1 network science (ns): hype or reality? chuanxiong guo microsoft research asia september 24, 2009
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Network science (NS): hype or reality?
Chuanxiong GuoMicrosoft Research Asia
September 24, 2009
![Page 2: 1 Network science (NS): hype or reality? Chuanxiong Guo Microsoft Research Asia September 24, 2009](https://reader030.vdocuments.net/reader030/viewer/2022032800/56649d4d5503460f94a2b5fc/html5/thumbnails/2.jpg)
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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
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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
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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
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The emerging of network science
• Inter-disciplinary – Physicist, mathematician, sociologist, information
theorist, computer scientist, economist (?)• Data-driven discovery
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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]
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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
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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]
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Wang-Sciencexpress09 Understanding the Spreading Patterns of Mobile Phone Viruses
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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
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Network Science
Network Engineering
tools
Data (and
problem)
Infrastructure