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Network science (NS): hype or reality?

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Network science (NS): hype or reality?. Chuanxiong Guo Microsoft Research Asia September 24, 2009. Definition. Science (Wikipedia) Any systematic knowledge-base or prescriptive practice that is capable of resulting in a prediction or predictable type of outcome - PowerPoint PPT Presentation
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1 Network science (NS): hype or reality? Chuanxiong Guo Microsoft Research Asia September 24, 2009
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Page 1: Network science (NS): hype or reality?

1

Network science (NS): hype or reality?

Chuanxiong GuoMicrosoft Research Asia

September 24, 2009

Page 2: Network science (NS): hype or reality?

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Definition

• Science (Wikipedia)– Any systematic knowledge-base or prescriptive

practice that is capable of resulting in a prediction or predictable type of outcome

• Network Science (the “Network Science” book)– The study of network representations of physical,

biological, and social phenomena leading to predictive models of these phenomena

Page 3: Network science (NS): hype or reality?

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Predictability• Internet collapse in 1980s

– TCP congestion control• Network expansion

– 32-bit IPv4 address and 16-bit AS number– Will IPv6 takeover?

• Network security – DDos, virus, worm, and spam

• Network traffic and topology– Self similarity, power law

• Network applications– Web

Page 4: Network science (NS): hype or reality?

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Networking research: An engineering perspective

• Classical networking topics– Network architecture/protocol/applications– Multiple access– Packet scheduling/switching/routing– congestion control, traffic engineering/measurement,

resource management• New technology trends, user requirement,

economics of scale– P2p, sensor networks, network security, data center

networking, social networking

Page 5: Network science (NS): hype or reality?

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The emerging of network science

• Inter-disciplinary – Physicist, mathematician, sociologist, information

theorist, computer scientist, economist (?)• Data-driven discovery

Page 6: Network science (NS): hype or reality?

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Data–driven discovery

• Spam and botnet detection– Spamming Botnets [Xie08-sigcomm]– Spamalytics [Kanich08-ccs]

• Network diagnostics, profiling – [Ionut08-sigcomm, Kandula08-sigcomm]

• Online social networking– [Mislove07-IMC, Nazir08-IMC]

Page 7: Network science (NS): hype or reality?

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Data-driven discovery: system infrastructure

• Build large scale computing infrastructure for researchers from different disciplines – Scalable data center systems and networks (NSF

CLuE program)– Dryad, Hadoop– DryadLinQ, MapReduce

• Data, data, data!– Accumulation and open access

Page 8: Network science (NS): hype or reality?

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What role can the wireless network and mobile computing community play?

• Mobile data services– Recent advances in smart-phones – Access bandwidth

• Mobility patterns– [Gonzalez08-nature, Lee09-infocom]– [Wang09-ScienceExpress]

• Mobile communication networks– [Palla07-nature, Seshadri08-kdd]

Page 9: Network science (NS): hype or reality?

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Wang-Sciencexpress09 Understanding the Spreading Patterns of Mobile Phone Viruses

Page 10: Network science (NS): hype or reality?

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Summary• Networking research currently is mainly an

engineering field– With research problems generated directly from real

world– “We believe in rough consensus and running code“– David

Clark • Bridging engineering and network science

– Data-driven discovery– New models and insights from the broader science

community– More predictable designs

Page 11: Network science (NS): hype or reality?

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Network Science

Network Engineering

tools

Data (and

problem)

Infrastructure


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