call admission control

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1 Call Admission Control Carey Williamson Department of Computer Science University of Calgary

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Call Admission Control. Carey Williamson. Department of Computer Science University of Calgary. The CAC Function: Everything you ever wanted to know but were afraid to ask. Carey Williamson. Department of Computer Science University of Saskatchewan. Introduction. - PowerPoint PPT Presentation

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Page 1: Call Admission Control

1

Call Admission Control

Carey Williamson

Department of Computer ScienceUniversity of Calgary

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The CAC Function:Everything you ever wanted to

know but were afraid to ask

Carey Williamson

Department of Computer ScienceUniversity of Saskatchewan

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Introduction

The purpose of an admission control algorithm is to decide, at the time of call arrival, whether or not a new call should be admitted into the network

A new call is admitted if and only if its Quality of Service (QOS) constraints can be satisfied without jeapordizing the QOS constraints of existing calls in the network

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Call Admission Control

Admission control decision is made using a traffic descriptor that specifies traffic characteristics and QOS requirements

Traffic characteristics:– peak cell rate (PCR), sustained cell rate (SCR),

maximum burst size (MBS),... QOS requirements:

– tolerable cell loss, cell delay, delay variation

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Issues

Want to make efficient use of the network (i.e., accommodate as many calls as possible, and maintain a reasonably high level of network utilization)

Want to guarantee quality of service for all calls that get into the network

Tradeoff: can’t always have both!

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Why is it Difficult?

ATM is completely based on the idea of statistical multiplexing of VBR sources

No assignment of specific slots to users, but statistical assignment of capacity based on expected traffic characteristics

Providing guarantees requires conservatism High utilization requires aggressiveness

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Why is it Difficult? (Cont’d)

Typical traffic sources are bursty Some traffic sources are VERY bursty Traffic can be highly unpredictable Accurate traffic descriptors may not be

known in advance Traffic may not conform to its descriptor

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LeastUnderstood

MostUnderstood

Traffic Characterization

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LeastUnderstood

MostUnderstood

Voice

Traffic Characterization

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LeastUnderstood

MostUnderstood

VoiceCBRvideo

Traffic Characterization

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LeastUnderstood

MostUnderstood

VoiceCBRvideo

Packetdata

Traffic Characterization

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LeastUnderstood

MostUnderstood

VoiceCBRvideo

Packetdata

Traffic Characterization

Image

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LeastUnderstood

MostUnderstood

VoiceCBRvideo

Packetdata

Image

VBRvideo

Traffic Characterization

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Multiplexing

Two basic approaches Deterministic multiplexing Statistical multiplexing

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Deterministic Multiplexing

The traditional means of bandwidth allocation in telecommunications networks

Each traffic type has an inherent bit rate (e.g., voice traffic = 64 kilobits per second)

Allocate precisely that bandwidth for each call, for the duration of the call

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Deterministic Multiplexing (Cont’d)

Advantages:– Simple– Works great for CBR traffic (PCR = SCR)

Disadvantages:– Inefficient for VBR traffic (PCR !=SCR)

Allocating PCR can waste lots of capacity

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Deterministic versus Statistical Multiplexing

Bit

rate

Source 1: peak 12 Mbps,mean 8 Mbps

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Deterministic versus Statistical Multiplexing

Bit

rate

12 Mbps

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Deterministic versus Statistical Multiplexing

Bit

rate

Source 2:peak 10 Mbps,mean 6 Mbps

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Deterministic versus Statistical Multiplexing

Bit

rate

22 Mbps(12 + 10)

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Deterministic versus Statistical Multiplexing

Bit

rate

22 Mbps(12 + 10)

Average utilizationwill be 14/22 = 64%

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Deterministic versus Statistical Multiplexing

Bit

rate

Bit

ra

te

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Deterministic versus Statistical Multiplexing

Bit

rate

Bit

ra

te

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Deterministic versus Statistical Multiplexing

Bit

rate

Bit

ra

te

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Deterministic versus Statistical Multiplexing

Bit

rate

Bit

ra

te

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Deterministic versus Statistical Multiplexing

Bit

rate

Bit

ra

te

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Deterministic versus Statistical Multiplexing

Bit

rate

Bit

ra

te

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Deterministic versus Statistical Multiplexing

Bit

rate

Bit

ra

te

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Deterministic versus Statistical Multiplexing

Bit

rate

Bit

ra

te

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Deterministic versus Statistical Multiplexing

Bit

rate

Bit

ra

te

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Deterministic versus Statistical Multiplexing

Bit

rate

Bit

ra

te

Bandwidth savingwith StatisticalMultiplexing

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Statistical Multiplexing

Basic idea: ‘‘pack in’’ more than would be able to fit with deterministic multiplexing

Takes advantage of the variable bit rate bursty nature of traffic

Not all traffic sources will need their peak rate at the same time (hopefully)

Peaks and valleys should balance out

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Statistical Multiplexing (Cont’d)

Advantages:– More calls can fit in the network– Increases utilization, efficiency of network– Statistical gain can be significant

Disadvantages:– QOS is hard to guarantee (100% guarantee)

Always an element of risk, however slight

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Simple CAC Schemes

int CAC_Function(TrafficDescriptor *TD)

{

return( YES );

}

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Simple CAC Schemes

int CAC_Function(TrafficDescriptor *TD)

{

return( YES );

}

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Simple CAC Schemes (Cont’d)

int CAC_Function(TrafficDescriptor *TD)

{

return( NO );

}

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Simple CAC Schemes (Cont’d)

int CAC_Function(TrafficDescriptor *TD)

{

return( NO );

}

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Possible CAC Schemes

Peak rate allocation Mean rate allocation (Peak + Mean) / 2 Virtual Bandwidth [Murase 90] Schedulable Region [Lazar 91] Effective Bandwidth [Elwalid 93]

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Peak Rate Allocation

Allocate the peak cell rate for the source Same as Deterministic Multiplexing Guarantees that no cell loss occurs Guarantees that bandwidth is wasted if

source is at all bursty (peak > mean) The amount of wasted bandwidth depends

on the peak-to-mean ratio

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Mean Rate Allocation

Allocate bandwidth based on the mean rate (SCR)

By definition, this is adequate over a long enough time duration

Drawback is the delay for traffic bursts May not be enough capacity to handle

bursts within a tolerable delay

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(Peak + Mean) / 2

Peak rate is the most that is needed Mean rate is the least that is needed ‘‘Correct’’ allocation must be in between But where is the real question! (Peak + Mean) / 2 is one guess Suitability depends on characteristics of

source (e.g., time spent at or near each)

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Can you do better?

Of course! Effective Bandwidth: [Elwalid 93] Virtual Bandwidth: [Murase 90] Schedulable Region: [Lazar 91] We’ll look at some of these in more detail

in just a moment...

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Summary

Call Admission Control is one of the most difficult problems to deal with in ATM networks

Difficult problem, no standard solution Lots of research activity Impossible to find a single ‘‘best’’ answer