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Waseda GITS Nakazato lab

Evolution in Coming 10 Years: What's the Future of Network? - Big Data- Big Changes in the Network. Waseda GITS Nakazato lab. WangHuan. 2013 2 nd Oct. Outline. Big Data Introduction Characteristics of Big Data Challenges Big Data Transmission Network Big Data Network Future Q/A.

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Waseda GITS Nakazato lab

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  1. Evolution in Coming 10 Years: What's the Future of Network?-Big Data- Big Changes in the Network Waseda GITS Nakazato lab WangHuan 2013 2nd Oct

  2. Outline • Big Data Introduction • Characteristics of Big Data • Challenges • Big Data Transmission Network • Big Data Network Future • Q/A

  3. Who’s Generating Big Data • The progress and innovation is no longer hindered by the ability to collect data • But, by the ability to manage, analyze, summarize, visualize, and discover knowledge from the collected data in a timely manner and in a scalable fashion Mobile devices (tracking all objects all the time) Social media and networks (all of us are generating data) Scientific instruments (collecting all sorts of data) Sensor technology and networks (measuring all kinds of data)

  4. How much data? • Google processes 20 PB a day (2008) • Wayback Machine has 3 PB + 100 TB/month (3/2009) • Facebook has 2.5 PB of user data + 15 TB/day (4/2009) • eBay has 6.5 PB of user data + 50 TB/day (5/2009) • CERN’s Large Hydron Collider (LHC) generates 15 PB a year 640Kought to be enough for anybody.

  5. Characteristics of Big Data: 1-Scale (Volume) • Data Volume • 44x increase from 2009 2020 • From 0.8 zettabytes to 35zb • Data volume is increasing exponentially Exponential increase in collected/generated data

  6. Characteristics of Big Data: 2-Complexity (Varity) • Various formats, types, and structures • Text, numerical, images, audio, video, sequences, time series, social media data, multi-dim arrays, etc… • Static data vs. streaming data • A single application can be generating/collecting many types of data To extract knowledge all these types of data need to linked together

  7. Characteristics of Big Data: 3-Speed (Velocity) • Data is begin generated fast and need to be processed fast • Online Data Analytics • Late decisions  missing opportunities • Examples • E-Promotions: Based on your current location, your purchase history, what you like  send promotions right now for store next to you • Healthcare monitoring: sensors monitoring your activities and body  any abnormal measurements require immediate reaction

  8. Challenges How to transfer Big Data?

  9. Big Data Transmission • Data transmission with high-value-per-bit • SONET/SDH (Synchronous Optical Network) • Lower-cost-per bit technologies • Carrier Ethernet. • Networking switching is moving rapidly to 10-40 Gbps • Big data requires big networks.

  10. Big Data- Network • However Ethernet on its own is not sufficient to handle the torrent of Big Data. • Network architectures also need to change to become flatter and more flexible. • Basic idea: • Push computing to data, not pushing data to computing.

  11. Limitations of Current Networks Switches

  12. Limitations of Current Networks • Old ways to configure a network Operating System App App App Specialized Packet Forwarding Hardware Operating System App App App Specialized Packet Forwarding Hardware Operating System App App App Specialized Packet Forwarding Hardware Operating System App App App Specialized Packet Forwarding Hardware Operating System App App App Specialized Packet Forwarding Hardware

  13. An OS for Networks Protocols Protocols • Towards an Operating System for Networks Software-Defined Networking (SDN) Control Programs Global Network View Network Operating System Control via forwarding interface

  14. Q & A Thank You for your attention! Q/A

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