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Addicted to speed:
Why broadband service providers
need a ‘healthier lifestyle’
CommunicAsia 2014
Singapore, 17th June 2014
PREDICTABLE
NETWORK
SOLUTIONS
© 2014 All Rights Reserved
Modified version for Web upload.
Same content, different format.
The only network
performance science
company in the world.
PREDICTABLE
NETWORK
SOLUTIONS
If we are wrong then please tell us,
as it’s a bit lonely sometimes!
Dr Neil Davies
Co-founder and Chief Scientist
Computer Scientist, Mathematician
and Engineer (but not a Futurologist)
Sustainability
of ICT
The
expertise I
am sharing
here
15-25 YEARS AHEAD
We can foresee
many likely
future demands
on broadband
networks
TODAY
15-25 YEARS AHEAD
Meeting these
requirements is
influenced by
what we do…
TODAY
15-25 YEARS AHEAD
We are unknowingly
storing up some big
problems!
This may be a
difficult message to hear
You need to
change your ‘lifestyle’…
…and adopt a
‘healthier’ alternative
But why…
…do I need to
change my
lifestyle?
Key messages
Problem
The pursuit of ever
more speed
has put the broadband
business in a
vicious circle.

Why so?
Speed (‘bandwidth’) is
no longer
a helpful model
for broadband.

So what?
You need to
change your model
to survive and

prosper.
Problem

More, more, more
More
supply
Great! A
“faster”
network!
More, more, more
More elastic
demand
But demand
automatically
expands to use
resources
More, more, more
Faster saturation
of infrastructure
This creates a
“jackhammer”
effect
More, more, more
More
variability
Applications need
consistency of loss
and delay
More, more, more
Lower QoE
When they experience
rapidly varying loss and
delay, you get…
More, more, more
More complaints
and churn
In competitive
markets that
drives…
In other markets the
regulator gets the flack and
comes under pressure to act
More, more, more
More cost
Churn is expensive, so
you have to restore QoE.
How?
More, more, more
More
supply
And round we go
again!
More supply
More elastic
demand
Faster
saturation of
infrastructure
More
variability
Lower QoE
More
complaints
and churn
More cost
The technical vicious circle
The investment ‘cycle of doom’Service
quality
Undepreciated
assetvalue 

($$$)
($)
Let’s look at how QoE
and operator debt
change over time
TIME
ServiceQualityUndepreciatedAssetValue
The investment ‘cycle of doom’Service
quality
Undepreciated
assetvalue 

($)
($$$)
As you add users to an
empty network, QoE
declines
Those users help you to
pay down the debt used to
fund the network
ServiceQualityUndepreciatedAssetValue
The investment ‘cycle of doom’Service
quality
Undepreciated
assetvalue 

($)
($$$)
QoE falls faster than
simplistic bandwidth
models suggest and
churn rises
You need to upgrade
earlier than your
capacity planning and
financial models
predicted
ServiceQualityUndepreciatedAssetValue


($$$)
($)
The investment ‘cycle of doom’
Rising load makes service quality fall,
forcing repeated upgrades
ServiceQualityUndepreciatedAssetValue


($$$)
($)
The investment ‘cycle of doom’
The period between upgrades falls due to
decreasing effectiveness of capacity upgrades
to resolve the QoE issue
ServiceQualityUndepreciatedAssetValue
The investment ‘cycle of doom’
Failure to keep up with ever-rising demand
forces ever-shorter upgrade cycles
UndepreciatedAssetValue
The end result?
UndepreciatedAssetValue
Death via
unserviceable
debt load

Why so?

What drives
the vicious circle?
Cosmic Ludic Ecological
Constraints on everything
We live in a finite universe where we
can’t get everything we might want
Cosmic
Cosmic constraints
Physics limits us in many
ways: not just the speed
of light, but also energy
conservation, or how
much information we
can encode on a channel
(Shannon limits)
Ludic
Ludic constraints
“Ludic” constraints are
“games”, with mathematical
rules and limits. Chess can be
mathematically modelled, for
example
Broadband is like a statistical
‘game of chance’
Ecological
Ecological constraints
There are constraints of
human nature, law,
technology availability,
standards, etc.
Cosmic Ludic Ecological
Speed
of light
Statistical
multiplexing
Pricing
policy
Broadband drug: stat mux gain
Why trust in increasing
speed is now misplaced
This may be a difficult
message to hear.
We did warn you!
Why trust in increasing
speed is now misplaced
Packetdelay
Let’s consider the delay a
packet experiences…
Why trust in increasing
speed is now misplaced
Pre-IP EarlyIP Now
…and see how that
changes over time
Packetdelay
Cosmic constraint
Pre-IP EarlyIP Now
Packetdelay
How did this
constraint change?
Pre-IP EarlyIP Now
Geography
Packetdelay
Cosmic constraint
Fixed overhead: Speed
of light, packet routing
lookups
Pre-IP EarlyIP Now
The speed of light
is not changing
Packetdelay
Geography
Cosmic constraint
Pre-IP EarlyIP Now
Packetdelay
Ecological constraint
How did this
constraint change?
Pre-IP EarlyIP Now
Serialisation
speed
Packetdelay
Ecological constraint
How quickly can we squirt
the packet over a link?
Pre-IP EarlyIP Now
Packetdelay
Ecological constraint
Historically speed did
correlate with more value
Serialisation
speed
Pre-IP EarlyIP Now
Packetdelay
Ludic constraint
How did this
constraint change?
Variability
Pre-IP EarlyIP Now
Packetdelay
Ludic constraint
Delay due to other
packets in the system
Pre-IP EarlyIP Now
Packetdelay
Ludic constraint
Variability
Now dominates application performance
G, S and V
G
S
V
Variability
Serialisation speed
Geography
The outliers are what kill application
performance, and they are growing
Shifting constraints
G
S
V
Ecological
Cosmic
Once we had digital networks, the key
constraint was ecological
Shifting constraints
G
S
V
Ludic
Ecological
Cosmic
It is now ludic, but mainstream
network engineering & regulatory
policy has yet to reflect this
Networks are…
trading
spaces


…principally for V,
in a statistical ‘game of chance’
How ‘V’ is
distributed among
competing streams
is how demand
is matched to the supply
Fact
“Magical”
thinking
Problem
When there is
excessive delay, people are
trying to make V disappear
by building more capacity
rather than distributing it
through scheduling
Problem
Attempting to solve scheduling problems using
capacity is inefficient and ineffective
Result: telecoms is a capital killer
Source: PwC
http://www.pwc.com/en_GX/gx/communications/publications/assets/pwc_capex_final_21may12.pdf
It’s not getting
any better since
then
So what?

Is there a better approach?
Can the cycle be broken?
What has to change?
NOW FUTURE
MORE
BANDWIDTH
Selling
peak speed
and commodity
inputs
What has to change?
NOW FUTURE
MORE
BANDWIDTH
Selling
peak speed
and commodity
inputs
BETTER
SCHEDULING
Selling QoE &
differentiated
application
outcomes
(Simplified) structure
of broadband demand
Bulk
Interactive
Real-time
(Simplified) structure
of broadband supply
Bulk
Interactive
Single
class of
service
Today’s economic model
Real-time
Bulk
Interactive
Real-time
Too quality-
sensitive
Too cost-
sensitive
COST REVENUE
Today’s economic model
Real-time
Bulk
Interactive
Real-time
COST REVENUE
Everything carries the high costs
of real-time, but the revenues
don’t match that cost structure
Example of a possible
alternative supply approach
Economy
Standard
Superior This three-class “polyservice”
model is specially constructed. It
should not be confused with
existing “priority QoS”
mechanisms
Example of a possible
alternative supply approach
Superior traffic costs more
to deliver… so should
attract a premium
Economy
Standard
Superior
Example of a possible
alternative supply approach
Standard traffic is today’s
off-peak Internet… but is
consistently the same
Economy
Standard
Superior
Example of a possible
alternative supply approach
Economy traffic does not
drive capacity upgrades
Economy
Standard
Superior
It is also unsuitable for real-time applications
Future
rational economic model
COST REVENUE
Economy
Standard
Superior
Economy
Standard
Superior
Five class model
incorporates resilience
SuperiorStandard
SuperiorStandard
Economy
SuperiorStandard
SuperiorStandard
Economy
SuperiorStandard
SuperiorStandard
Economy
Drives capacity
planning
(primary service)
COST
Drives resilience &
redundancy
capacity planning
COST
Drives
REVENUE
How to reach
health and prosperity?
NO!
1. Firefighting
– due to rapid QoE declines.
2. Panic buying
– of capacity to deal with QoE crises.
3. Complaining!
– There's loads of slack.
YES!
1. Measure QoE
– on customer-centric basis.
2. Increase utilisation via scheduling
– to make a profit.
3. Plan capacity
– based on QoE effects.
The Prize
10%?
30%?
>100%?
Improvement in
QoE from assets
Spectacular cost and QoE
improvements are possible
when the best available
mathematics is applied to
scheduling problems.
Dr Neil Davies
Neil.Davies@pnsol.com
Tel: +44 (0)3333 407715
PREDICTABLE
NETWORK
SOLUTIONS
Thank you

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