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PREDICTABLE
NETWORK
SOLUTIONS

Future of Broadband Workshop
ITU Telecom World 2013, Bangkok
Dr Neil Davies

Predictable Network Solutions Ltd

Martin Geddes

Martin Geddes Consulting Ltd
© 2013 All Rights Reserved
PREDICTABLE
NETWORK
SOLUTIONS

The only ex-ante network performance
engineering company in the world.
Consultancy on the future of voice,
cloud and broadband.

Dr Neil Davies Co-founder and Chief Scientist
Ex: University of Bristol (23 years).
Former technical head of joint university/research institute (SRF/PACT).

Martin Geddes Founder
Ex: BT, Telco 2.0, Sprint, Oracle, Oxford University.
Thought leader on the future of the telecommunications industry.
Our offer to you today
• Help you to understand the mismatch
between:
– What people are aspiring to achieve (demand)
– What you are actually doing (supply)

• Propose how to close the gap
– Technically grounded in reality
– Practical advice on how to proceed
This may be a
difficult message to hear
We’ve had a lot
of experience of
people not
wanting to hear
what we’re
about to tell you
Our three key messages
1. Speed (‘bandwidth’) is no longer a
helpful model for broadband.
2. The pursuit of ever more speed
means the broadband business is in
a death spiral.
3. You need to re-frame your
resource model to survive.
The whole market is

ADDICTED TO PEAK SPEED
Selling data speed and mechanisms

A proxy for
‘more speed’
Pressure from regulatory
environment for speed

SPEED!
League tables for speed
Incentives
matter and
everyone gets
incentivised to
deliver more
speed
Speed is not the only

THING THAT MATTERS
Example: Satellite in Asia-Pacific
SERVICE A

SERVICE B

< 1Mbit

> 6Mbit

Which is better?
Service A: Low variability
Service B: High variability
Same satellite,
same location,
similar time,
different service
More speed is not necessarily better

SERVICE A


‘Slower’
and
good QoE

SERVICE B
Probably not
what you
would have
expected


‘Faster’
but
poor QoE
This is a common issue to

ALL BROADBAND DELIVERY
Was this just a
one-off issue?
No.
DSL: same bandwidth, different QoE
Comparison between two LLU broadband providers to same location in the UK

 
Two customers
serviced off the same
pole in the same
street by two
different wholesale
DSL providers

The one on right has 1/3 the capability of the

left for carrying POTS-quality VoIP
Same problem on cable

We see the
same thing on
other networks
(e.g. 3G, small cells)
but cannot share the
data for contractual
reasons
What network attributes drive

GOOD USER EXPERIENCE?
A Skype experience (3-way call)
1.8M/448k ADSL – wholesale 20CN
Loss: 0.1%.
Delay: 40ms-50ms
We measured
path loss and
delay (summary
on next slide)

20M/2M Cable broadband
Loss: <0.5%.
Delay (one-way): 50ms-60ms, jumping
to 500ms for a second or two, then back

10M/1M ADSL Business LLU
Loss: Wandering from a typical 0%-2% up
to as high as 48% for a second or two.
Delay: 50-70ms
Different speeds & characteristics
SLOW & LOW VARIABILITY OF LOSS/DELAY





Good Experience

Bad Experience

VERY FAST
& VARIABLE DELAY


FAST
& VARIABLE LOSS
Speed was not the key differentiator

VARIABILITY



Bad Skype QoE

HIGH

The faster
broadband lines
gave a worse
experience as
reported by Skype’s
own QoE metric



LOW
SLOW

SPEED

FAST
Why did these
user experiences differ?

Because they had different

loss and delay
(and that’s it!)
So why are we
promoting
‘speed’?
The application hierarchy of need

3. Predictable loss and delay

2. Stable: Good ‘stationarity’

These are not
getting enough
attention

We need more
than just
‘speed’ for
good QoE

1. Feasible: Sufficient capacity
Yes, we need
capacity

Note: exact requirements are application-dependent

!
!
What network attributes

DRIVE COST?
Valid reasons for spending capex

• More customers
 More revenue
• Increased usage
 More revenue
• Regulatory requirement
Invalid reason for spending capex

Premature
infrastructure and
capacity upgrades
Lots of capex spent on ‘tin’
Spectrum, fibre,
copper, ducts,
street cabinets,
cell towers, and
the transmission
and routing
equipment
Is it being
well spent?
More, more, more
When we believe
more speed is the
only answer, we
are doomed to go
round again (and
again)

More supply

More
complaints
and churn

More elastic
demand

Lower QoE

Faster
saturation of
backhaul
More
variability

There is a
‘jackhammer’
effect that gets
worse over
time
Service quality
Service Quality

The investment ‘cycle of doom’

QoE declines
faster than
network planning
rules forecast
Time

Rising load makes
service quality fall,
forcing upgrades

Failure of technology to keep
up with ever rising demand
forces shorter upgrade cycles

Undepreciated
asset value
Undepreciated Asset Value


Death via
unserviceable
debt load
Time
Telecoms is a capital killer

As an industry,
we’re not
covering our cost
of capital

Something is
very badly wrong

Source: PwC
http://www.pwc.com/en_GX/gx/communications/publications/assets/pwc_capex_final_21may12.pdf
What drives the

PREMATURE UPGRADES?
Quality of experience

How to think about cost drivers
HEAVEN
HIGH

Network has lots of
users, who feel like the
network is still empty
because they are
suitably isolated from
each other

LOW

HELL
LOW

HIGH

Resource efficiency
Quality of experience

As load increases, QoE falls
Add more demand to
today’s packet
networks, and
everyone’s experience
degrades since all your
packets are ‘pollution’
to other users

HIGH

Access
network
LOW

LOW

HIGH

Resource efficiency
Quality of experience

Add capacity to resolve falling QoE
HEAVEN
HIGH

HEAVEN

Heaven gets further away

Access
network
LOW

LOW

MEDIUM

Resource efficiency

HIGH
Quality of experience

Can’t ensure QoE for applications
with strong stationarity requirements
Current approaches require
all traffic to be schedulable
within very short timescales

HIGH

Access
network

Infeasible

LOW

LOW

MEDIUM

Resource efficiency

HIGH
Quality of experience

Broadband networks need to be
kept empty to keep working
HIGH

!
Access
network

The only way
current network elements
can deliver good
enough QoE is by
being idle frequently

Queues
need time
to ‘relax’

!

This microscopic
queueing effect has
massive macroscopic
implications, both
technically and
economically

LOW

LOW

MEDIUM

Resource efficiency

HIGH
Quality of experience

Because of this you currently
can’t run networks ‘hot’
HIGH

Access
network

Protocols ‘collapse’
‘Goodput’ plummets

LOW

LOW

MEDIUM

Resource efficiency

HIGH
Quality of experience

With every upgrade the QoE
boundary for next upgrade drops
HIGH

Diminishing
returns from
adding more
capacity to solve
excess delay

UPGRADE
THRESHOLD

5

4

3

2

1

LOW

LOW

MEDIUM

Resource efficiency

HIGH
How to re-frame the

RESOURCE PROBLEM?
Delay (and loss) have a structure
Delay is due to…

G

S

V

Geography

Serialisation
speed

Variability
Why trust in increasing
speed is now misplaced

The speed of light
is not changing
G

Pre-IP

Early IP

Now

Geography
Why trust in increasing
speed is now misplaced

Historically speed
did correlate with
more value
S
G

Pre-IP

Early IP

Serialisation speed
Geography

Now
Why trust in increasing
speed is now misplaced
Not all packets
experience this
much delay, but the
outliers are the
ones that matter to
QoE

Now dominates
application
performance
V

S

Early IP

Serialisation speed

G

Pre-IP

Variability

Geography

Now
The commercial challenge:

How to break
the investment
cycle of doom?
The technical challenge:

How to measure,
manipulate and
manage ‘V’?
+

REVENUE
REQUIRES
FIT-FOR-PURPOSE EXPERIENCE

Demand

APPLICATION OUTCOMES
Click here for separate
presentation on this
model

DATA FLOWS

SCHEDULING

Supply

TRANSMISSION RESOUCE
POWERED MECHANISMS
UNPOWERED TIN
ENABLES
COSTS

-

We need a robust
causative model of
the relationship
between
operator revenue
and cost
Networks are ‘trading spaces’

How ‘V’ is
distributed among
competing streams
is how demand
is matched to the supply
REVENUE
This makes all the
difference between
commercial success
and failure

Scheduling
SCHEDULING

This is where supply
and demand meet
…and nowhere else

COSTS
Quality of experience

The real difference between
telecoms heaven and hell
IDEAL
SCHEDULING

HIGH

LOW

TODAY!
LOW

HIGH

Resource efficiency
Your problem: magical thinking

When there is
excessive delay, you are
trying to make V disappear
by building more capacity
rather than distributing it
through scheduling
TWO fundamental resource limits
MAX CAPACITY

If you want to
move 10mbits in
1 sec, you need
(at least)
10mbit/sec of
transmission

Schedulability
demand

HIGH

Feasible

LOW
LOW

HIGH

Capacity demand

Infeasible
TWO fundamental resource limits
Infeasible

MAX
SCHEDULABILITY

Feasible

Schedulability
demand

HIGH

Even with perfect
knowledge and
mechanisms, you
can only schedule
so well

LOW
LOW

HIGH

Capacity demand
TWO fundamental resource limits

Schedulability
demand

HIGH

Infeasible
Feasible
In practise we
aren’t nearly
that good

LOW
LOW

HIGH

Capacity demand
TWO fundamental resource limits
We typically hit this
limit first (which is
why adding capacity
is not a good idea)

Schedulability
demand

HIGH
MAX CAPACITY

Infeasible

MAX
SCHEDULABILITY

Feasible
Feasible

LOW
LOW

HIGH

Capacity demand

Infeasible
Our problem

Schedulability
demand is growing fast
VoIP, gaming, 2-way video,
UC, HTML5 web…
The problem

Solving schedulability issues
(i.e. non-stationarity)
with capacity is
inefficient and ineffective
Quality of experience

There is only one feasible route
HEAVEN
HIGH

No slack
means
this is
not
possible

Focus on
scheduling
and QoE
first

We are going
about
broadband the
wrong way

LOW

…then
you get
stuck
here

HELL
LOW

HIGH

Resource efficiency

If you
focus on
resource
usage
first…
Is the path to heaven

TECHNICALLY ACHIEVABLE?
Yes
Pro-active control over scheduling ‘V’
We built a
demo ISP to
prove what we
say actually
works

HELL

HEAVEN
This network is
still delivering
good QoE at
100% load
Some qualityinsensitive traffic
gets slightly
worse treatment

We used a different resource
model to achieve this

90% of
load
What is the right

RESOURCE MODEL?
Different supply ‘performance’

1.LOSS
2.DELAY

}

Quality
This is the
resource
model you
need

Networks create value
by moving data with
bounded loss and delay
Need to frame the supply
differently to make issues soluble

Bandwidth

Quality

‘Quality’ is the
absence of
something
unwanted

‘Bandwidth’ is
the presence of
something
wanted
Speed

Loss and
delay
How to use this quality-centric

RESOURCE MODEL?
What has to change?
NOW

FUTURE

SUPPLY-PUSH

DEMAND-PULL

Selling
commodity
bandwidth
inputs

Selling
differentiated
application
outcomes
What has to change?

Focus on
enabling outcomes
not higher ‘speed’
Properly characterise
your demand

Demanddriven model
REVENUE
REQUIRES
FIT-FOR-PURPOSE
EXPERIENCE

OUTCOMES
FLOWS

Characterise
Demand
Do this first…

SCHEDULING
TRANSMISSION
MECHANISMS
TIN
ENABLES
COSTS

…then do this

Construct
Matching
Supply
What has to change?

Understand how
delivered QoE is a function
of loss and delay
Properly characterise
your supply requirements
So your service is
fit-for-purpose
A practical network

SUPPLY RESOURCE MODEL
Example of a supply approach:
Three layer model
Superior

Superior traffic costs more to deliver…
so should attract a premium

Standard

Standard traffic is today’s off-peak
Internet… but is consistently the same

Economy

Economy traffic does not drive capacity
upgrades
Today’s QoS
mechanisms
don’t deliver
this (or create
a service of no
value trying)

They don’t
understand
the ‘trades’
properly
– …but they still have
connectivity

Superior
Standard

• When there is a period of
network stress, some people
may get reduced service…

Standard

– …but not everyone needs it
– So we separate out resilient
traffic from non-resilient

Superior

• Provisioning capacity
for total resilience is
a real cost…

Resilient

Extend this to a five class model

Economy
Superior

Superior

Standard

Standard

Standard

Superior

Superior

Standard

Standard

Superior

Superior

Standard

Five class model has
rational economics

Economy

Economy

Economy

Drives
capacity planning
(primary service)
cost

Drives resilience &
redundancy capacity
planning cost

Drives revenue
SUMMARY & CONCLUSIONS
We are in a race to the bottom

This is not
negotiable
We’ve got into a
fight with the
mathematics of
statistical
multiplexing
Why so? Demand is not being met
Supply-push business
and technology model
Why so? Wrong kind of supply

Failure to align
with underlying
and unchanging
reality of packet
networking
Speed (and volume) are not value

We’ve seen
networks
where adding
capacity made
performance
get worse

!

Dangerous myth:
MORE SPEED IS ALWAYS BETTER

!
Broadband is becoming
critical national infrastructure

Needs to be dependable
Advanced
services need
predictable and
dependable
supply

No ice cream
(or insulin)
without fridgefreezers, which
need a reliable
power supply
We are creating a digital society

We can’t
externalise
our collective
risks

Implicit social contract
Keep getting scheduling wrong:
Crisis of legitimacy

Angry:
Customers
Investors
Regulators
Governments
Get scheduling right:
Golden age of broadband
1890s

Railways
1920s

Electricity
1960s

Oil
2020s

Broadband
RECOMMENDATIONS
What operators
should be asking themselves
1. Why am I trying to solve my scheduling
problems with more capacity?
2. For my key customer applications, am I
delivering the network supply that enables
good QoE?
– i.e. am I delivering the right loss and delay?

3. Given that there is a trading space, am I
constructing and offering the right data
transport products?
What regulators
should be asking themselves
1. What is the value that I am getting from
demanding more speed?
2. Measurement is de facto regulation,
therefore am I measuring the right thing?
3. What are the key applications that need
managed QoE and cost to drive societal
benefits?
To learn more
Free Future of Communications newsletter:
www.martingeddes.com
Follow Martin Geddes on Twitter: @martingeddes
Other presentations:
slideshare.net/mgeddes/
White papers on network performance:
www.pnsol.com
PREDICTABLE
NETWORK
SOLUTIONS

Neil Davies
Neil.Davies@pnsol.com

Martin Geddes
mail@martingeddes.com

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Future of Broadband workshop presentation - ITU Telecom World 2013

  • 1. PREDICTABLE NETWORK SOLUTIONS Future of Broadband Workshop ITU Telecom World 2013, Bangkok Dr Neil Davies Predictable Network Solutions Ltd Martin Geddes Martin Geddes Consulting Ltd © 2013 All Rights Reserved
  • 2. PREDICTABLE NETWORK SOLUTIONS The only ex-ante network performance engineering company in the world. Consultancy on the future of voice, cloud and broadband. Dr Neil Davies Co-founder and Chief Scientist Ex: University of Bristol (23 years). Former technical head of joint university/research institute (SRF/PACT). Martin Geddes Founder Ex: BT, Telco 2.0, Sprint, Oracle, Oxford University. Thought leader on the future of the telecommunications industry.
  • 3. Our offer to you today • Help you to understand the mismatch between: – What people are aspiring to achieve (demand) – What you are actually doing (supply) • Propose how to close the gap – Technically grounded in reality – Practical advice on how to proceed
  • 4. This may be a difficult message to hear We’ve had a lot of experience of people not wanting to hear what we’re about to tell you
  • 5. Our three key messages 1. Speed (‘bandwidth’) is no longer a helpful model for broadband. 2. The pursuit of ever more speed means the broadband business is in a death spiral. 3. You need to re-frame your resource model to survive.
  • 6. The whole market is ADDICTED TO PEAK SPEED
  • 7. Selling data speed and mechanisms A proxy for ‘more speed’
  • 9. League tables for speed Incentives matter and everyone gets incentivised to deliver more speed
  • 10. Speed is not the only THING THAT MATTERS
  • 11. Example: Satellite in Asia-Pacific SERVICE A SERVICE B < 1Mbit > 6Mbit Which is better?
  • 12. Service A: Low variability
  • 13. Service B: High variability Same satellite, same location, similar time, different service
  • 14. More speed is not necessarily better SERVICE A  ‘Slower’ and good QoE SERVICE B Probably not what you would have expected  ‘Faster’ but poor QoE
  • 15. This is a common issue to ALL BROADBAND DELIVERY Was this just a one-off issue? No.
  • 16. DSL: same bandwidth, different QoE Comparison between two LLU broadband providers to same location in the UK   Two customers serviced off the same pole in the same street by two different wholesale DSL providers The one on right has 1/3 the capability of the left for carrying POTS-quality VoIP
  • 17. Same problem on cable We see the same thing on other networks (e.g. 3G, small cells) but cannot share the data for contractual reasons
  • 18. What network attributes drive GOOD USER EXPERIENCE?
  • 19. A Skype experience (3-way call) 1.8M/448k ADSL – wholesale 20CN Loss: 0.1%. Delay: 40ms-50ms We measured path loss and delay (summary on next slide) 20M/2M Cable broadband Loss: <0.5%. Delay (one-way): 50ms-60ms, jumping to 500ms for a second or two, then back 10M/1M ADSL Business LLU Loss: Wandering from a typical 0%-2% up to as high as 48% for a second or two. Delay: 50-70ms
  • 20. Different speeds & characteristics SLOW & LOW VARIABILITY OF LOSS/DELAY   Good Experience Bad Experience VERY FAST & VARIABLE DELAY  FAST & VARIABLE LOSS
  • 21. Speed was not the key differentiator VARIABILITY  Bad Skype QoE HIGH The faster broadband lines gave a worse experience as reported by Skype’s own QoE metric  LOW SLOW SPEED FAST
  • 22. Why did these user experiences differ? Because they had different loss and delay (and that’s it!) So why are we promoting ‘speed’?
  • 23. The application hierarchy of need 3. Predictable loss and delay 2. Stable: Good ‘stationarity’ These are not getting enough attention We need more than just ‘speed’ for good QoE 1. Feasible: Sufficient capacity Yes, we need capacity Note: exact requirements are application-dependent ! !
  • 25. Valid reasons for spending capex • More customers  More revenue • Increased usage  More revenue • Regulatory requirement
  • 26. Invalid reason for spending capex Premature infrastructure and capacity upgrades
  • 27. Lots of capex spent on ‘tin’ Spectrum, fibre, copper, ducts, street cabinets, cell towers, and the transmission and routing equipment Is it being well spent?
  • 28. More, more, more When we believe more speed is the only answer, we are doomed to go round again (and again) More supply More complaints and churn More elastic demand Lower QoE Faster saturation of backhaul More variability There is a ‘jackhammer’ effect that gets worse over time
  • 29. Service quality Service Quality The investment ‘cycle of doom’ QoE declines faster than network planning rules forecast Time Rising load makes service quality fall, forcing upgrades Failure of technology to keep up with ever rising demand forces shorter upgrade cycles Undepreciated asset value Undepreciated Asset Value  Death via unserviceable debt load Time
  • 30. Telecoms is a capital killer As an industry, we’re not covering our cost of capital Something is very badly wrong Source: PwC http://www.pwc.com/en_GX/gx/communications/publications/assets/pwc_capex_final_21may12.pdf
  • 32. Quality of experience How to think about cost drivers HEAVEN HIGH Network has lots of users, who feel like the network is still empty because they are suitably isolated from each other LOW HELL LOW HIGH Resource efficiency
  • 33. Quality of experience As load increases, QoE falls Add more demand to today’s packet networks, and everyone’s experience degrades since all your packets are ‘pollution’ to other users HIGH Access network LOW LOW HIGH Resource efficiency
  • 34. Quality of experience Add capacity to resolve falling QoE HEAVEN HIGH HEAVEN Heaven gets further away Access network LOW LOW MEDIUM Resource efficiency HIGH
  • 35. Quality of experience Can’t ensure QoE for applications with strong stationarity requirements Current approaches require all traffic to be schedulable within very short timescales HIGH Access network Infeasible LOW LOW MEDIUM Resource efficiency HIGH
  • 36. Quality of experience Broadband networks need to be kept empty to keep working HIGH ! Access network The only way current network elements can deliver good enough QoE is by being idle frequently Queues need time to ‘relax’ ! This microscopic queueing effect has massive macroscopic implications, both technically and economically LOW LOW MEDIUM Resource efficiency HIGH
  • 37. Quality of experience Because of this you currently can’t run networks ‘hot’ HIGH Access network Protocols ‘collapse’ ‘Goodput’ plummets LOW LOW MEDIUM Resource efficiency HIGH
  • 38. Quality of experience With every upgrade the QoE boundary for next upgrade drops HIGH Diminishing returns from adding more capacity to solve excess delay UPGRADE THRESHOLD 5 4 3 2 1 LOW LOW MEDIUM Resource efficiency HIGH
  • 39. How to re-frame the RESOURCE PROBLEM?
  • 40. Delay (and loss) have a structure Delay is due to… G S V Geography Serialisation speed Variability
  • 41. Why trust in increasing speed is now misplaced The speed of light is not changing G Pre-IP Early IP Now Geography
  • 42. Why trust in increasing speed is now misplaced Historically speed did correlate with more value S G Pre-IP Early IP Serialisation speed Geography Now
  • 43. Why trust in increasing speed is now misplaced Not all packets experience this much delay, but the outliers are the ones that matter to QoE Now dominates application performance V S Early IP Serialisation speed G Pre-IP Variability Geography Now
  • 44. The commercial challenge: How to break the investment cycle of doom?
  • 45. The technical challenge: How to measure, manipulate and manage ‘V’?
  • 46. + REVENUE REQUIRES FIT-FOR-PURPOSE EXPERIENCE Demand APPLICATION OUTCOMES Click here for separate presentation on this model DATA FLOWS SCHEDULING Supply TRANSMISSION RESOUCE POWERED MECHANISMS UNPOWERED TIN ENABLES COSTS - We need a robust causative model of the relationship between operator revenue and cost
  • 47. Networks are ‘trading spaces’ How ‘V’ is distributed among competing streams is how demand is matched to the supply
  • 48. REVENUE This makes all the difference between commercial success and failure Scheduling SCHEDULING This is where supply and demand meet …and nowhere else COSTS
  • 49. Quality of experience The real difference between telecoms heaven and hell IDEAL SCHEDULING HIGH LOW TODAY! LOW HIGH Resource efficiency
  • 50. Your problem: magical thinking When there is excessive delay, you are trying to make V disappear by building more capacity rather than distributing it through scheduling
  • 51. TWO fundamental resource limits MAX CAPACITY If you want to move 10mbits in 1 sec, you need (at least) 10mbit/sec of transmission Schedulability demand HIGH Feasible LOW LOW HIGH Capacity demand Infeasible
  • 52. TWO fundamental resource limits Infeasible MAX SCHEDULABILITY Feasible Schedulability demand HIGH Even with perfect knowledge and mechanisms, you can only schedule so well LOW LOW HIGH Capacity demand
  • 53. TWO fundamental resource limits Schedulability demand HIGH Infeasible Feasible In practise we aren’t nearly that good LOW LOW HIGH Capacity demand
  • 54. TWO fundamental resource limits We typically hit this limit first (which is why adding capacity is not a good idea) Schedulability demand HIGH MAX CAPACITY Infeasible MAX SCHEDULABILITY Feasible Feasible LOW LOW HIGH Capacity demand Infeasible
  • 55. Our problem Schedulability demand is growing fast VoIP, gaming, 2-way video, UC, HTML5 web…
  • 56. The problem Solving schedulability issues (i.e. non-stationarity) with capacity is inefficient and ineffective
  • 57. Quality of experience There is only one feasible route HEAVEN HIGH No slack means this is not possible Focus on scheduling and QoE first We are going about broadband the wrong way LOW …then you get stuck here HELL LOW HIGH Resource efficiency If you focus on resource usage first…
  • 58. Is the path to heaven TECHNICALLY ACHIEVABLE? Yes
  • 59. Pro-active control over scheduling ‘V’ We built a demo ISP to prove what we say actually works HELL HEAVEN This network is still delivering good QoE at 100% load Some qualityinsensitive traffic gets slightly worse treatment We used a different resource model to achieve this 90% of load
  • 60. What is the right RESOURCE MODEL?
  • 61. Different supply ‘performance’ 1.LOSS 2.DELAY } Quality This is the resource model you need Networks create value by moving data with bounded loss and delay
  • 62. Need to frame the supply differently to make issues soluble Bandwidth Quality ‘Quality’ is the absence of something unwanted ‘Bandwidth’ is the presence of something wanted Speed Loss and delay
  • 63. How to use this quality-centric RESOURCE MODEL?
  • 64. What has to change? NOW FUTURE SUPPLY-PUSH DEMAND-PULL Selling commodity bandwidth inputs Selling differentiated application outcomes
  • 65. What has to change? Focus on enabling outcomes not higher ‘speed’ Properly characterise your demand Demanddriven model
  • 67. What has to change? Understand how delivered QoE is a function of loss and delay Properly characterise your supply requirements So your service is fit-for-purpose
  • 68. A practical network SUPPLY RESOURCE MODEL
  • 69. Example of a supply approach: Three layer model Superior Superior traffic costs more to deliver… so should attract a premium Standard Standard traffic is today’s off-peak Internet… but is consistently the same Economy Economy traffic does not drive capacity upgrades Today’s QoS mechanisms don’t deliver this (or create a service of no value trying) They don’t understand the ‘trades’ properly
  • 70. – …but they still have connectivity Superior Standard • When there is a period of network stress, some people may get reduced service… Standard – …but not everyone needs it – So we separate out resilient traffic from non-resilient Superior • Provisioning capacity for total resilience is a real cost… Resilient Extend this to a five class model Economy
  • 71. Superior Superior Standard Standard Standard Superior Superior Standard Standard Superior Superior Standard Five class model has rational economics Economy Economy Economy Drives capacity planning (primary service) cost Drives resilience & redundancy capacity planning cost Drives revenue
  • 73. We are in a race to the bottom This is not negotiable We’ve got into a fight with the mathematics of statistical multiplexing
  • 74. Why so? Demand is not being met Supply-push business and technology model
  • 75. Why so? Wrong kind of supply Failure to align with underlying and unchanging reality of packet networking
  • 76. Speed (and volume) are not value We’ve seen networks where adding capacity made performance get worse ! Dangerous myth: MORE SPEED IS ALWAYS BETTER !
  • 77. Broadband is becoming critical national infrastructure Needs to be dependable Advanced services need predictable and dependable supply No ice cream (or insulin) without fridgefreezers, which need a reliable power supply
  • 78. We are creating a digital society We can’t externalise our collective risks Implicit social contract
  • 79. Keep getting scheduling wrong: Crisis of legitimacy Angry: Customers Investors Regulators Governments
  • 80. Get scheduling right: Golden age of broadband 1890s Railways 1920s Electricity 1960s Oil 2020s Broadband
  • 82. What operators should be asking themselves 1. Why am I trying to solve my scheduling problems with more capacity? 2. For my key customer applications, am I delivering the network supply that enables good QoE? – i.e. am I delivering the right loss and delay? 3. Given that there is a trading space, am I constructing and offering the right data transport products?
  • 83. What regulators should be asking themselves 1. What is the value that I am getting from demanding more speed? 2. Measurement is de facto regulation, therefore am I measuring the right thing? 3. What are the key applications that need managed QoE and cost to drive societal benefits?
  • 84. To learn more Free Future of Communications newsletter: www.martingeddes.com Follow Martin Geddes on Twitter: @martingeddes Other presentations: slideshare.net/mgeddes/ White papers on network performance: www.pnsol.com