Call Admission Control Instructor: Hamid R. Rabiee Spring 2012
Outlines Call admission Control Definition Issues Design approaches Multiplexing Possible CAC Schemes
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Digital Media Lab - Sharif University of Technology
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 jeopardizing the QOS constraints of existing calls in the network
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Digital Media Lab - Sharif University of Technology
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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Design Approaches Two basic approaches to admission control parameter-based admission control (PBAC) Computes the amount of network resources required to support a set of flows given a priori flow traffic characteristics Better for real-time applications (peak & average rates)
measurement-based admission control (MBAC) Relies on the measurement of actual traffic loads in making admission decisions Higher network utilization Low service commitments
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Multiplexing
Two basic approaches Deterministic multiplexing Statistical multiplexing
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Deterministic Bound We can define it by B/W or Delay requirements Provides for the worst-case requirements of flow Does granting a new request for service cause the worst-case behavior of the network to violate any delay bound?
For example, checks that the sum of all peak rates is less than the link capacity or not!
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 Bound 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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Probabilistic Bound Basic idea: „„pack in‟‟ more than would be able to fit with
deterministic multiplexing Interleaving of packets from different sources where the instantaneous degree of multiplexing is determined by the statistical characteristics of
the sources Using the statistical characterizations of current and incoming traffics
Takes advantage of the variable bit rate “burst 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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Probabilistic Bound 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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Bit rate
Deterministic versus Statistical Multiplexing
Source 1: peak 12 Mbps, mean 8 Mbps
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Digital Media Lab - Sharif University of Technology
Bit rate
Deterministic versus Statistical Multiplexing
12 Mbps
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Digital Media Lab - Sharif University of Technology
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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Digital Media Lab - Sharif University of Technology
Deterministic versus Statistical Multiplexing
Bit rate
22 Mbps (12 + 10)
Average utilization will be 14/22 = 64%
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Digital Media Lab - Sharif University of Technology
Bit rate
Bit rate
Deterministic versus Statistical Multiplexing
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Digital Media Lab - Sharif University of Technology
Bit rate
Bit rate
Deterministic versus Statistical Multiplexing
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Digital Media Lab - Sharif University of Technology
Bit rate
Bit rate
Deterministic versus Statistical Multiplexing
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Digital Media Lab - Sharif University of Technology
Bit rate
Bit rate
Deterministic versus Statistical Multiplexing
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Digital Media Lab - Sharif University of Technology
Bit rate
Bit rate
Deterministic versus Statistical Multiplexing
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Digital Media Lab - Sharif University of Technology
Bit rate
Bit rate
Deterministic versus Statistical Multiplexing
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Digital Media Lab - Sharif University of Technology
Bit rate
Bit rate
Deterministic versus Statistical Multiplexing
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Digital Media Lab - Sharif University of Technology
Bit rate
Bit rate
Deterministic versus Statistical Multiplexing
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Digital Media Lab - Sharif University of Technology
Bit rate
Bit rate
Deterministic versus Statistical Multiplexing
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Digital Media Lab - Sharif University of Technology
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Bandwidth saving with Statistical Multiplexing
Digital Media Lab - Sharif University of Technology
Bit rate
Bit rate
Deterministic versus Statistical Multiplexing
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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Digital Media Lab - Sharif University of Technology
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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Digital Media Lab - Sharif University of Technology
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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Digital Media Lab - Sharif University of Technology
(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] Reflects the source characteristics & the service requirements
Virtual Bandwidth: [Murase 90] Schedulable Region: [Lazar 91] The region in the space of possible loads for which a scheduling algorithm guarantees QoS The size & shape of the region depend on the scheduling algorithm, QoS constraints & traffic load
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Digital Media Lab - Sharif University of Technology
Summary Call Admission Control is one of the most difficult problems to deal
with in IP network Difficult problem, no standard solution Lots of research activity Impossible to find a single „„best‟‟ answer
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Digital Media Lab - Sharif University of Technology
References Elwalid, A.I.; Mitra, D.; , "Effective bandwidth of general Markovian traffic
sources and admission control of high speed networks," Networking, IEEE/ACM Transactions on , vol.1, no.3, pp.329-343, Jun 1993 Jay M Hyman, Aurel A Lazar, and Giovanni Pacifici, “Real-Time Scheduling
with Quality of Service Constraints,” IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 9 (1991): 1052--1063. T. Murase, H. Suzuki, S. Sato, and T. Takeuchi, "A call admission control scheme for ATM networks using a simple quality estimate," IEEE J. Select. Areas Commun., vol. 9, pp. 1461-1470, Dec. 1991.
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Next Session
Traffic Control Access
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