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CHAPTER 11:CHAPTER 11:IP QoS IP QoS
I. F. AkyildizI. F. Akyildiz
Broadband & Wireless Networking LaboratoryBroadband & Wireless Networking Laboratory
School of Electrical and Computer EngineeringSchool of Electrical and Computer Engineering
Georgia Institute of TechnologyGeorgia Institute of Technology
Tel: 404-894-5141; Fax: 404-894-7883 Tel: 404-894-5141; Fax: 404-894-7883
Email: [email protected]: [email protected]
Web: http://www.ece.gatech.edu/research/labs/bwnWeb: http://www.ece.gatech.edu/research/labs/bwn
2IFA’2005ECE6609
IP WORLDIP WORLD
Commonly agreed that IP should be Commonly agreed that IP should be the the future multi-service networking future multi-service networking technology…technology…
But this is not our “father’s” IPBut this is not our “father’s” IP TECHNOLOGY… Maybe we can call itTECHNOLOGY… Maybe we can call it “ “IP on STEROIDS” or “ATMized IP”IP on STEROIDS” or “ATMized IP”
3IFA’2005ECE6609
““FATHER’S” IPFATHER’S” IP
Based on DatagramBased on Datagram Data TrafficData Traffic “ “Best Effort” Traffic ParadigmBest Effort” Traffic Paradigm QoS is NON-EXISTENTQoS is NON-EXISTENT
4IFA’2005ECE6609
““FATHER’s” IPFATHER’s” IP
Question:Question:
How can F-IP take care of new How can F-IP take care of new multi-media applications that multi-media applications that demand QoS?demand QoS?
5IFA’2005ECE6609
Key ApplicationsKey Applications
Web + MailWeb + Mail Large File TransfersLarge File Transfers Interactive AccessInteractive Access Streaming Audio/VideoStreaming Audio/Video GamesGames Many More…Many More…
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Key QuestionKey Question
Shall we MANAGE BANDWIDTH or Shall we MANAGE BANDWIDTH or NOTNOT
for QoS? for QoS?
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Just Keep Adding Just Keep Adding Bandwidth?Bandwidth? ( (No BW Management)No BW Management)
Bandwidth management is not Bandwidth management is not needed unless (until) needed unless (until) congestion occurs.congestion occurs.– Looks like adding bandwidth Looks like adding bandwidth gives premium service with gives premium service with minimal complexity and minimal complexity and management burden.management burden.
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VISION OF SOME IP FOLKSVISION OF SOME IP FOLKS
NO BW MANAGEMENT, i.e., NO BW MANAGEMENT, i.e., OVER-PROVISION/OVER-OVER-PROVISION/OVER-DIMENSION!!!DIMENSION!!!
i.e., whenever and how much BW is neededi.e., whenever and how much BW is needed
just keep adding/assigning new BW. just keep adding/assigning new BW.
9IFA’2005ECE6609
NO BW MANAGEMENTNO BW MANAGEMENT
Maybe this was viable in the Maybe this was viable in the beginning!!!beginning!!!
* * The Internet boom was peaking, with many Service Providers and Enterprises were flushed with FUNDS.. * The additional bandwidth was perceived as cheaper than QoS deployment.
However, However, Not economically efficient!!Not economically efficient!!
10IFA’2005ECE6609
Managed Bandwidth Managed Bandwidth AdvantagesAdvantages
Constant resources and No BW management Constant resources and No BW management No QoS can be guaranteed !!!No QoS can be guaranteed !!!
WAN bandwidth is very expensive compared to WAN bandwidth is very expensive compared to the LAN (and WAN service pricing is not the LAN (and WAN service pricing is not necessarily driven by open market factors).necessarily driven by open market factors).– IT managers and service providers need to IT managers and service providers need to
squeeze as much functionality out of WAN squeeze as much functionality out of WAN BW as possible.BW as possible.
11IFA’2005ECE6609
Managed Bandwidth Managed Bandwidth AdvantagesAdvantages
Traffic growth models fall apart Traffic growth models fall apart when new “killer” applications when new “killer” applications appearappear– Mission critical applications must Mission critical applications must
get required network resources get required network resources consistently, even when consistently, even when competing with such applications. competing with such applications.
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ResultResult
FOR THE SAKE of QoS in IPFOR THE SAKE of QoS in IP
BANDWIDTH MUST BE MANAGED!!! BANDWIDTH MUST BE MANAGED!!!
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QoS EveryWhereQoS EveryWhere
QoS in Wireless LANs QoS in Sensor Networks QoS in Wireless Ad-Hoc Networks QoS in P2P Networks QoS in Access Networks QoS in Optical Networks QoS in VoIP QoS in Wireless Mesh Networks QoS in 2.5 G (GPRS) Systems QoS in 3G (UMTS/IMT2000) Systems
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Plethora of QoS Plethora of QoS ConferencesConferences
IWQoS (94: Aachen, 95: Brisbane, 96: Paris, 97: NY, 98: Napa/CA, 99: London, 00: Pittsburgh, 01: Karlsruhe, 02: Miami, 03: Montreal, 04: Monterrey)
QofIS (01: Coimbra; 02 Berlin; 03: Stockholm; 04: Barcelona)
QoSIP (01: Roma; 03: Milano; 05: Catania)
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Providing QoS in IP Providing QoS in IP NetworksNetworks
Back to USSR !! (ATM) Back to USSR !! (ATM)
““IP on Steroids” or “ATMized IP”IP on Steroids” or “ATMized IP”
The ATM Framework for QoS The ATM Framework for QoS under new nomen-clatura is under new nomen-clatura is
being being RECREATEDRECREATED!!! !!!
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Examples for Examples for RECREATIONRECREATION????Service Level ParametersService Level Parameters
Traffic Parameters:Traffic Parameters: (Peak Rate, Peak Bucket Size, Sustainable Rate,(Peak Rate, Peak Bucket Size, Sustainable Rate,
Sustainable Bucket Size, Max Allowed Packet Size)Sustainable Bucket Size, Max Allowed Packet Size)
QoS Classes:QoS Classes: (Guaranteed Service, CL Service, BE Service)(Guaranteed Service, CL Service, BE Service)
QoS Requirements: QoS Requirements: (Loss Ratio, Transfer Delay, Delay Variation)(Loss Ratio, Transfer Delay, Delay Variation)
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IP QoS OverviewIP QoS Overview
Best Effort Best Effort (No State) (Original IP (No State) (Original IP Service)Service) IntServ/RSVP IntServ/RSVP (Per Flow State) (Per Flow State) First efforts at IP QoSFirst efforts at IP QoS DiffServ DiffServ (Aggregated State)(Aggregated State) (Seeking Simplicity and Scalability)(Seeking Simplicity and Scalability) IntServ + DiffServ + Traffic EngineeringIntServ + DiffServ + Traffic Engineering (BW Optimization; E2E SLAs)(BW Optimization; E2E SLAs) Static DiffServ + MPLSStatic DiffServ + MPLS
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IntServ + DiffServIntServ + DiffServ
Complimentary:Complimentary:
IntServ provides a guaranteed traffic deliveryIntServ provides a guaranteed traffic delivery DiffServ enables better QoS scalabilityDiffServ enables better QoS scalability
Together, they form a robust QoS deployment.Together, they form a robust QoS deployment.
Diff Serv functionalities are Diff Serv functionalities are Class Based Class Based WeightedWeighted Fair QueueingFair Queueing (CBWFQ) and the (CBWFQ) and the Committed Access Rate (CAR)Committed Access Rate (CAR)
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IntServ + DiffServIntServ + DiffServ+ Traffic Engineering+ Traffic Engineering
End-to-end IntServ does not scale well because it End-to-end IntServ does not scale well because it requires per-flow state on every routerrequires per-flow state on every router
DiffServ does not provide enough granularity for DiffServ does not provide enough granularity for classifying applicationsclassifying applications
Solution:Solution:– Use DiffServ at the network coreUse DiffServ at the network core– Use IntServ at the edgesUse IntServ at the edges– Apply traffic engineering principles and Apply traffic engineering principles and
admission controls to ensure end-to-end admission controls to ensure end-to-end quality.quality.
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Static DiffServ + MPLSStatic DiffServ + MPLS
Flows are grouped into Class-Types and fast forwarding using label switching
– DiffServ-aware Traffic Engineering Traffic belonging to the same class is Traffic belonging to the same class is
aggregated and routed on a dedicatedaggregated and routed on a dedicated
virtual tunnel (LSP)virtual tunnel (LSP)
Difficult to dimension the LSPs efficientlyDifficult to dimension the LSPs efficiently
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Our Approach:Our Approach:Measurement based Measurement based Adaptive DiffServ MPLS Adaptive DiffServ MPLS NetworkingNetworkingNSF, NASA, Swayles (2000-2004)NSF, NASA, Swayles (2000-2004)
Capacity allocation is adapted using measurements, not based on traffic descriptors.
Statistical Multiplexing is achieved among flows belonging to the same class.
Efficient use of resources and provisioning of QoS monitored on the need
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Traffic Engineering Automated Traffic Engineering Automated Manager (TEAM) Manager (TEAM) C. Scoglio, T. Anjali, J. Cavalcante, I. F. Akyildiz, G. Uhl, C. Scoglio, T. Anjali, J. Cavalcante, I. F. Akyildiz, G. Uhl, ““TEAM: A Traffic Engineering Automated Manager for TEAM: A Traffic Engineering Automated Manager for DiffServ based MPLS Networks“, DiffServ based MPLS Networks“, IEEE Communications, Oct’04. IEEE Communications, Oct’04.
Rou
teR
esou
rce
LSP Routing
Traffic Routing
LSP Preemption
LSP Setup
Management Plane
DiffServ/MPLS
Domain
SimulationTool (ST)
TrafficEngineeringTool (TET)
Measurement/
Performance Evaluation
Tool (MPET)
To neighboring TEAM
Network Dimensioning and Topology Design
LSP Dimensioning
23IFA’2005ECE6609
Traffic Engineering Traffic Engineering Automated Manager (TEAM)Automated Manager (TEAM)
External LightstreamATM 155 Mbps
Gigabit Ethernet
7204 VXR (rtr1)
7204 VXR (rtr2)
ATM 622 Mbps
7505(rtr3) Catalyst
6506
Catalyst 4000
Lightstream 1010
Fast
Eth
ern
et
Ro
ute
LSP Routing
Re
sou
rce
LSP Preemption
LSP Setup/DimensioningLSP Capacity
Allocation
Management Plane
SimulationTool (ST)
TrafficEngineeringTool (TET)
Measurement/Performance
EvaluationTool (MPET)
TEAM
MPLS NetworkDimensioning
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TESTBED TESTBED NETWORK TOPOLOGYNETWORK TOPOLOGY
Abilene
NASA Goddard
BWN-Lab
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MPLS Network MPLS Network ManagementManagement
Existing MPLS Network Management Existing MPLS Network Management Tools:Tools:
– RATES (Bell Labs, 2000):RATES (Bell Labs, 2000):✓ Sets up bandwidth guaranteed LSPsSets up bandwidth guaranteed LSPs✘ Does not support DiffServDoes not support DiffServ✘ No performance measurement and analysisNo performance measurement and analysis
– DISCMAN (EURESCOM, 2000):DISCMAN (EURESCOM, 2000): Provides test and analysis results of DiffServ and Provides test and analysis results of DiffServ and
MPLS-based DiffServMPLS-based DiffServ✘ Does not provide its own management system Does not provide its own management system
functionalityfunctionality
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MPLS Network ManagementMPLS Network Management
Other existing MPLS Network Management Tools:Other existing MPLS Network Management Tools:
– MATE (Bell Labs, Univ. Michigan, Caltech, Fujitsu, 2001):MATE (Bell Labs, Univ. Michigan, Caltech, Fujitsu, 2001): The goal is to distribute the traffic across several LSPs The goal is to distribute the traffic across several LSPs
established between a given ingress and egress node pairestablished between a given ingress and egress node pair✘ Not for traffic that requires bandwidth reservationNot for traffic that requires bandwidth reservation
– TEQUILA (European Union Project, 2002):TEQUILA (European Union Project, 2002): Global and integrated approach to network design and Global and integrated approach to network design and
managementmanagement✘ No network management methods developed and implementedNo network management methods developed and implemented✘ No evaluation of performancesNo evaluation of performances
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Traffic Engineering ToolTraffic Engineering Tool– LSP SetupLSP Setup – LSP DimensioningLSP Dimensioning– LSP PreemptionLSP Preemption– LSP RoutingLSP Routing
Measurement ToolMeasurement Tool– Available Bandwidth MeasurementAvailable Bandwidth Measurement
TEAM ComponentsTEAM Components
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LSP Setup/DimensioningLSP Setup/Dimensioning
LSP Setup Problem: LSP Setup Problem: A new LSP setup request A new LSP setup request arrivesarrives– When to setup a new direct LSP?When to setup a new direct LSP?– When to re-dimension an existing When to re-dimension an existing
LSP?LSP?– When to route the traffic on the When to route the traffic on the
hop-by-hop IP route?hop-by-hop IP route?
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LSP Setup/DimensioningLSP Setup/Dimensioning
Related work: Related work: Very little Very little attention was given to this attention was given to this problemproblem– S. Uhlig and O. Bonaventure, “On the S. Uhlig and O. Bonaventure, “On the
cost of using MPLS for interdomain cost of using MPLS for interdomain traffic,” traffic,” in Proc. of QoFIS’00.in Proc. of QoFIS’00.An LSP is established whenever the An LSP is established whenever the
number of bytes forwarded within one number of bytes forwarded within one minute exceeds a thresholdminute exceeds a threshold
Very high signaling costs and high Very high signaling costs and high control efforts for variable and bursty control efforts for variable and bursty traffictraffic
30IFA’2005ECE6609
LSP Setup/Dimensioning LSP Setup/Dimensioning C. Scoglio, T. Anjali, J. de Oliveira, I. Akyildiz, and G. Uhl, C. Scoglio, T. Anjali, J. de Oliveira, I. Akyildiz, and G. Uhl, “A New Threshold-Based Policy for Label Switched Path Setup “A New Threshold-Based Policy for Label Switched Path Setup in MPLS Networks,”in MPLS Networks,” Proc. of ITC 2001, Salvador, Brazil, Dec. Proc. of ITC 2001, Salvador, Brazil, Dec. 2001.2001.Also in Computer Networks Journal (Elsevier), 2002.Also in Computer Networks Journal (Elsevier), 2002.
Find an Find an Adaptive Traffic DrivenAdaptive Traffic Driven PolicyPolicy for Dynamic for Dynamic Setup, Teardown and Dimensioning of LSPsSetup, Teardown and Dimensioning of LSPs
Based on Markov Decision Process theoryBased on Markov Decision Process theory Objective Function: Objective Function:
– Minimize the expected infinite-horizon discounted Minimize the expected infinite-horizon discounted total costtotal cost
To determine the optimal policy, To determine the optimal policy, the the transition probabilities and the optimality transition probabilities and the optimality equationsequations
The optimality equations are solved using the The optimality equations are solved using the Value Iteration Algorithm.Value Iteration Algorithm.
31IFA’2005ECE6609
LSP Setup/DimensioningLSP Setup/Dimensioning
Novelty in our approach:Novelty in our approach: –Online threshold-based Online threshold-based traffic driven policy which traffic driven policy which takes into account takes into account bandwidth, switching, and bandwidth, switching, and signaling costssignaling costs
32IFA’2005ECE6609
Traffic Engineering ToolTraffic Engineering Tool– LSP Setup LSP Setup – LSP DimensioningLSP Dimensioning– LSP PreemptionLSP Preemption– LSP RoutingLSP Routing
Measurement ToolMeasurement Tool– Available Bandwidth MeasurementAvailable Bandwidth Measurement
TEAM ComponentsTEAM Components
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LSP PreemptionLSP Preemption
Problem:Problem:– An LSP with higher priority can preempt an An LSP with higher priority can preempt an LSP with lower priority if there is a competition LSP with lower priority if there is a competition for resources.for resources.– The preempted LSP may be rerouted. The preempted LSP may be rerouted. Which LSP(s) to preempt?Which LSP(s) to preempt?
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LSP PreemptionLSP Preemption
Related Work:Related Work:– M. Peyravian and A. Kshemkalyani, “Decentralized Network M. Peyravian and A. Kshemkalyani, “Decentralized Network Connection Preemption Algorithms,” Connection Preemption Algorithms,” Computer NetworksComputer Networks, June , June
19981998Optimizes preemption criteria in a given order of importanceOptimizes preemption criteria in a given order of importance
– F. Le Faucheur et al., “Requirements for Support of DiffServ-F. Le Faucheur et al., “Requirements for Support of DiffServ-Aware MPLS Traffic Engineering,” Aware MPLS Traffic Engineering,” IETF Internet DraftIETF Internet Draft, March , March 20032003The need for preemption is stressed but no policy is definedThe need for preemption is stressed but no policy is defined
– BWN-Lab Testbed preemption experiments:BWN-Lab Testbed preemption experiments: Commercial policy purely based on priority and tunnel ageCommercial policy purely based on priority and tunnel age
35IFA’2005ECE6609
An LSP with higher priority can An LSP with higher priority can preemptpreempt an LSP with lower priority an LSP with lower priority if there is a competition for if there is a competition for resourcesresources– Versatile preemption policy Versatile preemption policy
complemented with an adaptive complemented with an adaptive scheme which can reduce the need scheme which can reduce the need for LSP reroutingfor LSP rerouting
LSP PreemptionLSP PreemptionJ. de Oliveira, C. Scoglio, I. Akyildiz, and G. Uhl,J. de Oliveira, C. Scoglio, I. Akyildiz, and G. Uhl, ““A New Preemption Policy for DiffServ-Aware Traffic A New Preemption Policy for DiffServ-Aware Traffic Engineering to Minimize Rerouting,”Engineering to Minimize Rerouting,” Proc. of IEEE INFOCOM Proc. of IEEE INFOCOM 2002.2002.Also in IEEE/ACM Transactions on Networking, August Also in IEEE/ACM Transactions on Networking, August 20042004
36IFA’2005ECE6609
LSP PreemptionLSP Preemption
Non-real time applications may afford Non-real time applications may afford to have their transmission rate to have their transmission rate reducedreduced
By reducing the rate in a fair fashion:By reducing the rate in a fair fashion:– These LSPs would not be torn down,These LSPs would not be torn down,– There would be no service disruption, There would be no service disruption,
extra setup and tear down signalingextra setup and tear down signaling– THERE WOULD BE NO REROUTING THERE WOULD BE NO REROUTING
DECISIONSDECISIONS
37IFA’2005ECE6609
LSP PreemptionLSP Preemption
Combines the three main preemption Combines the three main preemption criteria:criteria:– Priority of preempted LSPsPriority of preempted LSPs– Number of preempted LSPsNumber of preempted LSPs– Bandwidth of preempted LSPsBandwidth of preempted LSPs
Optimization formulation and Optimization formulation and heuristicheuristic
38IFA’2005ECE6609
Traffic Engineering ToolTraffic Engineering Tool– LSP Setup LSP Setup – LSP DimensioningLSP Dimensioning– LSP PreemptionLSP Preemption– LSP RoutingLSP Routing
Measurement ToolMeasurement Tool– Available Bandwidth MeasurementAvailable Bandwidth Measurement
TEAM ComponentsTEAM Components
39IFA’2005ECE6609
LSP Routing LSP Routing AlgorithmAlgorithm
LSP Routing Problem:LSP Routing Problem:–Setting up bandwidth Setting up bandwidth guaranteed LSPs, where LSP guaranteed LSPs, where LSP setup requests arrive setup requests arrive individually, and future individually, and future requests are not known a-requests are not known a-prioripriori
40IFA’2005ECE6609
LSP Routing LSP Routing AlgorithmAlgorithm
Related work:Related work:– K. Kar, M. Kodialam, and T. Lakshman, K. Kar, M. Kodialam, and T. Lakshman,
“Minimum Interference Routing of Bandwidth “Minimum Interference Routing of Bandwidth Guaranteed Tunnels with MPLS Traffic Guaranteed Tunnels with MPLS Traffic Engineering Application,”Engineering Application,” IEEE INFOCOM 2000 IEEE INFOCOM 2000 and IEEE JSAC,Dec.2000and IEEE JSAC,Dec.2000MIRA – Tries to minimize interference between MIRA – Tries to minimize interference between
different routes in a network for specific set of different routes in a network for specific set of ingress-egress nodesingress-egress nodes
Shortcomings:Shortcomings: Computation burden (maxflow), Computation burden (maxflow), uses much longer paths, cannot estimate uses much longer paths, cannot estimate interference for a cluster of nodesinterference for a cluster of nodes
Not very likely to be implemented by vendors Not very likely to be implemented by vendors due to complexitydue to complexity
41IFA’2005ECE6609
LSP Routing LSP Routing AlgorithmAlgorithm
Simple algorithm:Simple algorithm:– uses simple known routing schemes; uses simple known routing schemes; – no assumptions about incoming traffic; no assumptions about incoming traffic; – non-stationary trafficnon-stationary traffic
At each interval, the algorithm At each interval, the algorithm evaluates the best routing evaluates the best routing algorithm for the measured algorithm for the measured current traffic loadcurrent traffic load
J. de Oliveira, F. Martinelli, and C. Scoglio,J. de Oliveira, F. Martinelli, and C. Scoglio,““SPeCRA: A SPeCRA: A Stochastic Performance Comparison Routing Algorithm Stochastic Performance Comparison Routing Algorithm for LSP Setup in MPLS Networks,” for LSP Setup in MPLS Networks,” IEEE Globecom, IEEE Globecom, Taiwan, Nov. 2002.Taiwan, Nov. 2002.
42IFA’2005ECE6609
Traffic Engineering ToolTraffic Engineering Tool– LSP Setup LSP Setup – LSP DimensioningLSP Dimensioning– LSP PreemptionLSP Preemption– LSP RoutingLSP Routing
Measurement ToolMeasurement Tool– Available Bandwidth MeasurementAvailable Bandwidth Measurement
TEAM ComponentsTEAM Components
43IFA’2005ECE6609
Bandwidth MeasurementBandwidth Measurement
Measure/estimate the available bandwidth in a Measure/estimate the available bandwidth in a link/path to analyze the performance of the link/path to analyze the performance of the networknetwork
Existing tools to measure link capacity:Existing tools to measure link capacity:– Pathchar based (Jacobson 1997):Pathchar based (Jacobson 1997): Link-by-Link MeasurementLink-by-Link Measurement– Packet Pair based (Keshav 1991):Packet Pair based (Keshav 1991): E2E CapacityE2E Capacity – Nettimer (Lai 2001):Nettimer (Lai 2001): E2E CapacityE2E Capacity– AMP (NLANR 2002):AMP (NLANR 2002): Active link-by-link MeasurementActive link-by-link Measurement– OCXmon (NLANR 2002):OCXmon (NLANR 2002): Passive link-by-link MeasurementPassive link-by-link Measurement– MRTG (Oetiker 2000):MRTG (Oetiker 2000): 5 min averages of link utilization5 min averages of link utilization– Pathload (Jain 2002):Pathload (Jain 2002): E2E available BW MeasurementE2E available BW Measurement
44IFA’2005ECE6609
AAvailable vailable BBandwidth andwidth EstEstimator imator (ABEst)(ABEst)
MRTGMRTG– Monitor the traffic load on network linksMonitor the traffic load on network links– Highly portable SNMP based toolHighly portable SNMP based tool– Provides only 5 min averages of link Provides only 5 min averages of link
utilizationutilization
MRTG++MRTG++– Our modification to MRTG to reduce the Our modification to MRTG to reduce the
averaging time to 10 secaveraging time to 10 sec– MRTG++ is used to poll the network devices MRTG++ is used to poll the network devices
with 10 sec granularity with 10 sec granularity T. T.
Anjali, C. Scoglio, L. Chen, I. Akyildiz, and G. Uhl,Anjali, C. Scoglio, L. Chen, I. Akyildiz, and G. Uhl,“ABEst: AnAvailable Bandwidth Estimator within an Autonomous System,” Proc. of IEEE Globecom, November 2002
45IFA’2005ECE6609
Available Bandwidth Available Bandwidth EstimatorEstimator
AssumptionsAssumptions– SNMP is enabled in the domainSNMP is enabled in the domain– MRTG++ is used to poll the network devices with 10 MRTG++ is used to poll the network devices with 10
sec granularitysec granularity NotationsNotations
– LL((tt) : Traffic load at time ) : Traffic load at time tt :: Length of averaging interval of MRTG++Length of averaging interval of MRTG++– LL[[kk] :] : Average load in [(Average load in [(kk-1)-1), k, k]]– p p : Number of past measurements in prediction: Number of past measurements in prediction– hh : Number of future samples reliably predicted : Number of future samples reliably predicted– AAhh[[kk] : Available bandwidth estimate for [(] : Available bandwidth estimate for [(k+k+1)1), , ((kk++hh))]]
46IFA’2005ECE6609
ABEst (Contd.)ABEst (Contd.)
We use the past We use the past pp samples to predict the samples to predict the utilization for the next utilization for the next hh samples samples
Utilize the covariance method for predictionUtilize the covariance method for prediction
Values of Values of pp and and hh varied according to the varied according to the estimation errorestimation error
kk-p+1 k+h
47IFA’2005ECE6609
ABEst (Contd.)ABEst (Contd.)
1.1. At time instant At time instant kk, available bandwidth measurement is desired., available bandwidth measurement is desired.
2.2. Find the vectors Find the vectors wwaa, , aa[1,[1,hh] using covariance method given ] using covariance method given pp and the previous measurements.and the previous measurements.
3.3. Find Find and and
4.4. Predict Predict AAhh[[kk] for [(] for [(kk+1)+1), (, (kk++hh)t].)t].
5.5. At time (At time (kk++hh)t, get )t, get
6.6. Find the error vector Find the error vector
7.7. Set Set kk = = kk++hh..
8.8. Obtain new values for Obtain new values for pp and and hh..
9.9. Go to step 1.Go to step 1.
ˆ ˆ[ 1], , [ ] TL k L k h [ 1], , [ ] TL k p L k
[ 1], , [ ] Te k e k h
[ 1], , [ ] TL k L k h
48IFA’2005ECE6609
ABEst (Contd.)ABEst (Contd.)
Covariance estimated asCovariance estimated as
Covariance normal equationsCovariance normal equations
AAhh[[kk] estimated] estimated– Either C – max{predicted utilization vector}Either C – max{predicted utilization vector}– Or C – Effective bandwidth from the utilization Or C – Effective bandwidth from the utilization
vectorvector
( , ) [ ] [ ]k
Li k N p
r n m L i n L i m
(0) (0, )(0,0) (0, 1)
(1) (1, )
( 1,0) ( 1, 1)( 1) ( 1, )
a LL L
a L
L La L
w r ar r p
w r a
r p r p pw p r p a
49IFA’2005ECE6609
ABEst (Contd.)ABEst (Contd.)
Algorithm for h and pAlgorithm for h and p– If s/m > ThIf s/m > Th11, decrease , decrease hh until until hhminmin and and
increase increase pp till till ppmaxmax multiplicatively multiplicatively
– If ThIf Th11 > s/m > Th > s/m > Th22, decrease , decrease hh until until hhminmin and increase and increase pp till till ppmaxmax additively additively
– If s/m < ThIf s/m < Th22, then:, then: If m> ThIf m> Th33*M*M22
EE, decrease , decrease hh until until hhminmin and increase and increase pp
till till ppmaxmax additively additively
If ThIf Th33*M*M22EE > m > Th > m > Th44*M*M22
EE, keep , keep hh and and pp constant constant
If m < ThIf m < Th44*M*M22EE, increase , increase hh and decrease and decrease pp till till ppminmin
additivelyadditively
50IFA’2005ECE6609
Performance Performance EvaluationEvaluation
hhminmin=10=10
200 300 400 500 60010
15
20
25
30
35
40
Sample number
Ba
nd
wid
th (
MB
/s)
Actual Peak-bw Est.Eff-bw Est.
51IFA’2005ECE6609
Performance Performance EvaluationEvaluation
hhminmin=20=20
200 300 400 500 60010
15
20
25
30
35
40
Sample number
Ba
nd
wid
th (
MB
/s)
ActualPeak-bw Est.Eff-bw Est.
52IFA’2005ECE6609
TEAM/AA ARCHITECTURETEAM/AA ARCHITECTURE
Traffic Engineering Automated Traffic Engineering Automated Manager (TEAM) and Adaptive Agent Manager (TEAM) and Adaptive Agent (AA):(AA):– Manage heterogeneous networksManage heterogeneous networks
Different services such as best-effort, real-time, Different services such as best-effort, real-time, etc.etc.
Different network technologies such as wired Different network technologies such as wired and wireless mobile networksand wireless mobile networks
– Manage large networksManage large networksMultiple domainsMultiple domains
53IFA’2005ECE6609
TEAM/AA ARCHITECTURETEAM/AA ARCHITECTURE
TEAM TEAMTEAM
AA
AA
AA
AA
AA
AA
Inter-Domain OperationInter-Domain Operation
54IFA’2005ECE6609
SimulationTool
TrafficEngineeringTool (TET)
Measurement/
Performance Evaluation
ToolNetworkPlanningTEAM
SimulationTool
TrafficEngineeringTool (TET)
Measurement/
Performance Evaluation
ToolNetworkPlanningTEAM
TEAM/AA TEAM/AA EXPERIMENTSEXPERIMENTS
BWN-Lab NASA GSFC
NPN (NREN)
55IFA’2005ECE6609
Inter-domain Resource Inter-domain Resource ManagementManagement
Inter-domain resource reservation agreementsInter-domain resource reservation agreementsEstimate the traffic on an inter-domain link and forecast Estimate the traffic on an inter-domain link and forecast
its capacity requirement, based on a measurement of the its capacity requirement, based on a measurement of the current usagecurrent usage
Efficient resource utilization while keeping the number of Efficient resource utilization while keeping the number of reservation modifications to low values.reservation modifications to low values.
Two approaches for resource allocationTwo approaches for resource allocation– Off-line: simple and predictable but lead to resource Off-line: simple and predictable but lead to resource
wastagewastage– On-line : “Cushion” scheme On-line : “Cushion” scheme (Terzis 2001)(Terzis 2001) wherein wherein
extra bandwidth is reserved over the current usage.extra bandwidth is reserved over the current usage.large number of re-negotiations to satisfy the QoS.large number of re-negotiations to satisfy the QoS.
- “A New Scheme for Traffic Estimation and Resource Allocation for Bandwidth Brokers,” Computer Networks Journal, April 2003
- “Filtering and Forecasting Problems for Aggregate Traffic in Internet Links,” Performance Evaluation Journal, 2004
56IFA’2005ECE6609
Resource Reservation Resource Reservation ProblemProblem
AssumptionsAssumptions– Estimate traffic for one traffic classEstimate traffic for one traffic class
– Number of established sessions is Number of established sessions is NN and stays and stays constant during analysisconstant during analysis
– For each session, flows are defined as active For each session, flows are defined as active periodsperiods
– Each flow has a constant rate of Each flow has a constant rate of bb bits per bits per secondsecond
– Flows are assumed to be Poissonian with Flows are assumed to be Poissonian with exponential inter-arrival times and durationsexponential inter-arrival times and durations
57IFA’2005ECE6609
Model FormulationModel Formulation
NotationsNotations– y(m): aggregate traffic on link at time m
– x(m): number of active flows on link at time m
y(m): noisy measure of the aggregate traffic on link at time m
– x(m): estimate of x(m)
– pk(t): probability that number of active flows at time
t is k
58IFA’2005ECE6609
Traffic EstimationTraffic Estimation
Generating function G(z,t), with the initial condition G(z,mT)=zx(m)
( )( )
( )
( 1)( , ) ( , ) where ( , )
( , ) ( 1)
N tx m
t
z z z eG z t C z t C z t
C z t z z e
ˆ ˆ ˆ( ) ( 1) ( ) ( ) ( 1)x m Ax m B k m y m CAx m CB
where ( )
( )1
( ) is Kalman Filter Gain
T
T
A e
NB e
C b
k m
59IFA’2005ECE6609
Allocation Allocation ForecastingForecasting
xx((mm) to forecast ) to forecast RR((mm+1)+1)Define Define and and
Q Q as the transition probability as the transition probability matrixmatrix
0 1( ) ( ) ( )T
NP p t p t p t
1
1 1
( 1)
0 1
ˆ[ ( ), ]
and
where
1 1Define
Define ( ) min . .
Then ( 1) ( )
t mTmT
m TTt
N
mT
xx x m N
P QP Q Y Y
P Ye C C e Y P
P Y e dt C p p pT T
x m x s t p
R m bx m
60IFA’2005ECE6609
Performance Performance EvaluationEvaluation
N=20, l=m=0.005N=20, l=m=0.005
0 3000 6000 90000
5
10
15
20
25
Time (sec)
Ba
nd
wid
th (
Mb
ps)
ActualEPABBCushion
61IFA’2005ECE6609
TEAM ImplementationTEAM Implementation C. Scoglio, T. Anjali, J. Cavalcante, I. F. Akyildiz, G. Uhl, C. Scoglio, T. Anjali, J. Cavalcante, I. F. Akyildiz, G. Uhl,
"TEAM: A Traffic Engineering Automated Manager for "TEAM: A Traffic Engineering Automated Manager for DiffServ based MPLS Networks“ DiffServ based MPLS Networks“IEEE Communications Magazine, October 2004.IEEE Communications Magazine, October 2004.
TEAM has been TEAM has been implemented to implemented to run on a computer run on a computer with the Linux OS.with the Linux OS.
This testbed has This testbed has been used as the been used as the platform to platform to implement and implement and test the operation test the operation of TEAM.of TEAM.
62IFA’2005ECE6609
TEAM Top-LevelTEAM Top-Level DesignDesign
User interfaceserver
Commands
New bandwidthrequest
LSP Setup
Configurerouters
Routers
Trigger receiver
Configuration
Topology updates
Update topology
Preemption Reroute
Route
Create/Destroy/Resize LSP
Create/Resize LSP
Route
Label, path,
priority, bandwidth
Path, priority, bandwidth
LSPs to be destroyed
LSPs to be re-routed
Route
Path, priority,bandwidth
Topology change
New bandwidth
request
Path, priority,bandwidth
Label, path
Scheduler MRTGInterface Measurements
63IFA’2005ECE6609
TEAM Module TEAM Module HierarchyHierarchy
ABEST
COMMAND CONFIG
EVENTS
GRAPH
LSP_DB
LSP_SETUP
MPET
MRTG
PREEMPT
REQUEST_DB
REQUEST
REA
ROUTING
RRDTOOL
SCHEDULER
SNMP
TOPOLOGY
UI-SERVER
UI-PROTOCOL
RE-ROUTE
GSL
TET
NET_SNMP
64IFA’2005ECE6609
Performance Performance EvaluationEvaluation
Topology with 40 nodes and 64 links of Topology with 40 nodes and 64 links of capacity 600 Mbpscapacity 600 Mbps
Comparison with a traditional managerComparison with a traditional manager– Shortest path routing for LSPsShortest path routing for LSPs– Shortest path routing for trafficShortest path routing for traffic– LSP setup based on service level LSP setup based on service level
agreementsagreements– No LSP preemptionNo LSP preemption– No on-line network measurementsNo on-line network measurements
65IFA’2005ECE6609
ConclusionsConclusions
Development of TEAM, an automated Development of TEAM, an automated manager for MPLS networks, that manager for MPLS networks, that performs network design and adaptive performs network design and adaptive network management including LSP network management including LSP and traffic routing, LSP setup and and traffic routing, LSP setup and capacity allocation, etc. based on capacity allocation, etc. based on network measurements.network measurements.
66IFA’2005ECE6609
TEAM Future WorkTEAM Future Work
– Heterogeneity: Heterogeneity: MPLS and non-MPLS and non-MPLS domains; fixed and MPLS domains; fixed and mobile wireless domainsmobile wireless domains
– Mobility Management IssuesMobility Management Issues– Preemption Policy for HandoffPreemption Policy for Handoff
67IFA’2005ECE6609
IETF on QoS (2000)IETF on QoS (2000)
What is needed is a Set of QoS mechanismsWhat is needed is a Set of QoS mechanisms and a number of ways these mechanisms canand a number of ways these mechanisms can be configured to interoperate in a stable andbe configured to interoperate in a stable and consistent fashion?consistent fashion?
Broader Architectural Approaches/RequirementsBroader Architectural Approaches/Requirements than IntServ and DiffServ, than IntServ and DiffServ, includ. routing, resource management, includ. routing, resource management, monitoring and accounting, application andmonitoring and accounting, application and service development. service development.
68IFA’2005ECE6609
IETF on QoS (2002)IETF on QoS (2002)
Most carriers zero out any QoS related bits Most carriers zero out any QoS related bits (ToS, DiffServ) of incoming packets and look at (ToS, DiffServ) of incoming packets and look at nothing but the IP destination address.nothing but the IP destination address.
IP routing protocols route around failures not IP routing protocols route around failures not congestion congestion (NOTE: some have congestion notification(NOTE: some have congestion notification indicators telling to sender to use less BW.. indicators telling to sender to use less BW.. But not good for VoIP).But not good for VoIP).
Scalability, security and restorability still big issues.Scalability, security and restorability still big issues.
Full integration of service types still a dream.Full integration of service types still a dream.
69IFA’2005ECE6609
IETF on QoS (2004)IETF on QoS (2004)
Application requirements are known; Application requirements are known; Needed QoS classes defined; monitoring metrics Needed QoS classes defined; monitoring metrics widely usedwidely used QoS is not just per-domain but E2E and thus has toQoS is not just per-domain but E2E and thus has to be signaled/provisioned across networksbe signaled/provisioned across networks Requirements for needed protocols largely doneRequirements for needed protocols largely done
Much work needed to ensure solutions are:Much work needed to ensure solutions are: Reliable, secure, and scalable capable of supportingReliable, secure, and scalable capable of supporting all traffic/service mixes/prioritiesall traffic/service mixes/priorities Resilient regarding any between layer dependencies, Resilient regarding any between layer dependencies, e.g., rapid restoration of QoS.e.g., rapid restoration of QoS.
70IFA’2005ECE6609
E2E QoS IssuesE2E QoS Issues
NI-to NI IP QOS classes but there is no widelyNI-to NI IP QOS classes but there is no widely accepted delivery mechanism yet.accepted delivery mechanism yet. Still unclear if QoS related resource control ofStill unclear if QoS related resource control of other networks will ever be allowed; even if someother networks will ever be allowed; even if some carriers agree, interoperability is still an issuecarriers agree, interoperability is still an issue Overprovisioning STILL central to many solutions.Overprovisioning STILL central to many solutions. No forum is addressing reliability and restorationNo forum is addressing reliability and restoration mechanism for E2E IP QOS in any tangible way yet.mechanism for E2E IP QOS in any tangible way yet. Recent attention on IP emergency communications Recent attention on IP emergency communications have served as a magnet for all of the have served as a magnet for all of the shortcomingsshortcomings of E2E proposals in IP world.of E2E proposals in IP world.
71IFA’2005ECE6609
Future of QoSFuture of QoS
Traffic load continues to double each yearTraffic load continues to double each year The industry will and has a very sustainable The industry will and has a very sustainable futurefuture Consequently, QoS deployment has become anConsequently, QoS deployment has become an increasingly attractive propositionincreasingly attractive proposition Service Providers offer QoS-based services, Service Providers offer QoS-based services, while Enterprises leverage these services to while Enterprises leverage these services to reduce expensesreduce expenses
72IFA’2005ECE6609
Why Still No QoS Why Still No QoS DeploymentDeployment
Lack of Business ModelsLack of Business Models Bad Experience in Service OfferingsBad Experience in Service Offerings Standardization EffortsStandardization Efforts Implementation ProblemsImplementation Problems Lack of Billing/Tariffing ModelsLack of Billing/Tariffing Models Misconception of “NO NEED FOR Misconception of “NO NEED FOR
QoS”QoS”