measurementbased admission control algorithms admission control is a preventive congestion control...
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IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
MeasurementBased Admission Control Algorithms
Bob Callaway Joni Finlon Susan Stewart
North Carolina State UniversityCSC/ECE 776  Performance Evaluation of Computer Networks
Student Research Presentation
April 27, 2004
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Presentation Outline
1 IntroductionGoals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
2 Three Different MBAC AlgorithmsCLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
3 Practical Implementations of CACVoice Over IP (VoIP)Video ConferencingMultimedia Resource Control
4 ConclusionsBob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Goals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
Section Outline
1 IntroductionGoals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
2 Three Different MBAC AlgorithmsCLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
3 Practical Implementations of CACVoice Over IP (VoIP)Video ConferencingMultimedia Resource Control
4 ConclusionsBob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Goals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
Congestion Control
The Role of Congestion Control
To protect the network and the user in order to achievenetwork performance objectives and optimize the usage of networkresources
Congestion control can be either preventive or reactive
Connection admission control is a preventive congestioncontrol method
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Goals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
Goals of Connection Admission Control
Three Main Goals of Connection Admission Control
Protect the network by preventing congestion
Meet QoS requirements of all connections
Obtain maximum statistical multiplexing gain
Uses an algorithm to decide whether to accept or reject arequest for a new connection to the network
Connection acceptance is based on two questions:
Does the new connection affect the QoS currently beingcarried by the switch?Can the switch provide the QoS requested by the newconnection?
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Goals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
Nonstatistical Connection Admission Control
Also called deterministic allocation or peak bandwidthallocation
Requires that the peak rate of the connection be reserved fora particular source
Advantages
It is easy to make adecision about whetherto accept or reject a newconnection
Disadvantages
The network will beunderutilized most of thetime (unless users aretransmitting CBR traffic)
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Goals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
Statistical Connection Admission Control
Allocated bandwidth is less than the peak rate of a source
Advantages
Network resources will bebetter utilized
Disadvantages
More difficult to implement
Can be CPU intensive
0 100 200 300 400 500 600 700 800 900 10000
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5x 105 Plot of Traffic Trace vs. Estimated Effective Bandwidths Meter Implementation: 1 Stream
Time (sec)
Thro
ughp
ut (b
ytes
/sec
)
Actual TrafficGaussian MethodCourcoubetis MethodNorros Method
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Goals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
Motivation of Effective Bandwidth
How do we determine the number of connections to admit to thenetwork to maximize efficiency by using statistical multiplexing?
Effective Bandwidth!
Effective bandwidth estimates the amount of bandwidth thatshould be allocated to a class of network traffic in order tomeet a QoS requirement, such as a delay or loss constraint
C =1
tlog E
[eX [0,t]
]
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Goals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
MeasurementBased Admission Control: An Overview
Why use a measurementbased scheme?
Nonmeasurementbased methods use the worst case boundsand result in low utilization of the network
Zero (or a very small number of) a priori assumptions must bemade about the arrival process of the traffic, sincemeasurements are used to describe the traffic
Useful for services that do not require tight guarantees, rathermore relaxed service commitments
Results in high network utilization and an acceptable level ofservice
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
CLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
Section Outline
1 IntroductionGoals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
2 Three Different MBAC AlgorithmsCLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
3 Practical Implementations of CACVoice Over IP (VoIP)Video ConferencingMultimedia Resource Control
4 ConclusionsBob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
CLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
Rate Envelope Multiplexing vs. Rate Sharing Multiplexing
Rate Envelope Multiplexing (REM)
Buffering effect is not taken into account when evaluatingcelllevel performance
Queueing process at the output port buffer is not considered
Provides for faster computations
Rate Sharing Multiplexing (RSM)
Requires model for queueing process at output port buffer
Can achieve higher efficiency than REM methods
Computationally complex; also dependent on input trafficmodel
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
CLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
Dynamic CAC in ATM Networks
B =
L
k=0
[k Cs
L
]+p(; t) ? n+1(k)
a(t) + san+1
Algorithm Overview
Independent of the classification of calls and does not use amodel for the arrival process
Makes admission decision by comparing measured upperbound of loss probability against QoS standard
Uses measurements to estimate the pdf of the number ofarriving cells per call in a renewal period
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
CLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
Dynamic CAC in ATM Networks (continued)
Algorithm Details
Uses exponential weighting to increase/decrease importanceof measurements/signalled parameters
If a new call request is received within the renewal period, thepdf is shifted by convolution to take the new worstcase cellarrival distribution into consideration
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
CLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
A DecisionTheoretic Approach to CAC in ATM Networks
Algorithm Overview
Key aspect of algorithm istime scale decomposition
Bayesian decisiontheoreticframework parameterizes thetradeoff between the costsand benefits of accepting anadditional call into thenetwork
Uses a measure of burstiness(peak to mean ratio) incalculations
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
CLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
A DecisionTheoretic Approach to CAC in ATM Networks
Algorithm Details
Makes the admission controldecision by comparing theinstantaneous load to a giventhreshold
Uses the control parameter y torepresent the tradeoff betweenutilization and cell loss
Cell loss ratio is effected by rate ofchange of the parameter p.
s =
[U(p, ) (y 1)M(p, )] f (p, )dpd
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
CLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
MBAC with Aggregate Traffic Envelopes
Algorithm Overview
Measures the maximal rateenvelope of the aggregate traffic,since the extreme values of theaggregate flow are likely to lead tolosses
Takes measurements in slottedtime, and computes statistics ofthe envelope over M time scales
Can make admission decision withregards to a specified loss rateand/or a given delay bound
R1k =1
kmax
tT+kst
su=sk+1
au
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
CLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
MBAC with Aggregate Traffic Envelopes
Algorithm Details
A confidence level is derived such that for a given , thetraffic will not exceed the maximal envelope
The admission control decision is made by testing the newaggregate envelope against the delay/loss criterion
In the worst case, this algorithm bounds the loss probability orthe maximum delay; in the best case, significant statisticalmultiplexing gains can be realized
maxk=1,2,...,T
{k(Rk + rk + k C )
} Cd
RT + rT + T C
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
CLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
Comparison of Algorithm Characteristics
Method Measurement Decision Memory Model AssumedSS91 O(M) O(M) O(M) None
GKK95 O(1) O(1) O(N) Poisson/ExponentialQK01 O(T) O(1) O(T) None
M = Number of Bins in Distribution N = Number of Connections T = Number of Time Slots
Comparisons
REM models are less dependent on a priori traffic assumptions
SS91 does not make any traffic assumptions, but it has thehighest computational costs
QK01 has been shown to be practically implementable intestbed experiments using RSVP
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Voice Over IP (VoIP)Video ConferencingMultimedia Resource Control
Section Outline
1 IntroductionGoals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
2 Three Different MBAC AlgorithmsCLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
3 Practical Implementations of CACVoice Over IP (VoIP)Video ConferencingMultimedia Resource Control
4 ConclusionsBob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Voice Over IP (VoIP)Video ConferencingMultimedia Resource Control
Example of CAC: Voice Over IP (VoIP)
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Voice Over IP (VoIP)Video ConferencingMultimedia Resource Control
Example of MBAC: Voice Over IP (VoIP)
VoIP Examples
Cisco
IOS SoftwareGateways
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Voice Over IP (VoIP)Video ConferencingMultimedia Resource Control
Example of CAC: Voice Over IP (VoIP)
Cisco
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Voice Over IP (VoIP)Video ConferencingMultimedia Resource Control
Example of CAC: Voice Over IP (VoIP)
VoIP Examples
NexTone
Multiprotocol Session Controller (MSC)
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Voice Over IP (VoIP)Video ConferencingMultimedia Resource Control
Example of CAC: Video Conferencing
Video Conferencing Examples
Polycom
PathNavigatorTM Premier CallProcessing Server Solution
Cisco
Multimedia Conference ManagerH.323 Gatekeeper
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
Voice Over IP (VoIP)Video ConferencingMultimedia Resource Control
Example of CAC: Multimedia Resource Control
Alcatel 5430 Session Resource Broker
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
References
Section Outline
1 IntroductionGoals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
2 Three Different MBAC AlgorithmsCLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
3 Practical Implementations of CACVoice Over IP (VoIP)Video ConferencingMultimedia Resource Control
4 ConclusionsBob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
References
Conclusions
Connection Admission Control
Some type of CAC is needed to ensure the QoS of existingconnections and to control additional connections to thenetwork
Measurementbased Admission Control Algorithms
How well does it ensure that the service commitments areupheld?
How high can network utilization reach while still upholdingQoS commitments?
Do the benefits of statistical multiplexing outweigh the cost ofonline measurements and other statistical computations?
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
References
H. Saito, K. Shiomoto.Dynamic Call Admission Control in ATM Networks.IEEE Journal on Selected Areas in Communications, 1991.
R. Gibbens, F. Kelly, P. Key.A DecisionTheoretic Approach to Call Admission Control inATM Networks.IEEE Journal on Selected Areas in Communications, 1995.
J. Qiu, E. Knightly.MeasurementBased Admission Control with Aggregate TrafficEnvelopes.IEEE/ACM Transactions on Networking, April 2001.
H. Perros, K. ElsayedCall Admission Control Schemes: A Review.IEEE Communications Magazine, November 1996.
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms

IntroductionThree Different MBAC AlgorithmsPractical Implementations of CAC
Conclusions
References
K. Shiomoto, N. Yamanaka, T. Takahashi.Overview of MeasurementBased Connection AdmissionControl Methods in ATM Networks.IEEE Communication Surveys, First Quarter 1999.
E. Knightly, N. Shroff.Admission Control for Statistical QoS: Theory and Practice.IEEE Network, March/April 1999.
S. Jamin, P.B. Danzig, S.J. Shenker, L. ZhangA Measurementbased Admission Control Algorithm forIntegrated Services Packet Networks (Extended Version)IEEE/ACM Transactions on Networking, February 1997
S. Jamin, P.B. Danzig, S.J. ShenkerComparison of Measurementbased Admission ControlAlgorithms for ControlledLoad ServiceIEEE INFOCOM, 1997
Bob Callaway, Joni Finlon, Susan Stewart MeasurementBased Admission Control Algorithms
IntroductionGoals of Connection Admission ControlTypes of CAC AlgorithmsEffective BandwidthOverview of MeasurementBased Admission Control
Three Different MBAC AlgorithmsCLR Upperbound FormulaDecisionTheoretic ApproachMBAC with Aggregate Traffic EnvelopesComparison of Algorithm Characteristics
Practical Implementations of CACVoice Over IP (VoIP)Video ConferencingMultimedia Resource Control
ConclusionsReferences