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Networks for An Infinite Service Future


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ICTON 2019 France Keynote Presentation

Only 50 years ago network design was dominated by well defined, characterised, and understood services, but the launch of mobile services in the 1980s brought that era of certainty and stability to a rapid close. Not only where mobile users different in their habits, they discovered TXT! At almost the same time the internet and dial-up modems were introduced, and these compounded the situation further. Since that time network designers have been largely guessing as to what services they should accommodate and when.

The real culprits of chaos here are accelerating technologies and the new services they engender. For example: Facebook did not exist 15 years ago; WhatsApp 10 years ago; Snapchat 8 Years ago; whilst Video/Audio downloading and streaming were not mainstream just 3 years ago. And waiting in the wings we have the IoT and AI services. Needless to say most networks and network designers will continue to be wrong footed by the pace of change!

Published in: Engineering
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Networks for An Infinite Service Future

  1. 1. Networks for an Infinite Service Future Peter Cochrane and Mohamed Abdel-Maguid
  2. 2. n e t w o r k s to C o m e What will they look like , can we design them? Today we have partial design Steered by EMERGENT demand complexity AND Behaviours Followed by lots of patches Network and system testing is limited / impossible performance is not assured we are guessing more and more Can we do better and Can we second Guess The nets to come
  3. 3. C o m m e r c i a l D r i v e r s Top IT copies that caused massive net demand/change Modest Traffic change and Demand
  4. 4. C o m m e r c i a l D r i v e r s Top IT copies that caused massive net demand/change Device / Customer Driven net design who/what is the next apple and the next iPhone Rapid Device / Customer Driven net design who/what is the next apple and the next iPhone
  5. 5. B I G G ES T G A M E C H A N G E R S S u p e r C o m p u t e r p o w e r, b r o w s e r & a p p s i n h a n d iPhone 4 & Beyond Cray II Super Computer
  6. 6. C a u s a l i t y Sporadic mobile working The office is whereyou happen to be PEOPLE/DEVICE HABITS DRIVE NETWORK DEMAND The Stochastic nature of demand shapes net design The nature of WORK and working changed FOREVER
  7. 7. People to AI AI to AI AI to People Analogue/ DIGITAL Demand impossible to predict A I A S A S E RV I C E Another big game changer to come People to machine Machine to Machine Machine to People Sociology of People Ai / People Sociology of AI
  8. 8. Digital Computers required to filter out correct answers Quantum Computing is Analogue not digital Q u a n t u m C o m p u t i n g P o s s i b l y t h e b i g g e s t g a m e c h a n g e r e v e r ? Potential network demands beyond our ability to predict A future tool for net simulation and design
  9. 9. Q C R e a l i t y A t e c h n o l o g y i n d o u b t Q u a n t u m C o m p u t i n g successes tend to be modest and very hard won! It is not at all clear when and if we will get w o r k i n g p r o d u c t s o f significant power. To date QCs have yet t o o v e r t a k e t h e i r d i g i t a l f o r e b e a r s i n a n y s i g n i f i c a n t calculation space!
  10. 10. Q C D R E A M A b i g t e c h m i r a c l e Quantum AI ? New machine-machine paradigms New human-machine paradigms Designing beyond human abilty Deep analysis and prediction Widespread global influence New nets/protocols evolve +++++
  11. 11. ! C O M B I N A T O R I C S More states than atoms in the universe
  12. 12. ! I n t e g r at e d 3D Printed and Puncture Free Integrated Wheel, Brakes, Electric Motor, Sensors & Active Suspension All fully instrumented and monitored components providing safety and control feedback
  13. 13. IoT EXEMPLAR Wired/Wireless sensor net All critical components are monitored for wear and performance - to communicate with on and off board analysis No sensor communicates beyond the internal net - a centra hub collects data and communicates direct to the pits continuously Stochastic states continual reporting
  14. 14. our cars are next Wired/Wireless sensor net Stochastic states and reporting Sensors do not communicate beyond internal net - a centra hub analyses data and communicates sporadically with service centre/s
  15. 15. IoT Challenge A Faraday Cage of shielding Direct container to shore fundamentally impossible Randomised container-to-container mesh networks can do the job at very low energy and cost throughout this Faraday Cage of stacked containers A battery life >10 years required
  16. 16. Direct content of boxes, or direct box to 3/4/5G fundamentally impossible Randomised content-to-content-to-box and on to pallet-to-pallet-to-container networks can do the job! IoT Challenge A Faraday Cage of shielding A battery life >1 year required
  17. 17. vehicle to vehicle W i re l e s s , a c o u s t i c , o p t i c a l s e n s o r s Communication V2V >> 5G Designated Vehicle/s can act as 5G core hub/s Stochastic states and reporting
  18. 18. Linked PRODUCTS Monitoring the in:out and effect… Stochastic states and reporting
  19. 19. Data Storage Dynamic and non-uniform
  20. 20. PRODUCT System NetS Traditional design methodologies migrating to evolution Old order embraced optimisation and is now unfit for purpose The New Order Evolutionary: realising adaptability & resilience through inefficiency; what works and is good enough!
  21. 21. Clustered NETs Dynamic focused mesh forms? Clustered by applications & users; convenience; and/or nearest resource, and connect point+++ Modelling average patterns and behaviours possible, but the extremes and actual distributions most likely to be impossible W E HAVE NO A-PRIORI EXPERIENCE
  22. 22. E m e r g e n t N E Ts Dynamic multiple mesh forms?
  23. 23. SEGUAY To: Axioms Intelligence must have some form of input and an output Memory & processing power are not always essential Communication and connection are essentials Things that think want to link Tenets Intelligence is an emergent property of complex systems Not all complex systems exhibit intelligence Intelligence always involves communication All intelligences are entropic AI always seeks the truth
  24. 24. 5 TYPE 1 Reactive Task Specific Very Limited Largely Pattern Matching Human Programmers: Chess, cards, dominoes data, speech, pictures, characters, behaviours, movements+ Narrow Cognition Largely Programmed by AI alone: Subsume the networked knowledge of previous and current generations TYPE 3 Reasoning Multi-Task Ability Broadly Applicable TYPE 2 Learning Task Specific Broadly Applicable Memory and Analysis Initial Human AI Program That Then Adapts: Recognises highly complex/ large scale non-linear relationships A I L A D D E R Progress & Categories Full Awareness May be categorised as a ‘being’: With a wide range of sensory units networked to other machines TYPE 4 Self-Aware ~ 70yrs to become a solid & deployable technology 2027 Robotic embodiment, extensive sensors & actuators plus entity networking rapidly raises the game 2017 Google Alpha GO p r o p e l s A I i n t o a n autonomous future of learning & doing 2024 AI-Human cooperation see exponential innovation & progress of AI capabilities
  25. 25. A I - VAST C H O I C E Most are emerging from IoT modelling A ‘zoo’ of AI Neural Network configurations have been ‘established’ by ‘near optimised’ apps created over the past 70 years…
  26. 26. Actuator A Processor P1 Memory M Processor P2 Sensors S T T System Environs S i m p l e A n i m a l Assuming a simple model of this form
  27. 27. Ic ~ k log2[1 + K.A.S ( 1 + P.M )] S = Sensor, A = Actuator, P = Processor, M = Memory Followed by analysis and some math juggling, normalisation, and engineering licence… …resulted in this descriptor for Comparative Intelligence:-
  28. 28. 1960 70 80 90 2000 10 ComputingPowerMIP/s Intelligence Level PC Pundit Estimates of Artificial Intelligence Compared to Biology Internet R i s e o f I n t e l l i g e n c e Our Estimate = Ic ~ k log2[1 + K.A.S ( 1 + P.M )]
  29. 29. SEGUAY BACK: Suppositions Dynamic focused mesh forms? Chance local & general net synchrony highly likely Emergent local and general ‘AI - like’ highly probable Sensors add to the likelihood that some form of AI will occur We may see the rapid rise of machine decision dominance over humans Sociologies of things likely to manifest with invisible communications/agendas Dynamic topologies almost certain to eclipse most implementations by design We will no doubt observe, discover and learn a lot of new phenomena !
  30. 30. AXIOMS Testing our complex systems/networks is now fundamentally impossible We are continually wrong footed by customer & machine behaviours CyberSecurity has to be fully automated/pre-emptive, not reactive! Evolution and emergent behaviours have transcended engineering design Combinatorial complexity now outguns our ability to model and predict 5G will never be the dominant player that industry is promoting Most “things” on the IoT will never connect directly to the internet There is no spectrum crisis - only a very badly managed resource Bandwidth is free & we should exploit it to simplify our systems Energy use has to transcend the $$ as a primary design driver Future net topologies may be determined by AI and not us!
  31. 31. Energy 1: there is not enough energy on the planet to power > 250Bn things using 5G and cell sites infrastructures - and we have no credible battery solutions Energy 2: we have to get down to µW and nW with distances in the range 1 - 10m with battery lives up to10+ years Challenge Today the internet and all our devices cost ~ 10% of all the energy generated
  32. 32. scarcity illusion This is allocation and application and not usage or exploitation!
  33. 33. Visible waste We have no digital wireless systems - only analogue - with modems at each end ! All our design principles stem from the 1930/50s with big towers, long-range broadcast and communications for Millions and Millions of static users! It really is time to go all digital, for very short range, secure and very low power for Bns & Bns of mobile users & the IoT ! NOTICE ALL THE W ASTED SIGNAL SPACE
  34. 34. LAND OF PLENTY <00.1% of usage Natures Natural Filters To be exploited for signal processing, coding and energy reduction >99.9% of usage
  35. 35. Degrees of freedom S/N Frequency Time I = k.B.T.log2(1+kS/N) Invisible @ >10dB below the thermal noise Think information volume and not signal space ! The same information conveyed by different combinations of S/N , BW and Time
  36. 36. BW ~ 500MHz U W B -T O - H y p e r ( H W B ) All digital no analogue - mixers, amplifies, filters UWB HWB Hyper Wide Band BW ~ 50GHz Negates phase noise, oscillator stability, scattering, interference, reflections, improves security and link resilience… 1bit/Hz 0.01bit/Hz
  37. 37. Antennas: spanning huge frequency ranges are the engineering ideal. BUT this is a non-trivial problem…and whilst fractal antennas are the theoretical holy grail, no one has yet succeeded in realising bench mark designs Challenge
  38. 38. VACUUM All of this demands bigger and better core networks with more FTTT(ower), FTTP(remises), FTTH(ome), FTTR(oom) and all with far higher speeds. The exponential demand is not going to stop or slow down…it will most likely accelerate ! Politicians, Investors, Media, Mobile Industry still don’t get it! NET RESULT 5G Cannot Deliver
  39. 39. “The future is not exactly in our engineering hands… but it will emerge for sure” Thank You www.