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Sam Samuel - Are we stuck in a Rut? The need for agressive research goals
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Sam Samuel - Are we stuck in a Rut? The need for agressive research goals

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  • Added figure on NPC evolution, including vectoring (estimate) Figure bottom left shows the NPC evolution where it is shown that by introducing vectoring on the VDSL2 lineboards (and having a next generation VDSL2 chipset) will enable a better NPC coefficient. Bottom right figure gives the numbers for a loop at 800 meter where the bubble shows the increase in bandwidth.

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  • 1. Are we stuck in a Rut? The need for aggressive research goals Sam Samuel iMinds 2010 – Bell Labs
  • 2. Are we stuck in a rut? How often do you see proposals for engineering research projects that say: “ We aim to improve/reduce X by 50%”
  • 3.
    • World is going green, need to reduce GHG
    • ICT network and data-traffic growth essential to social and economic progress and to low carbon economy
    • Innovations have kept network energy consumption in check
    • However innovation rate in key technologies is slowing: Moore’s law, fiber capacity, router capacity
    Huge opportunity to reinvent scalable networks that maximize energy-efficiency while reducing total-cost-of-ownership Sustainable Network Growth & Low Carbon Economy 2007: ICT contributes 2% to global GHG Enabling a Low Carbon Economy 2020: ICT can offset 5X its own carbon footprint E-Health Smart Buildings Smart Transportation Smart Communities Smart Grids
  • 4. Bell Labs Traffic Projections for North America Data from : RHK, McKinsey-JPMorgan, AT&T, MINTS, Arbor, ALU, and Bell Labs Analysis : Linear regression on log(traffic growth rate) versus log(time) with Bayesian learning to compute uncertainty Energy Consumption Driven by Exponential Traffic Growth
    • Traffic Doubling every 2-3 years
    • Continuous increases in equipment unit-capacity used to keep network energy in check
    • Many technologies are slowing down
    Wireless Data Total Backbone Internet Video Wireless Voice P2P
  • 5. Slowdown in Technology
    • Reduction in dynamic dissipation of silicon with feature size, is slowing.
    • Capacity of single rack IP routers due to thermal density is saturating
    • Capacity of a single fiber transmission system saturating
    What do these slowdowns imply for energy efficiency of the entire network?
  • 6. Computing Network Energy Efficiency Trends: Start With Network Model Traffic transaction Can compute energy required to deliver any kind of traffic transaction on network Enterprise Fixed Access Access Switch Agg’n Switch Core Sw Firewall/ WAN Metro/Edge Network & VDN Metro Router Metro Router Ethernet Switch ROADM ROADM ROADM ROADM Ethernet Switch Ethernet Switch ROADM OTN Core Router Core Router Core Router Core Router Core Network ROADM ROADM OTN OTN OTN OTN ROADM ROADM IMS Telephony & Apps Core Integrated IMS MGC MGW Residential Fixed Access OLT OLT ONU DSLAM+ONU SPLT DSLAM ADSL+GWY VDSL+GWY Wireless Access & Core eNB (LTE) NodeB Data Data Voice Femto Fixed Access Back-Haul Secur. GW Back-Haul RNC S-GW SGSN GGSN P-GW NodeB CDMA MMC Pkt Sw Data OMP OMC MME
  • 7. Wireline-Network Energy Consumption Lower Bound
    • Network Properties
    • Connect every pair of users with “Shannon-capacity” fiber
    • Use least amount of switching at CMOS estimated-limit
    • Energy consumption only depends on size of transaction, not on installed capacity
    Framed question : What is minimum energy required to uniquely connect N users over long haul distances?
  • 8. Estimating Lower Energy Bounds for Wireline Networks
    • Minimum energy for single switch:
    • For CMOS
    • Switch to connect N users activates at least log 2 N stages
    • Assume ideal fiber transport: - perfect conversion efficiency - 3 dB noise figure amplifiers - operating at Shannon limit
    Comparing above to P2P transaction today, ~10W, we get the result that networks can be 10 8 more energy-efficient than today E sw E sw E sw E term E term f(L tr )E trans f’(L sw )E trsw f(L tr ) E trans f(L tr ) E trans Amplifier Amplifier f(L tr ) Amplifier E noise = N A hv E trans E noise = Ghv G G G f(L tr ) E rec
  • 9. Energy Consumption in Wireless Access Inherently more inefficient than wireline 10x (Typical macro BST: 10% of consumed power transmitted as RF Power) 10 17 x (Huge difference between transmitted power and minimal required receive power)
    • For energy-efficient wireless communication, focus on reducing need for high transmit power
    • Macro BSTs could be 10,000 more efficient that today
    • Higher efficiencies possible with small cells
  • 10. Analysis of Wireless Link Energy Efficiency Illustration Through Macro Cell of Radius 500m
    • Modeling Assumptions
    • Infinite BW
    • Antenna gain 14 dBi
    • Noise figure 9 dB
    • Bldg penetration 20 dB
    • Path-loss exponent 3.8
    • Shadow fading 8 dB std dev
    Shannon Limit R x ~ 10 -12 nJ/bit (Received energy per bit for single link in limit of zero spectral efficiency) Tx 10 0 nJ/bit Tx 10 2 nJ/bit Grid Power 10 6 nJ/bit Ideal Small Cells Radius ~ 50 m Ideal Macro Cells Radius ~ 500 m Simulation Result Opportunity ~10 4 path losses Opportunity ~10 MIMO ~10 Ant. Gain & Improved Rx Opportunity ~10 2 High BW T x = RF transmit pwr R x = RF receive pwr T x 10 -4 nJ/bit Tx 10 -2 nJ/bit Opportunity ~10 MIMO ~10 Ant. Gain & Improved Rx Residual Losses ~10 8 Tx 10 5 nJ/bit Actual Macro Cells Radius ~ 500 m Opportunity ~10 Efficient PAs, low power electronics, passive cooling, etc. Other ~ 10 margin for QoS, overheads, nonidealities, etc. Shannon Limit
    • Huge difference (17 orders of magnitude) between transmitted power and minimal required received power
    • Best ways to capitalize on above opportunity
      • Small Cells
      • Antenna gains (MIMO, etc.)
      • Increased bandwidth
  • 11. Innovating Ultra Low-Energy Networks is Super-Hard: Requires Global Consortium, Therefore
    • In real networks (mesh in the core, tree at the edges), dynamically allocate/switch a virtual fiber link between the two end-points of a transaction, with minimum routing
    • Bring antenna as close to user as economically feasible; design for high antenna gains; opportunistic use of high BW
    • Service aware and adaptive network with ultra-low energy information and content delivery
    • Low Power, ultra-high energy efficiency, energy-follows load components everywhere
    Macro Base Station Small Base Stations
  • 12. Approach
    • Bottom Up Research Organization
    • Use of models to structure and guide research and collaboration
    • Combine resources to innovate & demonstrate new network architectures & technologies
    • Funding through member & external contributions
    • Measure, model and predict energy consumption in ICT networks
    • Gauge impact of innovations on:
    • Alternative metrics (carbon footprint, network power, embedded energy)
    • Adjacent technologies (data centers, handsets)
  • 13.
    • Stretch goal that forces us to rethink every part and aspect of the network, setting us on an innovation path that focuses on long-term network sustainability
    • Unimpeded traffic growth could be 1000x in 20 years
    • Goal is well under theoretical limits
    : Ambitious Goal of 1000x Circuit Design Network Architectures Advanced Coding Protocols Transport
  • 14. GreenTouch 5 year Goal: Element efficiency demonstration targets for 2015 Overall network efficiency target in 2020 (Mbps/W) 50X 10X 100X 400X Network efficiency depends upon network architecture and technology, which depends upon services, applications, and traffic Path to 1000x Not Unique: Innovations Beyond Business as Usual
  • 15. : Path to 1000x
    • Path to 1000x improvement not unique , but requires aggressive improvements and new architectures
    • One scenario:
      • ~3000x improvement in wireless through small cells, MIMO, active antennas, efficient transceivers, etc.
      • ~1200x improvement in routing & switching with architectures with fewer routers and switches, low power electronics, low power interconnect, reduced processing, power-efficient protocols, minimum size buffers, etc.
      • ~50x improvement in optical transmission with energy efficient components and systems, optical restoration, passive cooling, etc.
      • ~25x improvement in broadband access from dramatic reductions in CPE power (from 11.1 W to 0.4 W) and CO power (from 0.6W/port to 0.1W/port)
    • Bell Labs GreenTouch focus on research where:
      • Improvement opportunity is immense
      • Collaboration is essential
      • Research in pre-competitive stage
  • 16. Approaches to GreenRadio Network Architecture
    • Base Station Hardware (10x)
      • Photonic Enablers for RF Systems (10x)
      • High Efficiency RF-Power Amplifiers (3x)
      • Renewable Energy Powering
    • Green Air Interface (1000x)
      • Small Cells (100x)
      • Large Scale MIMO (10-100x)
      • Very High Bandwidth (100x)
    • Network Architecture & Mgmt
      • Dynamic Management for EE
      • New BS Architecture – Cloud Computing for Signal Processing
    RN eNB
  • 17. Summary
    • The problem may overtake us unless we choose to think differently
    • We are well above the theoretical limits nothing is stopping us from aiming for aggressive goals
    • The need for sustainable, yet rapid growth of ICT networks, offers great opportunities for spectacular research in improving network energy-efficiency
    • GreenTouch is an example of consortium with aggressive goals that wants to address this big problem collaboratively
    • We need your collaboration for GreenTouch to reach its goals!