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Addicted to speed: Why broadband service providers need a ‘healthier lifestyle’

The document discusses the need for broadband service providers to adopt a 'healthier lifestyle' to escape the cycle of speed accumulation that leads to diminishing Quality of Experience (QoE) and increasing operational costs. It emphasizes that traditional models focused on increasing bandwidth are ineffective and proposes a shift towards more efficient scheduling and differentiated service delivery. By measuring QoE and planning capacity to align with customer needs, significant improvements in service quality and cost management can be achieved.

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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