Solutions for User-Plane Congestion in Mobile
Networks
Andreas Maeder, Stefan SchmidNEC Laboratories Europe
Sept. 28th, 2012
Outline
▐ Background and motivation
▐ Congestion and congestion mitigation components
▐ A possible architecture for congestion mitigation in LTE EPS
▐ Standards activities
▐ Conclusions and outlook
2
The Mobile Data Tsunami is Coming...
3
On the move...
Mobile data traffic, measuredin exabytes per month, willkeep growing.
...with moving pictures
Video and web are the maindrivers of the mobile data explosion.
videow
eb
...what is the answer?
4
▐ More Spectrum? Spectrum is scarce and expensive
▐ More equipment? Small cells alone will not be sufficient
▐ Higher tariffs? Customers expect good connections for reasonable prices
Congestion is inevitable!
Smart traffic & congestion management technologies instead of simply throwing capacity at the problem
Congestion Scenarios▐ Traffic load increases during peak times at “hot-spot” areas,
leading to user plane congestion
▐ This scenario occurs especially at places where many users wait/stay while using their mobile
▐ It is not cost-effective for operators to dimension such “hot-spot” areas for the “worst case” peak, as this would imply very high investments given the rapid increase of mobile data traffic.
5 © NEC Corporation
What is "Congestion"?
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New metrics for end-user congestion based on QoE metrics are required.
Network view
Resource congestion• Full buffers• Fully occupied
radio resources• Packet drops/ECN
markings
User view
ApplicationQoE
Duration...
End-user congestion• Bad user experience• Dissatisfied users• Customer frustration
With TCP, resource congestion is "normal"
For the end user, the experience is important
Codec
adaptation
▐ Adapt data rate to device capabilities
▐ Downscale data rate if necessary
Solution Components
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Congestion detection & indication
Application
Awareness
▐ Timely reaction▐ Lightweight signaling▐ Flexible and future proof
▐ Provide and maintain expected user QoE
▐ Efficient support of different traffic characteristics (long vs. short flows)
TrafficManagement
▐ Prioritization and bandwidth shaping
▐ Operator policy control for OTT traffic
Functional pieces of user plane congestion management...
...but how to build?
▐ QoS is tied to dedicated bearer concept: one bearer for each flow? high signaling load, high latencies for setup and modification
▐ No mechanisms for congestion detection, signaling and control▐ Only coarse-grained QoS for long-lived flows
does not scale with application diversification▐ Nearly all traffic is mapped to one single QoS class (best effort)
All traffic is treated "fairly" – but customer satisfaction depends on application!
Doesn't LTE support QoS already?
8
The QoS architecture of the LTE Evolved Packet System is not designed to handle Internet traffic in congested scenarios.
Application-aware traffic management
RANCore network
Application User satistfaction
Default EPS bearers for all Internet traffic
No traffic differentiation
Today's networks
IP aggregate
RANCore network
Packet marking in default EPS bearers
Traffic differentiation in core NW and eNodeB
Scenario with application-aware traffic management
IP aggregate
Solution Components in EPS
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UE
S-GW P-GW
Internet
UE
PCRFDifferentiated traffic
handling on default Bearer(without additional out-of-
band signaling)
Congestion indication (towards core NW)
Intelligent traffic handling and packet
marking
AF
1. Congestion detection and indication in Radio Access, Backhaul or Core Network entities
2. Intelligent traffic handling mechanisms to handle user plane traffic, based on Subscriberprofile, Application type and Content type per-user and/or per-application traffic shaping application-aware QoE scheduling codec adaptation, etc.
3. Packet marking in the P-GW based on application/service types for lightweight traffic differentiation
4. Policy control for operators to flexibly configure the traffic handling in the network
eNB
default EPS bearer
Cloud Services
Policy control for traffic engineeringDownlink example:
Congestion detectionscheduling based on traffic differentiation
P-GW PCC
eNB
EPC
RAN
UE
S-GW
Hierarchical Congestion Control in EPS
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Congestion detection based on ECN (in EPC and transport
network nodes)
Congestion Indication based on GTP/PMIP-level ECN-ECHO
Congestion detection in RAN
Congestionindication
Service/app.marking
EPC
RAN
Coarse-grained traffic shaping based on simple congestion
indications and traffic engineering policies
Fine-grained application-aware scheduling based on
application/service markers and operator policies
Policy control for traffic eng.
Internet / ServiceNetworks
Application/service detection and marking, + Coarse-grained traffic shap.
+ Fine-grained app. aware scheduling
Congestion detection and indication
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Intermediate nodesSender
Control plane
User planeCongestion
GGSN / P‐GW / TDF
PCRF
Mobile NW
Base station
Receiver(UE)
ECN echo
ECN
2. Congestion indication3. Traffic engineering policy
1. Congestion detection
▐ Solutions approach based on ECN: 1. congestion detection on the data path2. congestion indication to PCRF in the GTP tunnel3. selection of traffic engineering policies and provisioning, and4. enforcement of traffic engineering policies
4. Traffic Engineering –enforcement
Application-Aware Traffic Shaping in Core Network
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User/Application
Aware Scheduler
ADC(Application Detection
and Marking)
Underlying Mobile Network Infrastructure (EPS)
Congestion Indication
(ECN ECHO)
PCRF(selects traffic engineering policies based on network
status and subscriber)
Congestion Indication +
Traffic Engineering Policy Provisioning
Application related QoE reports
U-Plane
C-Plane
PDN GW
Application-aware scheduling in eNodeB▐ Fine-grained app. aware scheduling in
eNodeB Reacts on air interface capacity
fluctuations and short-term traffic peaks Handling of delay-sensitive applications
(e.g. thin clients)
▐ Use service/app. information for: App.-aware traffic differentiation QoE scheduling for important applications
(e.g. progressive video, gaming, ThinClients, Cloud applications)
Congestion detection based on app. type
▐ Congestion indication towards EPC Lightweight signaling with ECN Consider application type
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id. flow
residual aggregate
flow identification/congestion detection based on service/app. Markers/QoE
EPS bearer 1 EPS bearer 2
EPS bearer 3
App.-aware scheduler
identifiedflow
priority/QoE/MAC profile assignment
IP traffic aggregate
500
1000
1500
2000
50
100
150
200
1
2
3
4
5
RTT (ms)Avg. bandwidth (kbps)
Web
MO
S
QoE models
S1GTP-U
Service/app.markers
ECN
Congestion Management in 3GPP
▐ 3GPP Study on User Plane Congestion Management (UPCON) Study scenarios and use cases for user plane congestion Define requirements for adequate traffic handling solutions
▐ UPCON Objective: Improve resource efficiency in the network to increase the number of active users
while maintaining good user experience (QoE)▐ Supporting mobile operators for the study item:
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▐ Study Item is completed, outcome in TR 22.805▐ Work on specifications for UPCON will start very soon in 3GPP technical
specification group SA2
Conclusions
▐ User plane congestion is inevitable in future mobile networks The mobile data tsunami meets scare resource in terms of
spectrum, equipment and money
▐ The QoS architecture of the LTE Evolved Packet System is not designed to handle Internet traffic in congested scenarios.
▐ Congestion management solutions rely on smart mitigation mechanisms which need New metrics to characterize end-user congestion Lightweight signaling of congestion occurence and location Application- and QoE aware traffic management Control loop to react timely on congestion
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Before the capacity era: the traffic management era?
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