1 statistical multiplexing: basic principles carey williamson university of calgary
Post on 18-Dec-2015
214 views
TRANSCRIPT
1
Statistical Multiplexing: Basic Principles
Carey Williamson
University of Calgary
2
Introduction Statistical multiplexing is one of the
fundamental principles on which ATM networking is based
Everyone understands the basic concept of stat mux, but figuring out how to do it right is still a hard problem
LOTS of papers on it, but probably as many “answers” as authors!
3
Agenda This presentation: one sample
paper Woodruff and Kositpaiboon,
“Multimedia Traffic Management Principles for Guaranteed ATM Network Performance”
IEEE JSAC, Vol . 8, No. 3, April 1990
4
Overview of Paper Identifies several high-level general
principles regarding statistical multiplexing, traffic management, and call admission control
Presents simulation results to illustrate quantitatively the regions where statistical multiplexing makes good sense and where it does not
5
Main Principles Reasonable bandwidth utilization Robustness to traffic uncertainties Simplicity Node architecture independence
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
Deterministic Multiplexing for Peak/Mean = 2
0.5
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
0.5
Deterministic Multiplexing for Peak/Mean = 20
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
Deterministic Multiplexing for Peak/Mean = 2
0.5
Deterministic Multiplexing for Peak/Mean = 20
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
0.5
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
0.5
Statistical Multiplexing for Peak/Mean = 2when average burst B = 10
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
0.5
Statistical Multiplexing for Peak/Mean = 2when average burst B = 100
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
0.5
B = 10
B = 100Peak/Mean = 2
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
0.5
Statistical Multiplexing for Peak/Mean = 20when average burst B = 10
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
0.5
Statistical Multiplexing for Peak/Mean = 20when average burst B = 100
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
0.5B = 10
B = 100
Peak/Mean = 20
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
0.5B = 10
B = 100
Peak/Mean = 20
B = 10
B = 100
Peak/Mean = 2
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Maxim
um
Lin
k U
tiliz
ati
on
0.0
1.0
0.5B = 10
B = 100
Peak/Mean = 20
B = 10
B = 100
Peak/Mean = 2
Best region for statistical multiplexing
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Bu
ffer
Siz
e/A
vg B
urs
t Le
ngth
0
30Buffer Requirements
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Bu
ffer
Siz
e/A
vg B
urs
t Le
ngth
0
30Buffer Requirements
Utilization = 10%
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Bu
ffer
Siz
e/A
vg B
urs
t Le
ngth
0
30Buffer Requirements
Utilization = 50%
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Bu
ffer
Siz
e/A
vg B
urs
t Le
ngth
0
30Buffer Requirements
Utilization = 90%
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Bu
ffer
Siz
e/A
vg B
urs
t Le
ngth
0
30Effect of Burst Size Distribution
Deterministic
Utilization = 10%
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Bu
ffer
Siz
e/A
vg B
urs
t Le
ngth
0
30Effect of Burst Size Distribution
Geometric
Utilization = 10%
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Bu
ffer
Siz
e/A
vg B
urs
t Le
ngth
0
30Effect of Burst Size Distribution
Utilization = 50%
Deterministic
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Bu
ffer
Siz
e/A
vg B
urs
t Le
ngth
0
30Effect of Burst Size Distribution
Utilization = 50%
Geometric
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Bu
ffer
Siz
e/A
vg B
urs
t Le
ngth
0
30Effect of Burst Size Distribution
Utilization = 90%
Deterministic
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Bu
ffer
Siz
e/A
vg B
urs
t Le
ngth
0
30Effect of Burst Size Distribution
Utilization = 90%
Geometric
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Bu
ffer
Siz
e/A
vg B
urs
t Le
ngth
0
30Effect of Burst Size Distribution
G
GG
D
DD
U = 90%
U = 50%
Granularity of Source (Peak rate/Link rate)
0.0 1.0
Bu
ffer
Siz
e/A
vg B
urs
t Le
ngth
0
30Effect of Burst Size Distribution
G
GG
D
DD
U = 90%
U = 50%
Best regionfor statisticalmultiplexing
31
Summary A nice paper describing the general
principles to follow in call admission control, statistical multiplexing, and traffic management
Quantitative illustration of performance effects, and illustration of when statistical multiplexing works and when it does not
32
Summary (Cont’d) General traffic management
principles:– Reasonable bandwidth utilization– Robustness– Simplicity– Node architecture independence
33
Summary (Cont’d) Simulation observations: Easier to multiplex “small” things than
“big” things (peak to link ratio) The burstier the traffic sources (peak
to mean ratio), the greater the potential gains of statistical multiplexing, but the harder it is to multiplex traffic safely and still guarantee performance
34
Summary (Cont’d) Easier to multiplex homogeneous traffic
than it is for heterogeneous traffic The larger the average burst length, the
harder it is to multiplex the traffic The larger the average burst length, and
the greater the variation in burst size, the more buffers you will need in your system in order to multiplex effectively