CSC7290: Advanced Computer Networking. Hongwei Zhang http://www.cs.wayne.edu/~hzhang



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Transcription:

CSC7290: Advanced Computer Networking Hongwei Zhang http://www.cs.wayne.edu/~hzhang

Objectives of the course Ultimate goal: You become an expert in network and system design and analysis, which are fundamental tools in scientific and technological innovations Humble course objectives: To help students understand the foundational principles and techniques of network design and analysis To help students appreciate why networks have been designed as they are today To build up students' capability in enhancing the state of the art in computer networking Suppose we are building the Internet from scratch up: How to select among different solutions to a problem (e.g., routing, error control, congestion control)?

Topics to cover Prelude How to have a bad career in innovation/research General principles on systems development & research Performance evaluation techniques and their applications to computer networks Common mistakes and how to avoid them Selection of techniques and metrics Review of basic probability theory and statistics Experiment design and analysis Simulation Summarizing measured data Comparing systems using sample data Mathematical regression models

Optional topics: if time permits Stochastic models of computer networks and their applications Stochastic processes and queuing theory Applications to protocol and system analysis Formal models of distributed algorithms and their applications to network protocol analysis Network process: syntax and semantics Models and analysis of network processes: specification and proof techniques Applications to network protocol design and analysis Network optimization and control

Two major components of the course Lecture Focus on basic techniques and tools Project Applying the basic techniques and tools in real-world applications, especially in innovative, emerging networking technologies wireless and sensor networks Vehicular networks disruption tolerant networks These techniques apply to fields far beyond computer networking!

Textbooks Required: [R0] Raj Jain, The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling, John Wiley & Sons, Inc., 1991. (ISBN: 0471503363) [R1] Dimitri Bertsekas and Robert Gallager, Data Networks (2nd edition), Prentice Hall, 1992. (ISBN: 0132009161) Recommended references: [R2] Mohamed G. Gouda, Elements of Network Protocol Design (1st edition), John Wiley & Sons. (ISBN: 0471197440) [R3] Sheldon M. Ross, Introduction to Probability Models, 9th edition, Academic Press, 2006. (ISBN: 9780125980623) [R4] Robert G. Gallager, Discrete Stochastic Processes, Kluwer Academic Publishers, 1996. (ISBN: 0792395832) [R5] Thomas G. Robertazzi, Computer Networks and Systems: Queueing Theory and Performance Evaluation (3rd edition), Springer. (ISBN: 0387950370) [R6] Anurag Kumar, D. Manjunath, Joy Kuri, Communication Networking: An Analytical Approach, Morgan Kaufmann, 2004. (ISBN: 0124287514) [R7] Ravindra K. Ahuja, Thomas L. Magnanti, James B. Orlin, Network Flows: Theory, Algorithms, and Applications, Prentice Hall, 1993.

Logistics Class timings MW 3:00pm-4:20pm in 314 State Hall Office hours MW 4:30pm-5:30pm in 454 State Hall, or by appointment Teaching Assistant Mr. Tung Nguyen dx1908@wayne.edu Office hours Tuesdays & Thursdays: 5:00-6:00pm in 312 State Hall, or by appointment

Logistics (contd.) Prerequisites Basic knowledge of computer networks, for instance, materials covered in CSC6290 or equivalent Elementary probability theory, statistics, and mathematical logic Or consent of instructor. Course website http://www.cs.wayne.edu/~hzhang/courses/7290/7290.html

Logistics (contd.) Grading Class participation: 10% Randomized quiz: 10% Homework assignments: 45% Project: 35% Letter grades will be assigned based on performance relative to other students; A tentative grading scale: A: 93-100 A-: 90-92 B+: 85-89 B: 80-84 B-: 75-79 C+: 70-74 C: 65-69 C-: 60-64 F: 0-60

Randomized quiz A quiz question before (almost) every lecture session A student is asked to answer the question, and will be graded Each student will be asked twice on average in the whole semester; the best of your quiz scores is used for your grade in the randomize quiz category So, please review the lecture materials after each session!

Project Evaluate the performance and/or analyze the properties of selected protocols/systems in the following fields: Vehicular sensor networks Intra-vehicle sensing and control Inter-vehicle sensing and control Urban/participatory/opportunistic sensing via vehicles

Project (contd.) Sensor networks in Healthcare Engineering: structural health monitoring, factory automation & industrial control, etc. Homeland security and military Daily life: urban sensing, security monitoring Scientific study: environmental engineering, social sciences, etc. Can focus on issues such as MAC, routing, transport control, data storage and querying, and localization.

Wireless mobile networks in traffic control: real-time road traffic condition detection and control Auto safety: DSRC Homeland security Social networks Heterogeneous networks integrated wireless networks (sensor networks, WiFi, cellular) and the Internet etc. Networking technologies for emerging economies network properties: wireless, mobility, intermittent connectivity... network services: telemedicine, mobile banking, e-retailing, stored data and voice messaging, remote education, local content and news, security, policing, etc. Other topics of your choice (with conscent of instructor)

Project (contd.) Overview of an emerging networking technology --- Wireless Sensor Networks Opportunities Challenges in network/system design

Retrospect on computing & networking ENIAC: first computer (1945) Apple II: first successful PC (1977) Laptop, PDA (1979 -) First computer network (1969) Internet, wireless

? What if Ubiquitous Computing & Networking + Sensing & Control? Ubiquitous, fine-grained sensing & control

Sensor nodes A XSM sensor node (2004) 8MHz CPU, 4KB RAM, 128KB ROM Chipcon CC1000 radio: 19.2 kbps Infrared, acoustic, and magnetic sensors Sounder Many more (2001 - )

Wireless sensor networks: innovative ways of interacting with the world Science: ecology, seismology, oceanography Engineering: industrial automation, precision agriculture, structural monitoring Daily life: traffic control, health care, home security, disaster recovery, virtual tour

Tiny computers that constantly monitor ecosystems, buildings, and even human bodies could turn science on its head. Nature, March 2006 The use of sensornets throughout society could well dwarf previous milestones in information revolution. National Research Council report, 2001

Humidity vs. Time 101 104 109 110 111 Rel H um idity(% ) 95 85 75 65 55 45 35 Sensor networks of today Temperature vs. Time 33 28 23 18 13 8 7/7/03 9:40 7/7/03 13:41 7/7/03 17:43 7/7/03 21:45 8/7/03 1:47 8/7/03 5:49 8/7/03 9:51 8/7/03 13:53 8/7/03 17:55 8/7/03 21:57 9/7/03 1:59 9/7/03 6:01 9/7/03 10:03 Date Redwood ecophysiology Wind response of Golden Gate Bridge Intruder detection, classification, and tracking

ExScal Field project to study scalability of middleware and applications in sensornets Deployed in an area of ~1,300m 300m 2-tier architecture Lower tier: ~ 1,000 XSM, ~210 MICA2 sensor nodes (TinyOS) Higher tier: ~ 210 IEEE 802.11b Stargates (Linux) Base Station........................

Other sensornet projects/applications Healthcare Social networking Industrial control Precision agriculture Homeland security Ecosystem conservation

Healthcare Medical implant: artificial retina Assisted living: health monitoring & coordination Health-environment monitoring: air quality, noise, bio & chemical-agent

Social dynamics and networking

BikeNet: mobile sensing system for cyclist experience mapping Monitor cyclist performance/fitness: speed, distance traveled, calories burned, heart rate, galvanic skin response, etc Collect environmental data: pollution, allergen, noise, and terrain condition monitoring/mapping, etc

Vehicular sensor networks

Industrial control: Intel Semiconductor Factory monitoring Preventative equipment maintenance: monitoring vibration signals

Precision agriculture: smart vineyard monitor soil humidity, temperature, chemistry

Homeland security: BioWatch

TurtleNet: track wood-turtles the turtle came out of the water to sun itself for only brief periods and went back into the colder water

SealNet: use nature to help scientific study To measure ocean s temperature and salinity levels, as well as the seal s location and depth. Sensing data are collected for every dive; Each time the seals resurfaced to breathe, that data was relayed via satellite to certain data centers in US and France As the seals migrated and foraged for food during their winter journey, they circumnavigated the Antarctic continent and its continental shelf, diving down to 2,000 feet more than 60 times a day

New applications (e.g., SensorWeb (MSR), sensor-rich vehicular networks) and startups keep emerging A seamless cyber-physical world of intelligent computing and networking agents

Are sensornets mature enough to be readily used in practice? Each large scale project may well take 5 professors 10 PhDs 20 Master and undergraduate 40 labors A few months/years of hard work $$$

Challenges of sensornet design?!

Challenging aspects of sensor networks Dynamic, unreliable, and interference-prone wireless channels Reliable messaging 100 100 5.5 meters packet delivery rate (%) 80 60 40 20 0 0 2 4 6 8 10 12 14 distance (meter) packet delivery rate (%) 95 90 85 80 transitional region (unstable & unreliable) ( 2 secs) 75 0 50 100 150 200 250 300 time series Indoor testbed at OSU; 3 feet node separation 300 data points for each distance, with each data points representing the status of 100 broadcast transmissions

Challenging aspects of sensor networks Dynamic, unreliable, and interference-prone wireless channels Reliable messaging Resource constraints (e.g., bandwidth, energy, memory) Resource-efficient services, sensornet architecture 19.2 kbps 2 AA batteries 4KB RAM

Challenging aspects of sensor networks Dynamic, unreliable, and interference-prone wireless channels Reliable messaging Resource constraints (e.g., bandwidth, energy, memory) Resource-efficient services, sensornet architecture Application diversity (e.g., traffic patterns, QoS requirements) Application-adaptivity periodic data collection can tolerate certain data loss and delay infrequent aperiodic report of hazards need reliable and real-time report

Challenging aspects of sensor networks Dynamic, unreliable, and interference-prone wireless channels Reliable messaging Resource constraints (e.g., bandwidth, energy, memory) Resource-efficient services, sensornet architecture Application diversity (e.g., traffic patterns, QoS requirements) Application-adaptivity Complex faults and large system scale Dependability despite fault complexity and system scale Node/link failure, state corruption, system signal loss, malfunctioning sensor, etc Increased overall probability of fault occurrence Fault propagation

Challenging aspects of sensor networks Dynamic, unreliable, and interference-prone wireless channels Reliable messaging Resource constraints (e.g., bandwidth, energy, memory) Resource-efficient services, sensornet architecture Application diversity (e.g., traffic patterns, QoS requirements) Application-adaptivity Complex faults and large system scale Dependability despite fault complexity and system scale Heterogeneity Architecture and service provisioning in integrated systems

Challenging aspects of sensor networks Dynamic and potentially unreliable wireless channels Reliable messaging Resource constraints (e.g., bandwidth, energy, memory) Resource-efficient services Application diversity (e.g., traffic patterns, QoS requirements) Application-adaptivity Complex faults and large scale Dependability irrespective of scale Growing heterogeneity Architecture and service provisioning in integrated systems

Project (contd.) Rules Students are allowed to form groups in doing projects, but the number of students per group should be no more than 3 First choose one of the above technical fields and focus on a specific problem (e.g., routing) in your selected field Evaluate and analyze different solutions to your chosen problem Report your findings in a scientific manner Deliverables In-class presentation Written project report (in the form of a technical paper)

Project (contd.): related resources TinyOS TinyOS Community Forum, http://www.tinyos.net/ Phil Levis's book on TinyOS programming: http://csl.stanford.edu/%7epal/pubs/tinyos-programming.pdf TinyOS documentation: http://www.tinyos.net/tinyos-2.x/doc/ Resources on using TinyOS and motes: http://www.tinyos.net/scoop/special/support Network simulators: TOSSIM ns-2 qualnet/glomosim opnet

Project (contd.) Timeline Select the topic and form your project group by 01/31/2009 Submit your detail project plan and timeline by 02/28/2009 Submit slides for your presentation at least one day before your presentation (date to be decided) Submit your project report electronically by midnight 05/01/2009 Evaluation criteria Breadth and depth of your understanding of the problem, as evidenced by your project report and presentation Presentation quality (e.g., clarity, readability, and conciseness) of your talk and written report Whether or not you are able to stick to the project timeline

What is this course NOT for? Technology tutorial Instead, we focus foundational issues Network programming Assemble networks with switches, routers, firewalls, etc. Design websites I do not really want to learn anything new, just want to get the credits and a good grade

Policies Lecture attendance required Homework No late submission without prior permission No collaboration Frequently check out the course website for updated information Other university regulations apply

How to succeed in this course? Attend lectures Look at the big screen, NOT the small computer monitor Read books Work on homework and project Ask questions!!! Questions?

Student questionnaire Name (optional): E-mail (optional): Major: Degree/Expected Year: Previous coursework in computer networking: Previous coursework in probability theory, statistics, and mathematical logic: What do you expect to learn from this course? How do you think this course should be taught? How might this course contribute to your career objectives?