Capacity Planning for Internet Service

Networks

Geoff HustonNTW Track4

Issues

TCP/IP Protocol Behavior

IssuesUsage ProfileCapacity GuidelinesGrowth Levels

Planning Issues

Understand the domain of operation technical issues market issues competitive issues regulatory issues

TCP/IP Protocol Issues

TCP/IP is NOT a flow damped protocol end to end flow management sliding window protocol adaptive flow rate designed to probe and

use max available end to end bandwidth only limited by end system buffering size

bandwidth x delay

system buffers are getting larger as OS vendors come to understand the problem

TCP/IP Protocol Issues

TCP/IP Data Flow Rate AdaptationTCP/IP Data Flow Rate Adaptation

Time

Dat

a F

low

Rat

e

Steady State Available Bandwidth

Rate overflow loading into network queues

TCP/IP Protocol Issues

No network-based flow control mechanismNetwork-based packet loss signals end

systems to collapse transmission window sizeVarying window size allows adaptive flow

metrics to adapt to changing maximum available capacity

Sustained insufficient capacity leads to congestion induced collapse of data throughput

TCP/IP Protocol Issues

Many simultaneous TCP sessions interact with non-predictive non-uniform load (ftp://thumper.bellcore.com/pub/dvw/sigcom93.ps.Z)

Peaks start to synchronize with each other

Buffering evens out individual flows, but buffers themselves behave with fluctuating load

Buffering adds latency

TCP/IP Protocol Issues

TCP/IP efficiency under congestion loadTCP/IP efficiency under congestion load

Traffic Level

Dat

a T

hro

ugh

put

33% 66%

33%

66% Congestive Collapse -

The slide to miseryand packet loss

TCP/IP Protocol Issues

TCP vs UDPUDP-based applications

Internet Phone, Video, WorkgroupUDP Issues

no flow control mechanism sustained use forces precedence over TCP

flows increasing use of flow bandwidth negotiated

protocols for these applications (RSVP)

TCP/IP Protocol Issues

Damping network capacity is not a demand management tool

Network capacity must be available to meet peak demand levels without congestion loss

Usage Profile

Two major Internet use profiles: Business use profile

peak at 1500 - 1600plateau 1000 - 1730

Residential dial profilepeak at 2030 - 2330plateau 1900 - 2400

Usage Profile

Distance profiles12% Local18% Domestic Trunk70% International

Traffic mix due to: Distance invisible applications without user

control Distance independent user tariff

Capacity Guidelines

Link Utilisation Average weekly traffic level set to 50%

of available bandwidth.Core network capacity should be

dimensioned according to aggregate access bandwidth

Link Usage Profile - optimal

peak loading less than 10% timegreater than 50% loading for

50% timetraffic bursting visible

Link Usage Profile - overloaded

90% peak loading for 45% time60% peak loading for 60% timeno burst profile at peak loadsimbalanced traffic (import based)

visible plateau traffic load signaturesmall load increases cause

widening plateau

Link Usage Profile - saturated

Overall Growth Levels

Two growth pressures: serviced population the changing Internet service model

more network-capable applicationsusing more bandwidth

Overall Growth Levels

For a constant service model the growth curve will exhibit demand saturation

0

100

200

300

400

500

1 11 21 31 41 51 61

Overall Growth Levels

For a changing service model the saturation point will move

More intense network use by increasingly sophisticated applications

0

200

400

600

800

1000

1200

1 11 21 31 41 51 61

Technology shift

How to plan

Generate a market demand model forecast the number of services in operation

existing servicesgrowth ratemarket capture level (competitive position)

forecast the average demand per servicedial access, leased lineweb, ftp, usenetcaching trendsnew Internet services

How to plan

demand models are typically very uncertain indicators high level of uncertainty of externalities highly dynamic competitive position poorly understood (and changing) service

demand model

How to plan

Forward extrapolation assume existing traffic follows a general

growth model forward extrapolat the growth model

Good for short term planning (12 months)

Cannot factor latent demand market price sensivity

Trend forecasting

0

20000

40000

60000

80000

100000

120000

7/1/

96

7/11

/96

7/21

/96

7/31

/96

8/10

/96

8/20

/96

8/30

/96

9/9/

96

9/19

/96

9/29

/96

10/9

/96

10/1

9/96

10/2

9/96

11/8

/96

11/1

8/96

11/2

8/96

12/8

/96

12/1

8/96

12/2

8/96

1/7/

97

1/17

/97

1/27

/97

2/6/

97

2/16

/97

2/26

/97

3/8/

97

3/18

/97

3/28

/97

4/7/

97

4/17

/97

4/27

/97

Total Capacity

Daily Traffic IN

Daily Traffic OUT

historical usage vs capacity data

Growth Trends

0

100000

200000

300000

400000

500000

600000

1/7/

96

28/7

/96

24/8

/96

20/9

/96

17/1

0/96

13/1

1/96

10/1

2/96

6/1/

97

2/2/

97

1/3/

97

28/3

/97

24/4

/97

21/5

/97

17/6

/97

14/7

/97

10/8

/97

6/9/

97

3/10

/97

30/1

0/97

26/1

1/97

23/1

2/97

19/1

/98

15/2

/98

14/3

/98

10/4

/98

7/5/

98

3/6/

98

30/6

/98

27/7

/98

23/8

/98

in

out

Trend - high

Trend - mid

Trend - Low

97/98 bandwidth

Planning

undertake demand and trend forecast models

constantly review the model against generated usage data

recognise that the larger the capacity you need the longer the lead time to purchase it

recognise that the bigger the purchase the greater the requirement for capital