Advanced Network Managementcourse#: 80240663

Spring 2015Instructor: Dan Pei

peidan@tsinghua.edu.cn

Teaching Assistant: Ruming Tang trm14@mails.tsinghua.edu.cn

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How to pronounce “Pei”?

Louvre MuseumI-M Pei: the famous architect who designed the glass pyramid

Just pronounce “Pei” as “Pay”

In fact, just call me “Dan”

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About the Instructor• Associate Professor. Joined Tsinghua CS Department in December 2012, with

Government Endorsement (“ Recruitment Program of Global Talents”) Homepage: http://netman.cs.tsinghua.edu.cn/~peidan

• Previously at AT&T Research, worked on Management of 3G, WiFi, CDN, IPTV, DSL,Backbone networks and services such as Baidu.com. 50+ Papers, 18 issued US Patents

• Supervised interns from CMU, Cornell, Princeton, UCLA, GaTech, Michigan, Northwestern etc. Now @ Google, MSR, IBM, Bell Labs, Ohio State, Northeastern, HKUST etc. Currently supervising a dozen of Ph.D. students at THU

• Current research focus: Network Management for Mobile Internet

• Research Methodology: solve Real problem, build Real systems, process Real data with Big Data analytics.

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Course Requirements• Goal: learn how to solve real network management

problems

http://netman.cs.tsinghua.edu.cn/~peidan/ANM

• Encourage interaction and discussion --- stop me and ask questions at any time!

• Most Importantly, enjoy the class!

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Course Info• Time: Wednesday 9:50am-12:15pm

– Session 1: Network Management Fundamentals• Network Basics, Tools, Techniques

– Sessions 2 &3: Case Studies based on Conference Papers

• Office Hours: – Advise on your course projects. – By appointments, preferably during Thursday 2pm-

4:30pm.

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What do you expect to learn (I): Networks & Services

• Targeted Services: Web-based Services such as search engine, online shopping and social networking; Video Streaming Services.

• Targeted Networks: Enterprise WiFi Network, Residential WiFi &Broadband Networks, Cellular Networks, and Data Center Networks.

• Targeted Devices: Smart Phones.

Enterprise WiFi Network s

Backbone

Data center

APController

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What’s “Network Management”?

• A network management system utilizes real data to impact how network runs, but does not need to change existing software on vendor/user devices.

• It’s BIG DATA analytics with feedback loop!

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Goals of Network & Service Management

– what happened in the past can be reconstructed automatically and accurately

– What’s going on now can be detected/inferred accurately to trigger automatic mitigation

– what will happen in the future can be predicted with some confidence

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What do you expect to learn (II)?Network Management Areas

• Measurement

• Anomaly detection

• Diagnosis

• Mitigation.

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What do you expect to learn (III)?Techniques

• Time series analysis

• Association rule mining

• Machine learning

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Enterprise WiFi Network s

Backbone

Data center

APController

This year’s focus:Managing The Performance of Mobile Internet

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HTTP and Video Streaming Services

• Search Response Time [SIGCOMM 2013]

• Web QoE modeling [Mobicom 2014]

• Demystifying Web Page Load Time

• QoE model for video streaming [SIGCOMM 2013]

• Opprentince: automatic anomaly detection for Search Service

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Home Networking

• Broadband Performance Measurement [Sigcomm2011]

• Performance Improvement [IMC2013]• What’s going on? [IMC2013]• Residential WiFi Interference [RxIP]• Residential WiFi Measurement [WiSe]• WiFi Union

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Enterprise WiFi

• Campus WiFi measurement[Dartmouth]

• Campus WiFi troubleshooting [UCSD]• Inferring interference in Enterprise

WIFI [PIE]• Mobility Support in WiFi [SensorHints]

Smart Phones• Radio Resource on Smart Phone

– Radio Resource Allocation [ARO]– Periodical Transfers– Screen-Off Traffic

• Measurement from your smart phones– Crowdsourcing & Performance Monitoring [3GTest]– Realtime performance forecasting [PROTEUS]

• Caching on smart phone? [Ideal vs Reality]

• WiFi Tethering[DozyAP]

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Cellular

• Carrier Measurement Methodologies– Throughput [Throughput Index]– Delay [TTFB]

• Content Caching– What to cache? [OTT video]– What caching technology? [MonBot]

• Accounting– Used Traffic Volume = Charged Traffic

Volume?

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Data Center

• Failures– Measurement [SIGCOMM 2011]– Analyzing trouble tickets [NetSieve, NSDI

2013]– Service Impact [SoCC 2013]

• Traffic & Performance– Nature of Traffic [IMC 2009]– Traffic Characteristics [IMC 2010]

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Course Projects• A project of team of one or two students.

• The course will provide a few suggested project topics, but the project team can choose their own.

• The instructor will interact with each project team regularly to help them pick project topic, and finish the project.

• Each Project will have one mentor (one of my Ph.D. students).

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Enterprise WiFi Network s

Backbone

Data center

APController

A glance at my research projects:Managing The Performance of Mobile Internet

How Much Are Your Neighbors Interfering with Your WiFi Web Experience?

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Web Search

VoIPIM(WeChat,InstaMag) Social Media: Twitter,Weibo

500msdelay causes 1.2% decrease in Bing revenue[souders 2009]

Every Millisecond Counts!

400msdelay causes 0.74% decrease in Google searches[Brutlag 2009]

100msdelay causes 1% decrease in Amazon revenue[Linden 2013]

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Wi-Fi Hop Latency

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Wi-Fi Hop Latency

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Anomaly Detection

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Top-down Project Approaches:

• Top-down: start with the problem YOU want to solve.

• Your ideas? – Start with your pains when you using mobile

Internet, e.g., in Tsinghua Campus.

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Suggested Project Ideas (I)• WiFi Security Scan: builds an App which scans the currently

connected WiFi network to see whether it is secure (e-payment, login, browsing etc, and find the security holes of the AP (server probe the AP) )– Based on encryption protocols

– Can you login using the factory default account/password (e.g., admin/admin)?

– Can you login from the WAN interface? Other security holes

• Measurement results• Suggest security fixes

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Suggested Project Ideas (II)

• We already have an OpenWrt-based tool which measures the wireless interference between neighboring APs.

• Build an APP which can visualize and analyze the results from the above tool.

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Suggested Project Ideas (III)

• Build a real-time heat map for the Campus WiFi.

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Suggested Project Ideas (IV)

• We have the rough location information for each device every 3 minutes.

• Build a mobility model based on Campus WiFi data– Movement frequency distribution– Inter-movement time distribution– Migration Pattern

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Suggested Project Ideas (V)

• Anomaly Detection Based on WiFi Usage data

• Detecting abnormal behavior by applying some existing anomaly detection algorithms (with existing implementation code)

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Suggested Project Ideas (VI)

Build an idiot-proof Android App which can administrate an OpenWRT based router.

Some sample code:https://forum.openwrt.org/viewtopic.php?id=35574