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Joint workshop COST2100-AROMA-NEWCOM, Brussels, December 13th, 2006
AROMA
AROMA
AROMA
Jordi Pérez-Romero
Universitat Politècnica de Catalunya (UPC)
Advanced Resource Management Solutions for Future All IP Heterogeneous Mobile Radio
Environments
Advanced Resource Management Solutions for Future All IP Heterogeneous Mobile Radio
Environments
2Joint workshop COST2100-AROMA-NEWCOM, Brussels, December 13th, 2006
AROMA
AROMA
- AROMA Consortium- AROMA Objectives- AROMA Reference Architectures- AROMA Scenarios- Common Radio Resource Management
- Architectures- RAT selection- Common Congestion Control
- Coordinated Radio and Transport Resource Management- Architectures- Functionalities- Coordinated Congestion Control
- Conclusions
OutlineOutline
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3Joint workshop COST2100-AROMA-NEWCOM, Brussels, December 13th, 2006
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Academia• Universitat Politècnica de Catalunya (UPC) – Spain• King’s College London (KCL) – U.K.• Instituto Tecnico Superior- Technical University of
Lisboa (IST-TUL) - Portugal
Mobile Operators• Portugal Telecom Inovação (PTIN) – Portugal • Telecom Italia (TI)- Italy• Telefónica I+D (TID)- Spain• Telia–Sonera (TEL) - Sweden
Mobile Operator driven STREP project
Project AROMA ConsortiumProject AROMA Consortium
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The AROMA project aims to devise and assess a set of specific strategies and algorithms for both the access and the core network parts that can guarantee the end-to-end QoS in the context of an all-IP heterogeneous radio access network
Project AROMA Main ObjectivesProject AROMA Main Objectives
AROMA addresses in an integral way the end-to-end QoS provision in Mobile networks. In particular, AROMA focuses in both a Heterogeneous Access Networks and an IP-based core and access transport network.
AROMA contributes to the development of an efficient wireless accessassuming IP based services.
The results coming from the AROMA project will provide a manufacturer-independent analysis of the end-to-end QoS strategies, which allow the mobile operators to evaluate and compare solutions coming from the market with an available reference of the system performance.
AROMA is the natural continuation of two legacy project ARROWS and EVEREST
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5Joint workshop COST2100-AROMA-NEWCOM, Brussels, December 13th, 2006
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Techniques:
- RRM (Radio Resource Management)- CRRM (Common Radio Resource Management)- CARM (Common Access Resource Management)- Automatic Tuning
Framework:
- Current RATs (UMTS, GERAN, WLAN…)- Current spectrum allocation- Current regulatory framework
Scope and ApproachesScope and Approaches
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Space Resolution
Use
rC
ell
Reg
iona
l
Time Resolutionµs ms s mn 10s mn ½ day day month
Short term Middle term Long term
Short
space
Middle
space
Large
space
Automatic tuning
RRMCRRMCARM
Scope and ApproachesScope and Approaches
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7Joint workshop COST2100-AROMA-NEWCOM, Brussels, December 13th, 2006
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AROMA reference architecture – Medium term scenario
RNC SGSNBSCMSC ServerGANC
PSTN/ISDN
CS-MGW GGSN
IMS ServicesExternal PDN
WLAN AP
Node-B BTS
IP-based transport backhaul IP-based transport core network
3GPP R6 network architectureMulti-mode terminals
Rad
io N
etw
ork
Laye
r (R
NL)
Tran
spor
t Net
wor
k La
yer (
TNL)
Radio Access Network (IP-RAN) UMTS-based Core Network
Medium term scenario assumptions:- Backhaul already migrated to IP transport- Iub interface fully supported over IP transport
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AROMA reference architecture – Medium term key drivers
RNC SGSNBSCMSC ServerGANC
PSTN/ISDN
CS-MGW GGSN
IMS ServicesExternal PDN
WLAN APNode-B BTS
IP backhaul IP transport network
radi
o
IP transportIP transport IP transport
Access network e2e QoS
Key Drivers CRRMRadio and IP transport coordination
(GERAN and WLAN may share backhaul resources or not)
RRM RRM RRM
CRRM
RRM
Over-provisioning in the backhaul may not be economically feasible
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9Joint workshop COST2100-AROMA-NEWCOM, Brussels, December 13th, 2006
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AROMA reference architecture – Long term scenario
aGW
PSTN/ISDN
MGW
IMS ServicesExternal PDN
eNB
IP backhaul IP transport network
MMEUPE
RRCBorder GW
Inter ASanchor
Aligned to 3GPP SAE/LTE
Long term scenario assumptions:- Aligned to TR 25.912- Iub interface no longer needed- High capillarity needs efficient resource management
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AROMA reference architecture – Long term key drivers
PSTN/ISDN
MGW
IMS ServicesExternal PDN
eNB
IP backhaul IP transport network
RRCBorder GW
radio
IP nativeIP transport/native?
Access network e2e QoS
RRM
Key DriversMulti-cell RRMIETF IP solutions for mobility and QoSRadio and IP transport coordination
aGW
MMEUPE
Inter ASanchor
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11Joint workshop COST2100-AROMA-NEWCOM, Brussels, December 13th, 2006
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• Six selected target scenarios• Three theoretical: Hot Spot within urban area, Hot spot along main road
and Urban residential area
• Three realistic: urban/suburban, dense urban area & multifloor
• Scenario description items• Network architecture and entities • Services mix and traffic load• Environment; suburban, urban and indoor• Radio access technologies and capabilities• Characterisation of the Transport Network
AROMA ScenariosAROMA Scenarios
GSM / GPRSUMTS UMTS UMTS
WLAN
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VoiceVideotelephonyVideo streamingWeb browsingEmailMMSFTP
Service UL kbytes/user/BH DL kbytes/user/BH Voice 75 75 Video Streaming 5 113 Video Telephony 53 53 Web Browsing 60 312 Email 88 328
The scenario vision encompasses the heterogeneous network supporting users with multimode mobile terminals with a target year around 2010.
AROMA ScenariosAROMA Scenarios
60%
4%
10%
10%
6%
7%3%
50%
4%10%
12%
11%
3%
10%Consumer users Business users
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13Joint workshop COST2100-AROMA-NEWCOM, Brussels, December 13th, 2006
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RRU (Radio Resource Unit): Set of basic physical transmission parameters necessary to support a signal waveform transporting end user information corresponding to a reference service.
RRU in FDMA: a certain bandwidth within a given carrier frequency RRU in TDMA: a pair of a carrier frequency and a time slotRRU in CDMA: a carrier frequency, a code sequence and a power level
RADIONETWORKPLANNING
RADIONETWORK
DEPLOYMENT
RADIONETWORK
OPERATION
RRU provision along timeand space
RRU allocation
RRM / CRRM
Radio Resource Management (RRM)Radio Resource Management (RRM)
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AROMA – RRM/CRRM ObjectivesAROMA – RRM/CRRM Objectives
• To develop advanced RRM strategies and algorithms in the context of 3G and Beyond systems, ensuring the QoS requirements of the proposed services, providing the planned coverage and increasing capacity. In particular, algorithms will target:
Individual RRM for different RANs
CRRM for heterogeneous RANs
• To assess and evaluate the proposed algorithms in a number of relevant scenarios, technological functionalities, network layout structures, services mix, etc. with the idea to cover medium- and long-term foreseen evolutions
f
GERAN ttt
c
UTRAN WLAN
RRM-GERAN RRM-UTRAN RRM-WLAN
f
GERAN ttt
c
UTRAN WLAN
RRM-GERAN RRM-UTRAN RRM-WLAN
f
GERAN ttt
c
UTRAN WLAN
CRRM
f
GERAN ttt
c
UTRAN WLAN
CRRM
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AMOUNT OFCOMMON
RADIORESOURCES
GERAN RADIO RESOURCESUTRAN RADIO RESOURCESWLAN RADIO RESOURCES
Common Radio Resource ManagementCommon Radio Resource Management
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CRRM – Functional modelCRRM – Functional modelThe functional model assumed in 3GPP for CRRM operation:
The interactions between RRM and CRRM entities involve two types of functions:a) Information reporting function
- Dynamic (e.g. cell load, transmitted carrier power, interference measurements, etc.)- Static (e.g. cell relations in HCS layers, cell capabilities and configuration)
b) RRM decision support functionCRRM simply advises the RRM entity (i.e. RRM remains as the master of the
decisions) or CRRM is the master, so that its decisions are binding for the RRM entity.
CRRM entity
CRRM entity
RRM entity
RRM entity
RRM entity
RRM entity
- Information reporting
- Information reporting - RRM decision support
- Information reporting - RRM decision support
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RRM functionalities in a single-RAT context:• Admission control• Congestion control• Horizontal (intra-system) handover• Packet scheduling• Power control
When these functionalities are coordinated between different RATs in a heterogeneous scenario, they can be denoted as “common”
In an heterogeneous scenario a new functionality arises: RAT selection (bothinitial RAT selection and Vertical Handover)
CRRM – Functionalities & splitCRRM – Functionalities & split
There exists a range of possibilities for the set of functionalities that the CRRM entity may undertake
The CRRM entity may be implemented either into existing nodes (i.e. RNC, BSC and APC) or in a separate node
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CRRM - TopologiesCRRM - Topologies
RNC
RRM entity
UTRAN GERAN
RNC
RRM entity
BSC
RRM entity
BSC
RRM entity
CRRM server CRRM entity
Core Network
RNC
CRRM entity
RRM entity
BSC
CRRM entity
RRM entity
RNC
CRRM entity
RRM entity
RNC
RRM entity
BSC
RRM entity
UTRAN GERAN
Core Network
CRRM server
Integrated CRRM
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CRRM - WLANCRRM - WLANThe interworking with WLAN is devised from a different perspective because WLANs are being mainly deployed by independent operators, not belonging to 3GPP, and consequently they do not follow the same networking architectures of 3GPP systems like UMTS or GSM/EDGE.
RNC
UTRANGERAN
Core Network
BSC
SGSN
APC
WLAN
GGSN
Data Network (Internet)
data flow signalling
HSS
Gi
IuIu/Gb Iu
A tight coupling approach allows consideringthe WLAN as an additional access network
like GERAN or UTRAN.
In order to support RRM and CRRM the functionalities of the Access Point Controller (APC) should be equivalent to the RNC or the BSC for the UTRAN and GERAN.
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RAT selectionRAT selectionSome possible guiding principles for RAT selection are:
Service-based RAT selection. A service-based RAT selection policy is based on a direct mapping between services and a prioritised list of preferred RATs.
Load-balancing RAT selection. This policy will distribute the load among all resources as evenly as possible.
Interference-based RAT selection. This principle intends to anticipate the effects that the allocation of a certain connection request to a certain cell and RAT will cause in terms of interference. Then, different criteria could be used for the RAT selection so that the interference tends to be minimised.
TerminalcharacteristicsServices
& QoS
RATsavailable
RATssupported Cell load
conditions
UE interferenceconditions
Userprofile
Operatorpreferences
RAT & CellSelection
Objective: To devise a generic framework that takes the different principles into account together with different conditions (non-homogeneous system conditions along time and space, service dimension, user category dimension, terminal capabilities dimension, etc.)
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Example of RAT selection algorithmExample of RAT selection algorithm
VHO PROCEDURE
LUTRAN>Lth+∆ for Mup consecutive
samples
Y
N
User in UTRAN
Y
N
VHO to GERAN
Do NOTHING
Y
Y
VHO to UTRAN
N
Voice
Y
N
Y
N
Interactive
RAT SELECTION
Start of session
LUTRAN>LthY N
Capacity available in
UTRAN
N
Y Y
N N
N
YY
ACCEPT IN GERAN
ACCEPT IN UTRAN
Service
Voice
Interactive
BLOCK CALL
INITIAL RAT SELECTION
YN
Capacity available in
GERAN
Capacity available in
GERAN
Capacity available in
UTRAN Capacity
available in GERAN
Capacity available in
UTRAN
Service
LUTRAN<Lth-∆ for Mdown consecutive
samples
User in UTRAN
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Example of RAT selection algorithmExample of RAT selection algorithmThe algorithm combines:
• Service principle (preference of UTRAN for interactive traffic)• Interference principle (tends to avoid at the possible extent to assign high path
loss users to WCDMA RAT)• Load balancing principle (setting of the path loss threshold Lth as a certain
percentile of the statistical path loss distribution)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
90 95 100 105 110 115 120 125 130 135 140
L (dB)
CDF
PLth=125 dB(80-th perc)
PLth=120 dB(60-th perc)PLth=115 dB
(40-th perc)
Key single parameter: Lth
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Example of RAT selection algorithmExample of RAT selection algorithm
Throughput gain up to 25%are observed with theproposed algorithm
Optimisation throughsuitable Lth setting
With different dominant principles
Downlink throughputVoice-only scenario Lth=120 dB
1.5
2
2.5
3
3.5
4
4.5
5
400 500 600 700 800 900 1000 1100 1200
Voice UsersD
L Th
roug
hput
(Mb/
s)
CRRM Algorithm
Load Balancing
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0
5
10
15
20
25
30
35
100 75 50 25Mult i-mode T erminal Availability (%)
Thro
ughp
ut D
egra
datio
n (%
)
VU=600;WU=600
VU=400;WU=400
VU=200;WU=200
UL Throughput degradation
• Increases degradation with
decrease of multi-mode availability
• Impact on the interactive users
exhibiting higher delays
Proposed solution: Average Packet Delay improvement with dedicated slots(i.e. some reserved resources for single-mode terminals)
Study provides insight into evolutionary paths (e.g. suitability to subsidizemulti-mode terminals to exploit CRRM gain depending on load levels)
Impact of Multi-Mode TerminalsImpact of Multi-Mode Terminals
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• Radio-Access Congestion Overload– UTRAN: ⇈ interference.– GERAN: ⇈ (data) timeslot reuse.
• Classical approach:– Congestion Detection (CD) ✔
• CD metric definitions for each RAT.• CR triggering mechanisms.
– Congestion Resolution (CR) ✔• CR algorithms:
– Resource Creation scheme: » Attempt VHO from congested BS/RAT to non-congested BS/RAT (VHO-CR).
– Demand Reduction schemes:» Bit-Rate Reduction (BRR-CR)» User Dropping (DROP-CR)
• User prioritization on which to perform algorithms. – Congestion Recovery (CRV)
Common Congestion ControlCommon Congestion Control
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• Congestion Detection (CD):– Metric UTRAN: Load Factor:
– Metric GERAN: Timeslot Reuse Factor (RF)
– Threshold-based triggering mechanism:
0 if 01 if 0
if
d
d d
dd d
d
NN C
RFC N CN
= < ≤= >
1 NUL
total
PI
η = −max
totalDL
PP
η =
4 0.410d
d
CRF N= = =
{ }, thUL DLη η> { }, thUL DLRF RF<
Common Congestion ControlCommon Congestion Control
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Common Congestion ControlCommon Congestion Control
• Congestion is detected in UTRAN and we try to solve it by performing VHO over GERAN users towards UTRAN.
• Expected negative impact on GERAN due to RF reduction.
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• Given a congestion situation in both RATs, using only VHO will not solve congestion. Idea: reduce load in UTRAN by reducing bit-rate demands so that:
1. Congestion in UTRAN is mitigated.2. GERAN users can be directed to UTRAN by means of VHO.
Common Congestion ControlCommon Congestion Control
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RRM RAT n
MC
RPSLC
AC CC
BS
Radio Controller(RNC, BSC, GANC)
Base Station(NodeB, BTS, AP)
SGSN GGSNMobile Terminal
Radio Resources IP Transport Resources IP Transport Resources IP Transport Resources
TRM
R5/R6
CC
PSRC
BS
AC
RRM RAT2
MC
RPSLC
AC CC
BS
RRM RAT1
MC
RPSLC
AC CC
BS
CRRM RS
RRM and TRM QoS functionsRRM and TRM QoS functions
CRRM:- RAT Selection (RS)
RRM and TRM:- Admission Control (AC)- Congestion Control (CC)- Bearer Selection (BS)
RRM:- Mobility Control (MC)- Radio Link Control (LC)- Radio Packet Scheduling (RPS)
TRM:- TNL Route Control (RC)- TNL Packet Scheduling (PS)
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CARM QoS functionsCARM QoS functions
RRM RAT n
RPSLC
RRM RAT 2
RPSLC
Radio Controller(RNC, BSC, GANC)
Base Station(NodeB, BTS, AP) SGSN GGSN
Mobile Terminal
Radio Resources IP Transport Resources IP Transport Resources IP Transport Resources
TRM
PS
RRM RAT 1
RPSLC RCMC
CC
AC
BS
CRRM RS
Coordinated Access Resource Management
(CARM) functions
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BearerSelection
Radio PacketScheduling
Congestion Control
Link Control
RRM functions TRM functions
TNL PacketScheduling
RouteControl
AdmissionControl
MobilityControl
CARM functions
RAT Selection
Proposed CARM QoS functionsProposed CARM QoS functions
• Goals:– Resource optimisation (RNL and TNL)– Business strategies (e.g. business users vs. consumer users)
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Transport Congestion ResolutionMechanisms based on RRM within the RNL:
•Bit rate reduction for non-guarateed PS services•Redistribute traffic via HO and network controlledcell reselection (intra/inter RAT)•Reduce soft HO connections•Flow control for High Speed channels•Increase admission blocking•Drop active sessions
Tranport Network CongestionResolution Mechanisms within the TNL itself:
•Packet Discarding policies (blind/selective)•Path re-calculation (routing control)
How TNL congestioncan be preventedand/orsolved?
Where TNL congestion oroverloadsituations can be detected?
Transport Congestion/Overload DetectionMechanisms in the radio layer
Transport Congestion/Overload DetectionMechanisms in the transport layer
Coordinated Congestion Control approachpure RNLapproach
pure TNL approach
Transport Congestion ResolutionMechanisms based on RRM within the RNL:
•Bit rate reduction for non-guarateed PS services•Redistribute traffic via HO and network controlledcell reselection (intra/inter RAT)•Reduce soft HO connections•Flow control for High Speed channels•Increase admission blocking•Drop active sessions
Tranport Network CongestionResolution Mechanisms within the TNL itself:
•Packet Discarding policies (blind/selective)•Path re-calculation (routing control)
How TNL congestioncan be preventedand/orsolved?
Where TNL congestion oroverloadsituations can be detected?
Transport Congestion/Overload DetectionMechanisms in the radio layer
Transport Congestion/Overload DetectionMechanisms in the transport layer
Coordinated Congestion Control approachpure RNLapproach
pure TNL approach
Cover those situations where: (1) pure-TNL mechanisms do not suffice to alleviate a given congestion situation and consequently the RNL
should be involved in congestion handling, and (2) useful metrics to characterise overload/congestion situations are computed in the TNL itself and notified to the
RNL, instead of letting the RNL layer to detect congestion by itself, so that the reaction of the RNL can be better directed to the location and adjusted to the severity of the overload situation.
Example: Coordinated Congestion ControlExample: Coordinated Congestion Control
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IP Transport Network
RNCn
RNCm
NodeBi
NodeBj
NodeBk
TNL Monitoring
Measurements
Congestion metrics
CoordinatedCongestionResolutionmechanims
li
lj
A bottleneck link in the transportnetwork is considered
Example: Coordinated Congestion ControlExample: Coordinated Congestion Control
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a) Mean LU (%)
50
55
60
65
70
75
80
85
90
95
0.4 0.5 0.6 0.7
Normalised Goodput
DCH64DCH128DCH256
b) Prob (LU>0.95) (%)
0
10
20
30
40
50
60
70
0.4 0.5 0.6 0.7Normalised Goodput
DCH64DCH128DCH256
c) FP PDU Loss Ratio (%)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0.4 0.5 0.6 0.7Normalised Goodput
DCH64DCH128DCH256
Potential Congestion Control Gain
Effect of the DCH bit rate selection in the LU indicator and potential coordinated congestion control gain.
Example: Coordinated Congestion ControlExample: Coordinated Congestion Control
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a) Mean LU (%)
50
5560
6570
75
8085
9095
100
0.4 0.5 0.6 0.7Normalised Goodput
Rep_Range=10dBRep_Range=0dB
b) FP PDU Loss Ratio (%)
00.5
11.5
22.5
33.5
4
4.55
0.4 0.45 0.5 0.55 0.6Normalised Goodput
Rep_Range=10dBRep_Range=0dB
Potential Congestion Control Gain
Effect of the reporting range value in the LU indicator and potential coordinated congestion control gain.
Example: Coordinated Congestion ControlExample: Coordinated Congestion Control
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-The objectives and main research lines of the AROMA project have been presented
-AROMA focuses on the end-to-end QoS in mobile heterogeneousall-IP networks, integrating solutions for both the radio and thetransport parts.
-For what the radio part concerns, the project focuses on CRRM strategies. Some examples of RAT selection strategies andcommon congestion control algorithms have been presented.
-Concerning the transport network part, a coordinatedradio+transport congestion control mechanism has beenpresented.
ConclusionsConclusions
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AROMA WEB site
http://www.aroma-ist.upc.edu
Thanks for your attention….
AROMA
AROMA