Se ha denunciado esta presentación.
Utilizamos tu perfil de LinkedIn y tus datos de actividad para personalizar los anuncios y mostrarte publicidad más relevante. Puedes cambiar tus preferencias de publicidad en cualquier momento.

Future of Broadband workshop presentation - ITU Telecom World 2013

15.925 visualizaciones

Publicado el

Is "bandwidth" the right resource model for broadband? This presentation suggests that the telecoms industry is in a death spiral because it has fundamentally misunderstood the nature of the resource it offers. In its place it offers a "quality" model that has the properties we desire, and enables us to properly match supply to demand.

Publicado en: Empresariales, Tecnología
  • Sé el primero en comentar

Future of Broadband workshop presentation - ITU Telecom World 2013

  1. 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. 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. 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. 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. 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. 6. The whole market is ADDICTED TO PEAK SPEED
  7. 7. Selling data speed and mechanisms A proxy for ‘more speed’
  8. 8. Pressure from regulatory environment for speed SPEED!
  9. 9. League tables for speed Incentives matter and everyone gets incentivised to deliver more speed
  10. 10. Speed is not the only THING THAT MATTERS
  11. 11. Example: Satellite in Asia-Pacific SERVICE A SERVICE B < 1Mbit > 6Mbit Which is better?
  12. 12. Service A: Low variability
  13. 13. Service B: High variability Same satellite, same location, similar time, different service
  14. 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. 15. This is a common issue to ALL BROADBAND DELIVERY Was this just a one-off issue? No.
  16. 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. 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. 18. What network attributes drive GOOD USER EXPERIENCE?
  19. 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. 20. Different speeds & characteristics SLOW & LOW VARIABILITY OF LOSS/DELAY   Good Experience Bad Experience VERY FAST & VARIABLE DELAY  FAST & VARIABLE LOSS
  21. 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. 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. 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 ! !
  24. 24. What network attributes DRIVE COST?
  25. 25. Valid reasons for spending capex • More customers  More revenue • Increased usage  More revenue • Regulatory requirement
  26. 26. Invalid reason for spending capex Premature infrastructure and capacity upgrades
  27. 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. 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. 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. 30. Telecoms is a capital killer As an industry, we’re not covering our cost of capital Something is very badly wrong Source: PwC
  31. 31. What drives the PREMATURE UPGRADES?
  32. 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. 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. 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. 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. 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. 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. 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. 39. How to re-frame the RESOURCE PROBLEM?
  40. 40. Delay (and loss) have a structure Delay is due to… G S V Geography Serialisation speed Variability
  41. 41. Why trust in increasing speed is now misplaced The speed of light is not changing G Pre-IP Early IP Now Geography
  42. 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. 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. 44. The commercial challenge: How to break the investment cycle of doom?
  45. 45. The technical challenge: How to measure, manipulate and manage ‘V’?
  46. 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. 47. Networks are ‘trading spaces’ How ‘V’ is distributed among competing streams is how demand is matched to the supply
  48. 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. 49. Quality of experience The real difference between telecoms heaven and hell IDEAL SCHEDULING HIGH LOW TODAY! LOW HIGH Resource efficiency
  50. 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. 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. 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. 53. TWO fundamental resource limits Schedulability demand HIGH Infeasible Feasible In practise we aren’t nearly that good LOW LOW HIGH Capacity demand
  54. 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. 55. Our problem Schedulability demand is growing fast VoIP, gaming, 2-way video, UC, HTML5 web…
  56. 56. The problem Solving schedulability issues (i.e. non-stationarity) with capacity is inefficient and ineffective
  57. 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. 58. Is the path to heaven TECHNICALLY ACHIEVABLE? Yes
  59. 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. 60. What is the right RESOURCE MODEL?
  61. 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. 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. 63. How to use this quality-centric RESOURCE MODEL?
  64. 64. What has to change? NOW FUTURE SUPPLY-PUSH DEMAND-PULL Selling commodity bandwidth inputs Selling differentiated application outcomes
  65. 65. What has to change? Focus on enabling outcomes not higher ‘speed’ Properly characterise your demand Demanddriven model
  67. 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. 68. A practical network SUPPLY RESOURCE MODEL
  69. 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. 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. 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. 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. 74. Why so? Demand is not being met Supply-push business and technology model
  75. 75. Why so? Wrong kind of supply Failure to align with underlying and unchanging reality of packet networking
  76. 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. 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. 78. We are creating a digital society We can’t externalise our collective risks Implicit social contract
  79. 79. Keep getting scheduling wrong: Crisis of legitimacy Angry: Customers Investors Regulators Governments
  80. 80. Get scheduling right: Golden age of broadband 1890s Railways 1920s Electricity 1960s Oil 2020s Broadband
  82. 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. 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. 84. To learn more Free Future of Communications newsletter: Follow Martin Geddes on Twitter: @martingeddes Other presentations: White papers on network performance:
  85. 85. PREDICTABLE NETWORK SOLUTIONS Neil Davies Martin Geddes