Embed Size (px)
Citation preview
Future of Broadband Workshop ITU Telecom World 2013, Bangkok
Dr Neil Davies Predictable Network Solutions Ltd
Martin Geddes
Martin Geddes Consulting Ltd
PREDICTABLE
NETWORK
SOLUTIONS
© 2013 All Rights Reserved
Dr Neil Davies Co-founder and Chief Scientist Ex: University of Bristol (23 years).
Former technical head of joint university/research institute (SRF/PACT).
The only ex-ante network performance engineering company in the world.
Martin Geddes Founder Ex: BT, Telco 2.0, Sprint, Oracle, Oxford University.
Thought leader on the future of the telecommunications industry.
Consultancy on the future of voice, cloud and broadband.
PREDICTABLE NETWORK
SOLUTIONS
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.
ADDICTED TO PEAK SPEED
The whole market is
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
THING THAT MATTERS
Speed is not the only
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 SERVICE B
‘Slower’
and good QoE
‘Faster’
but poor QoE
Probably not what you
would have expected
ALL BROADBAND DELIVERY
This is a common issue to
Was this just a one-off issue?
No.
DSL: same bandwidth, different QoE
The one on right has 1/3 the capability of the left for carrying POTS-quality VoIP
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
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
GOOD USER EXPERIENCE?
What network attributes drive
A Skype experience (3-way call)
20M/2M Cable broadband 10M/1M ADSL Business LLU
1.8M/448k ADSL – wholesale 20CN
Loss: <0.5%. Delay (one-way): 50ms-60ms, jumping
to 500ms for a second or two, then back
Loss: Wandering from a typical 0%-2% up to as high as 48% for a second or two.
Delay: 50-70ms
Loss: 0.1%. Delay: 40ms-50ms
We measured path loss and
delay (summary on next slide)
Different speeds & characteristics
VERY FAST
& VARIABLE DELAY
FAST
& VARIABLE LOSS
SLOW & LOW VARIABILITY OF LOSS/DELAY
Good Experience
Bad Experience Bad Experience
Speed was not the key differentiator
Bad Skype QoE
SPEED
VA
RIA
BIL
IT
Y
SLOW FAST
LOW
HIGH
The faster broadband lines
gave a worse experience as
reported by Skype’s own QoE metric
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’
1. Feasible: Sufficient capacity
Note: exact requirements are application-dependent
!
!
These are not getting enough
attention
We need more than just
‘speed’ for good QoE
Yes, we need capacity
DRIVE COST?
What network attributes
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
More supply
More elastic demand
Faster saturation of
backhaul
More variability
Lower QoE
More complaints and churn
When we believe more speed is the only answer, we
are doomed to go round again (and
again)
There is a ‘jackhammer’
effect that gets worse over
time
Failure of technology to keep
up with ever rising demand
forces shorter upgrade cycles
Rising load makes
service quality fall,
forcing upgrades
Serv
ice
Qu
alit
y
Time
Un
dep
reci
ated
Ass
et V
alu
e
Time
The investment ‘cycle of doom’
Death via unserviceable
debt load
QoE declines faster than
network planning rules forecast Se
rvic
e q
ual
ity
Un
dep
reci
ated
as
set
valu
e
Telecoms is a capital killer
Source: PwC http://www.pwc.com/en_GX/gx/communications/publications/assets/pwc_capex_final_21may12.pdf
As an industry, we’re not
covering our cost of capital
Something is very badly wrong
PREMATURE UPGRADES?
What drives the
Qu
alit
y o
f ex
pe
rie
nce
LOW HIGH
LOW
HIGH
HEAVEN
How to think about cost drivers
HELL
Resource efficiency
Network has lots of users, who feel like the network is still empty
because they are suitably isolated from
each other
Resource efficiency
Qu
alit
y o
f ex
pe
rie
nce
LOW HIGH
LOW
HIGH
Access network
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
Resource efficiency
Qu
alit
y o
f ex
pe
rie
nce
LOW MEDIUM
LOW
HIGH
HIGH
HEAVEN HEAVEN Heaven gets further away
Add capacity to resolve falling QoE
Access network
Resource efficiency
Qu
alit
y o
f ex
pe
rie
nce
LOW MEDIUM
LOW
HIGH
HIGH
Current approaches require all traffic to be schedulable within very short timescales
Can’t ensure QoE for applications with strong stationarity requirements
Access network
Infeasible
Resource efficiency
Qu
alit
y o
f ex
pe
rie
nce
LOW MEDIUM
LOW
HIGH
HIGH
The only way current network elements
can deliver good enough QoE is by
being idle frequently
Broadband networks need to be kept empty to keep working
! !
This microscopic queueing effect has
massive macroscopic implications, both
technically and economically
Queues need time to ‘relax’
Access network
Resource efficiency
Qu
alit
y o
f ex
pe
rie
nce
LOW MEDIUM
LOW
HIGH
HIGH
Protocols ‘collapse’ ‘Goodput’ plummets
Because of this you currently can’t run networks ‘hot’
Access network
Resource efficiency
Qu
alit
y o
f ex
pe
rie
nce
LOW MEDIUM
LOW
HIGH
HIGH
With every upgrade the QoE boundary for next upgrade drops
1 2 3 4 5
Diminishing returns from adding more
capacity to solve excess delay
UPGRADE THRESHOLD
RESOURCE PROBLEM?
How to re-frame the
Delay (and loss) have a structure
Delay is due to…
V S G Geography Serialisation
speed Variability
Why trust in increasing speed is now misplaced
G
Pre-IP Early IP Now
The speed of light is not changing
Geography
Why trust in increasing speed is now misplaced
Historically speed did correlate with
more value
G
S
Pre-IP Early IP Now
Geography
Serialisation speed
Why trust in increasing speed is now misplaced
G
S
V Variability
Pre-IP Early IP Now
Now dominates application
performance
Serialisation speed
Geography
Not all packets experience this
much delay, but the outliers are the
ones that matter to QoE
The commercial challenge:
How to break the investment cycle of doom?
The technical challenge:
How to measure, manipulate and
manage ‘V’?
COSTS
REVENUE
DATA FLOWS
APPLICATION OUTCOMES
FIT-FOR-PURPOSE EXPERIENCE
POWERED MECHANISMS
TRANSMISSION RESOUCE
REQUIRES
ENABLES
UNPOWERED TIN
SCHEDULING
Supply
-
Demand +
We need a robust causative model of
the relationship between
operator revenue and cost
Click here for separate presentation on this
model
Networks are ‘trading spaces’
How ‘V’ is distributed among competing streams
is how demand is matched to the supply
COSTS
REVENUE
SCHEDULING
Scheduling
This is where supply and demand meet
This makes all the difference between commercial success
and failure
…and nowhere else
Resource efficiency
Qu
alit
y o
f ex
pe
rie
nce
LOW HIGH
LOW
HIGH
IDEAL SCHEDULING
The real difference between telecoms heaven and hell
TODAY!
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
Capacity demand LOW HIGH
Feasible Infeasible
MAX CAPACITY
TWO fundamental resource limits
Sch
ed
ula
bili
ty
de
man
d
LOW
HIGH If you want to move 10mbits in 1 sec, you need
(at least) 10mbit/sec of transmission
Capacity demand LOW HIGH
TWO fundamental resource limits
Feasible
Sch
ed
ula
bili
ty
de
man
d
Infeasible
LOW
HIGH
Even with perfect knowledge and
mechanisms, you can only schedule
so well
MAX SCHEDULABILITY
Capacity demand LOW HIGH
TWO fundamental resource limits
Feasible
Sch
ed
ula
bili
ty
de
man
d Infeasible
LOW
HIGH
In practise we aren’t nearly
that good
Feasible
Infeasible
Capacity demand LOW HIGH
Feasible Infeasible
MAX CAPACITY
TWO fundamental resource limits
MAX SCHEDULABILITY
Sch
ed
ula
bili
ty
de
man
d
LOW
HIGH
We typically hit this limit first (which is
why adding capacity is not a good idea)
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
Resource efficiency
Qu
alit
y o
f ex
pe
rie
nce
LOW HIGH
LOW
HIGH
HEAVEN
There is only one feasible route
HELL If you
focus on resource
usage first…
Focus on scheduling and QoE
first
No slack means this is
not possible
…then you get stuck here
We are going about
broadband the wrong way
TECHNICALLY ACHIEVABLE?
Is the path to heaven
Yes
Pro-active control over scheduling ‘V’
We used a different resource model to achieve this
HELL
HEAVEN
90% of load
We built a demo ISP to
prove what we say actually
works This network is still delivering good QoE at 100% load
Some quality-insensitive traffic
gets slightly worse treatment
RESOURCE MODEL?
What is the right
Different supply ‘performance’
1.LOSS
2.DELAY
} Quality
Networks create value by moving data with
bounded loss and delay
This is the resource
model you need
Quality
Need to frame the supply differently to make issues soluble
Bandwidth
‘Bandwidth’ is the presence of
something wanted
‘Quality’ is the absence of something unwanted
Loss and delay
Speed
RESOURCE MODEL?
How to use this quality-centric
What has to change?
NOW FUTURE
SUPPLY-PUSH
Selling commodity bandwidth
inputs
DEMAND-PULL
Selling differentiated
application outcomes
What has to change?
Focus on enabling outcomes not higher ‘speed’
Properly characterise your demand
Demand-driven model
COSTS
REVENUE
FLOWS
OUTCOMES
FIT-FOR-PURPOSE EXPERIENCE
MECHANISMS
TRANSMISSION
REQUIRES
ENABLES
TIN
SCHEDULING
Construct Matching Supply
Characterise Demand
Do this first…
…then do this
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
SUPPLY RESOURCE MODEL
A practical network
Example of a supply approach: Three layer model
Superior traffic costs more to deliver… so should attract a premium
Economy
Standard
Superior
Standard traffic is today’s off-peak Internet… but is consistently the same
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
Extend this to a five class model
• Provisioning capacity for total resilience is a real cost…
– …but not everyone needs it
– So we separate out resilient traffic from non-resilient
• When there is a period of network stress, some people may get reduced service…
– …but they still have connectivity
Economy
Sup
erio
r St
and
ard
Sup
erior
Stand
ard
Res
ilien
t
Five class model has rational economics
Sup
erio
r St
and
ard
Su
perio
r Stan
dard
Economy
Sup
erio
r St
and
ard
Sup
erior
Stand
ard
Economy
Sup
erio
r St
and
ard
Sup
erior
Stand
ard
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
We’ve got into a fight with the
mathematics of statistical
multiplexing
This is not negotiable
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
Dangerous myth: MORE SPEED IS ALWAYS BETTER
We’ve seen networks
where adding capacity made performance
get worse
! !
Broadband is becoming critical national infrastructure
Needs to be dependable No ice cream
(or insulin) without fridge-freezers, which need a reliable power supply
Advanced services need
predictable and dependable
supply
We are creating a digital society
Implicit social contract
We can’t externalise
our collective risks
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
