The 20% Rule: How the seismic growth of data has always and will always outgrow telcom
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This a presentation I gave to Fog World Congress 2018 in San Francisco. It translates my findings from over 100 data sources and 40 years of historical data to show how data generation outpaces data movement (telcom) by 20% year over year. This will soon be published in a white paper.
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The 20% Rule: How the seismic growth of data has always and will always outgrow telcom
- 2. 40 Years of Data Generation and Communication in a Nutshell or Why the Edge/Fog is inevitable or The 20% Rule. Perry Lea Principal Technologist at Microsoft Co-Founder and Distinguished Technologist at Rumble
- 3. Topics Why the edge is required Worldwide capacity to move data Cost of data creation and transportation The economics of data generation Data generation and proliferation
- 4. Take Away Executive Summary • Edge computing is the natural state of computing and is inevitable. • The economics and trends suggest that the amount of data generated versus the ability to move data grows by 20% YoY
- 5. Sources of Data • Cisco VNI Study • Hilbert and Lopez Global Data Generation • Ethernet Alliance Telcom Capacity • IDC Data Generation Study • Public information from Intel, ARM, Nvidia, AMD, Seagate, Western Digital, and Micron. • Telcom Transit Database (historical and projected) by DrPeering. • FCC Federal Databases • Securities Exchange Commission • IBM Research • Federal Reserve Bank of St. Louis - Economic Database • World Economic Forum Database • Internet Trend Code Conference • The Economist • TSMC • NCTA • Dozens of other sources…
- 6. 40 years of data generation & communication
- 7. Data Generation versus Data Motion 1988 2018 Data Generation Data Movement
- 9. Factors Improving Data Generation Gordon Moore Intel - 1975 Chip density doubles every 18 months Robert Dennard IBM - 1974 As transistors get smaller, their power density stays constant. Each generation scales transistors by 0.7x in size and increases speed by 1.7x Jonathan Koomey Stanford - 2010 Performance per watt doubles every 1.57 years
- 10. There are exceptions.. • Dennard scaling has slowed down since 2016 • Moore’s law is now doubling transistor count every 24 months. • Software Bloat – Wirth’s Law 1998 2008 2018 Max Transistor Density 10M Intel Pentium II 2B Intel Itanium 20B AMD Ryzen Manufacturing Steps 200 400 1000 Node Size 130nm 28nm 7nm Max Frequency 450 MHz 1.8 GHz 3.6 GHz CAPEX $2B $29B $80B $10B to build new fab Density growth decreased Results in decreased yields and increased costs 5nm requires significant litho investment and quantum mitigation Clock frequency growth has flattened
- 13. Data Movement
- 14. Courtesy of Nielsen’s Group and Arris Corp)
- 16. Limits of Data MovementShannon Limit: Maximum data rate physically allowable
- 17. Costs of Data Motion Wired Wireless • Wired and wireless communication services and equipment cost have greater variability • The reduction in hardware and service cost has not followed Moore’s law (copper: -0.05%) (fiber: -1.39%) (wireless hardware: -3.4%) (wireless services: -4.8%)
- 18. Why Does Data Motion Lag Moores Law? Telcom CAPEX •Overhaul towers •Dig up roads •Lay wire Reluctance to buy bandwidth •Buy a faster computer •Buy more flash storage •Buy more bandwidth may or may not have an effect Service Cost •Bandwidth has always come with some form of recurring cost
- 19. Summary so Far • The cost to generate a bit of data << cost to transport data • Telcom services and hardware have not followed Moore’s law in reducing overall cost/transmitted bit
- 20. Data Growth
- 21. The Killer Apps & Data Generation
- 22. Global Data Generation and Capacity
- 23. Opportunities at the Edge
- 24. IoT Still Reaps the Rewards Printed Sensors$0.01 ARM Cortex M0 Polymeric
- 25. IoT Still Reaps the Rewards 1998 2018 Product Intel 80C51 Microchip SAMA5D2 CPU Single 8-bit ALU @ 33MHz 32-bit ARM A5 @ 500 MHZ with NEON Media Processing FPU Memory 64K addressable 4 GB DDR3/LPDDR3 IO Full Duplex UART, 32 GPIO 1024x768 LCD, 10/100 Ethernet, Two USB 2.0, SPI, CAN, UART, 2-wire, I2C, ADC, 128 GPIO Operating Systems None Linux and modern RTOS’ Die Size About 3000 transistors in 0.33mm2 About 20,000,000 transistors in 0.4 mm2 Power 0.11 mW/MHz 0.09 mW/MHz Performance About 3 MIPS 785 DMIPS Cost Roughly $4.00 in 1998 $3.97 in 2018 • Edge devices have room to absorb Moore’s advantages • Edge devices still enjoy Koomey’s scaling of power.
- 26. The “New” Edge Use Cases Data Aggregation Situational Awareness Geolocation Tracking Content Caching Gateway Services Edge Rules and AI Edge Security & Health Denaturing & FilteringLocal Control Systems
- 27. Edge Data in a 2010 World Courtesy Sandive Corp. Edge devices are data producers more-so than data consumers: • Device status • Unstructured data generation • Time series correlated data • 1Billion nodes Average Downstream Average Upstream 4G LTE 27.33 Mbps 8.63 Mbps 5G theoretical (mmWave) 20 Gbps 10 Gbps 5G realistic (mmWave) ~186 Mbps ~50Mbps DOCSIS 100.07 Mbps 33.58 Mbps
- 29. Edge Opportunities • Next wave of data next killer app • A single spigot to the cloud won’t work. The cloud must be localized • Latency effects need to be tempered for realtime control and streaming applications • SLA costs need to be mitigated
- 30. The 20% Rule 1 10 100 1000 10000 100000 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 WorldNetworkCapacity(EB/month) World Data Generated vs World Network Capacity Data Growth (EMC, UNECE & IDC Projection) EB/month Network Capacity Projected Growth (Cisco VNI) EB/month 126x 231x
- 31. About this Work Perry Lea Founder and Technologist for Rumble: www.rumblenow.com Advisor and Technologist for SimplyLEDs: www.simplyleds.com Author: “Internet of Things for Architects” Principal Technologist for Microsoft: www.microsoft.com Founder of Computational Vision: www.computationalvision.com
Editor's Notes
- The Hilbert and Lopez study for example draws in 40 years of data in various formats and medias. It considers not only digital data but analog, such as radio in the 1980s and newsprint. Today most data is digital, but we need to account for all types of data for an accurate study to measure data growth year over year.
- Much of the data reflects 40 years of aggregate data generation and communication. Printed material Radio Television Video Data communication Internet Traffic and Web Traffic Mobile Traffic Digitization and Digital Video Streaming
- We separate data generation from data transport. This is important Data generation represents the local creation of data. This could be human created or machine created data. It could be structured (databases and time correlated data) or unstructured (images and audio). It can even be analog or digital. Data Movement is the telecommunication and networking component to the equation. It considers local and wide area movement of data. From legacy wireline transport to MPLS systems to Intenert and cloud data. It may be Internet based or may not. Data motion takes physical components like coper or fiber cables as well as energy of transport. For the amount of data we are considering the costs and energy are overwhelming. As an anecdote, my past life was to find ways to resolves data motion in CPU design. Making CPUs and processors faster has reach their limits as we will see. A bulk of the time and energy is moving data. Not just between a sensor and a cloud datacenter, but even from an ALU and DRAM. Data movement has impact at all levels of computing.
- Dennard Scaling has slowed. Transistor counts still increase, but performance improvements are minimal. We are unable to increase clock frequencies any more without significant thermal issues. The trend is to add more silicon, hardware assist, and CPUs to a single die without increasing frequency. This leads to dark silicon. Moore’s law has also slowed. IT used to be doubling every 18 months. However expense and complexity in lithography and fabrication steps has made it prohibitively difficult to produce higher density chips at good yields for logic and memory components.
- Moore’s law has translated directly into end user cost. Price for storage, computing, and semiconductors has tracked Moore’s law well through 2010 Even as the cost of a single die has increased YoY, overall cost has followed the law.
- It is interesting to note that communication equipment follows a different curve in cost reductions YoY. Whereas data storage and logic costs have followed Moore’s law as transistor density increases, actual communication equipment has not followed the same curve.
- Nielsen’s Law of Broadband connectivity (Jakob Nielsen) is a good measure of overall communication bandwidth over time. It states that high end bandwidth grows at approximately 50% per year. It should be noted this is only downstream bandwidth. Upstream bandwidth has only increased by 30% YoY. This is 10% less than Moore’s law.
- Bandwidth costs and speed follow nearly the same slopes. Average bandwidth has slowed. This is partly due to technical limitations and hardware speeds, but also due to limitations in available spectrum and bandwidth that will have greater availability with 5G spectrum space.
- There are limits. The upper limit on data rate is found with Shannon’s limit. Any communications medium is characterized by signal and noise. Industry crams more data into a narrow slice of spectrum. You can use techniques like Raman amplification, larger constellations of OFDM, and better fiber-optic or wireless quality to improve SNR. These techniques are expensive to incorporate in a global telecommunication network.
- Wired costs follow material and commodity pricing of copper, metals, and fiber For example, between 2002 and 2008 the cost of copper soared from $0.50 per pound to $4.00 per pound.
- Data Movement has always lagged the growth of the rest of the IT industry. 5G for example will require new MIMO based towers, femto cell and small cell infrastructure, as well as new silicon.
- About every 5 years we have a set of technologies that allow us to create and store and transmit more content Web and Broadband MP3 and MP4 video compression and streaming Social media and digital photos HD, 4k and 8K resolution The current path puts us on course to produce 2.6 Zetabytes of data per year. IoT and edge computing will nearly double that to 4.3 ZB per year
- What we see if that during the early 2000’s telcom capacity grew as broadband became prevalent and affordable and technologies like cellular became mainstream. In a sense telcom finally could up to the IT revolution. Now telcom capacity is levelling off and the growth rates are no longer 50% YoY. We anticipate telcom capacity to grow at roughly 20% YoY. Even with the advent of mmWave spectrum, the growth will be capped. Data generation however continues to grow and find new uses cases of data generation. We anticipate between a 30% and 50% YoY growth in data generation. This leads to the gap…
- Sensor prices have fallen at a steeper slope than Moore’s law. When we approach .20 sensor devices consumer can support a “throwaway model”. This will happen with polymeric fasbrication as well as printable electronics.
- New use cases are generating the plethora of “mew” data. In particular, we have seen concentrated growth in: Filtering – removing of redundant or temporal data. To alleviate network pressure, bandwidth and service costs, edge devices are used to remove significant data. Most cases remove 98% of edge data. Control systems aren’t new. In fact they were the first connected things dating back to 1935 when the early US power grid managed power stations using “pilot wires”. Connecting Industry and Industry 4.0 has produced significant value by connecting brownfield devices. Situational awareness edge devices combine AI and geolocation to provide systems that can respond to events depending on time, space, distance, or cause. Data aggregation and caching provide the answer to latency issues at the edge. Content is cached and managed locally to avoid long hops.
- Whereas intenet bandwith for the last 20 years has been dominated by downstream data. IoT and edge devices will be content producers. It will demand greater upstream bandwidth and better latency. Cat0, Cat1 and Cat NB will help close some of the disparity between uplink and downlink speed but they are focused on low bandwidth use cases. Unstructured edge data still has significant hurdles.
- The bulk of modern Internet data is unstructured: Netflix, Facetime, Youtube, Skype A sizable amount remains structured or partially structured: Facebook and HTTP. This data will continue to grow, but at a steady rate, but the 1.7ZB of data will be edge created. Not all of it will (or can) move through our networks.
- YoY there continues to be a disparity between the amount of content being generated and the ability, financials, or need to move that data. More data is produced than absorbed. The average growth rate over the last 15 years has been 20% year over year. We predict this will continue to grow as Moore’s law still has a play space at the edge and in sensors, but service costs and data transmission will not follow the same curve.