hongwei zhang hzhanghzhang/courses/7290b/lectures/00 - course plan.pdfinternet packet forwarding...

CSC7290: Advanced Computer Networking

Hongwei Zhang

http://www.cs.wayne.edu/~hzhang

Sprint US backbone network

Seattle

Atlanta

Chicago

Roachdale

Stockton

San Jose

Anaheim

Fort Worth

Orlando

Kansas City

CheyenneNew York

PennsaukenRelayWash. DC

Tacoma

…

to/from customers

peering

to/from backbone

…

.………

POP: point-of-presence

DS3 (45 Mbps)

OC3 (155 Mbps)

OC12 (622 Mbps)

OC48 (2.4 Gbps)

Q0: Why this (and not other) network topology?

Internet structure: network of networks

Tier 1 ISP

Tier 1 ISP

Tier 1 ISP

NAP

Tier-2 ISPTier-2 ISP

Tier-2 ISP Tier-2 ISP

Tier-2 ISP

localISPlocal

ISPlocalISP

localISP

localISP Tier 3

ISP

localISP

localISP

localISP

Q0’: Why this (and not other) network hierarchy?

Internet packet forwarding

Tier 1 ISP

Tier 1 ISP

Tier 1 ISP

NAP

Tier-2 ISPTier-2 ISP

Tier-2 ISP Tier-2 ISP

Tier-2 ISP

localISPlocal

ISPlocalISP

localISP

localISP Tier 3

ISP

localISP

localISP

localISP

Q1: Why this (and not other) end-to-end path?

Internet routing

Q1’: Given a network topology and a routing protocol, how is link weight decided?

Recurring questions in emerging contexts

Objectives of the course

� Ultimate goal:

� You become an expert in network design and optimization

� Humble course objectives:

� To help students understand the foundation, algorithms, and systems techniques for network design and optimization

� To help students appreciate both classical and emerging network design problems

� 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 solve different network design and optimization problems (e.g., topology design, routing)

Topics to cover

� Introduction

� Overview of network design

� Notation and illustrations of network design problems

� Technology-specific network modeling

� Foundation

� Modeling of network design problems

� General optimization methods for network design:

� linear programming

� mixed-integer programming

� stochastic heuristic methods

� convex programming

� multi-commodity flow optimization, etc

� Case studies of classical network design problems

� Location and topological design

� Shortest-path routing

� Fairness, network resilience, etc

� Case studies of emerging network design problems (project-based)

� Vehicular networks

� Sensor networks

� Wireless networks

Two major components of the course

� Lecture

� Focus on basic concepts, techniques, and tools

� Project

� Applying the basic concepts, techniques, and tools to real-world

applications, especially in innovative, emerging networking

technologies such as embedded wireless networks as used in

connected vehicles, smart grid, and industrial automation

Textbooks

� Required:

� [R0] Michal Pioro, Deepankar Medhi, Routing, Flow, and Capacity Design in Communication and Computer

Networks, Morgan Kaufmann, 2004.

� Recommended references:

� [R1] Gilbert Held, Inter- and Intra-Vehicle Communications, Auerbach Publications, 2008.

� [R2] Ravindra K. Ahuja, Thomas L. Magnanti, James B. Orlin, Network Flows: Theory, Algorithms, and

Applications, Prentice Hall, 1993.

� [R3] Anurag Kumar, D. Manjunath, Joy Kuri, Communication Networking: An Analytical Approach, Morgan

Kaufmann, 2004.

� [R4] Dimitri Bertsekas and Robert Gallager, Data Networks (2nd edition), Prentice Hall, 1992.

� [R5] Thomas G. Robertazzi, Computer Networks and Systems: Queueing Theory and Performance Evaluation

(3rd edition), Springer.

� [R6] Raj Jain, The Art of Computer Systems Performance Analysis: Techniques for Experimental Design,

Measurement, Simulation, and Modeling, John Wiley & Sons, Inc., 1991.

� [R7] Sheldon M. Ross, Introduction to Probability Models, 9th edition, Academic Press, 2006.

� [R8] Robert G. Gallager, Discrete Stochastic Processes, Kluwer Academic Publishers, 1996.

Logistics

� Class timings

� MW 3:00pm-4:20pm in 318 State Hall

� Office hours

� MW 4:30pm-5:30pm in Suite 14101.3, Maccabees Building, or by

appointment

� Teaching Assistant

� TBA

Logistics (contd.)

� Prerequisites

� Basic knowledge of computer networks, for instance, materials

covered in CSC4290/CSC6290 or equivalent

� Calculus, linear algebra

� Or consent of instructor.

� Course website

� http://www.cs.wayne.edu/~hzhang/courses/7290b/7290b.html

� Course mailing list

� [email protected]

� Web-section only: [email protected]

Logistics (contd.)

� Grading

� Class participation: 10%

� TinyExam: 30%

� Project: 60%

� Note: Students in the web section are required to come to campus to take the quizzes

and to give the project presentations in class

� 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

Project

The project consists of three parts:

� Study embedded wireless networking for intra- and/or inter-vehicle

sensing and control, smart grid sensing and control, or industrial plant

sensing and control; characterize the corresponding traffic demand in

wireless networked sensing and control;

� Formulate and solve the network design problem for wireless

networked sensing and control in connected vehicles, smart grid, or

industrial automation;

� Implement and evaluate the performance of your solution in TOSSIM,

another simulator, or NetEye testbed.

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)

Internet, wireless …

Laptop, PDA … (1979 -)

First computer network

(1969)

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

Sensor networks of today

Redwood ecophysiology

Wind response of Golden Gate Bridge

Intruder detection, classification, and tracking

Temperature vs. Time

8

13

18

23

28

33

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

Humidity vs. Time

35

45

55

65

75

85

95

Rel Humidity (%)

101 104 109 110 111

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)

• • • • … •

• • • • … •

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• • • • … •

• • • • … •• • • • … •

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• • • • … •• • • • … •

• • • • … •

• • ………... • • • ………... • • • ………... • • • ………... •

• • ………... • • • ………... • • • ………... • • • ………... •

Base Station

Other sensornet projects/applications

� Precision agriculture

� Social networking

� Ecosystem conservation

� Homeland security

� Healthcare

� Industrial control

…

Precision agriculture: smart vineyard

monitor soil humidity, temperature, chemistry …

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

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

Homeland security: BioWatch …

Healthcare

Medical implant: artificial retina …

Assisted living: health monitoring & coordination …

Health-environment monitoring: air quality, noise, bio

& chemical-agent …

Industrial control: Intel Semiconductor Factory monitoring …

Preventative equipment maintenance:

monitoring vibration signals …

Vehicular sensor networks

• New applications and startups keep emerging …

� A seamless cyber-physical world of intelligentcomputing 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

0 2 4 6 8 10 12 140

20

40

60

80

100

distance (meter)

pa

cket

deliv

ery

rate

(%

)

0 50 100 150 200 250 30075

80

85

90

95

100

time series

pa

cket

deliv

ery

rate

(%

)

5.5 meters

(×2 secs)

transitional region (unstable & unreliable)

� 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




� Resource constraints (e.g., bandwidth, energy, memory)

� Resource-efficient services, sensornet architecture

� 19.2 kbps

� 2 AA batteries

� 4KB RAM

…






� Application diversity (e.g., traffic patterns, QoS requirements)

� Application-adaptivity

� infrequent aperiodic report of hazards

� need reliable and real-time report

� periodic data collection

� can tolerate certain data loss and

delay








� Complex faults and large system scale

� Dependability despite fault complexity and system scaleNode/link failure, state corruption, system signal loss, malfunctioning sensor, etc

Fault propagation

Increased overall probability of fault occurrence








� Complex faults and large system scale

� Dependability despite fault complexity and system scale

� Heterogeneity

� Architecture and service provisioning in integrated systems


� Dynamic and potentially unreliable wireless channels



� Resource-efficient services



� Complex faults and large scale

� Dependability irrespective of scale

� Growing heterogeneity

� Architecture and service provisioning in integrated systems

OUR FOCUS (1): mission-critical vehicular sensing and control

Our focus (2):mission-critical sensing and control in smart grids and industrial automation

O th e r C o n tro lla b le

L o a d s

W a s h e r

D ry e r

W a te r H e a te r

U n c o n tro lla b le L o a d s

P lu g -in H y b r id E le c tr ic V e h ic le

M ic rog rid

H o m e R e n e w a b le & E n e rg y

S to ra g e S y s te m

A /C

H o m e

C o n tro lle r (s )

M ic ro g rid D is tr ib u te d G e n e ra to r &

C o m b in e d H e a t a n d P o w e r S y s te m

M ic ro tu rb in eF C

M ic ro g r id


M ic ro g rid

R e n e w a b le & E n e rg y S to ra g e S y s te m

U tility G

rid

C o m m e rc ia l M ic ro g rid

O th e r M ic ro g r id s

In d u s tr ia l M ic ro g rid

R e s id e n tia l M ic ro g rid

Tra n

smiss io

n

Netw

ork

G rid


Project (contd.)

� Rules

� Students are allowed to form groups in doing projects, but the number of

students per group should be no more than 2

� Deliverables

� In-class presentation

� Written project report (in the form of a technical paper)

� Timeline

� Form your project team and select reading materials by 01/31/2015

� Submit your detailed project plan (including precise problem formulation)

and timeline by 02/28/2015

� Submit slides for your presentation at least one day before your

presentation (date to be decided)

� Submit your project report electronically by midnight 05/01/2015

Project (contd.)

� 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

Project (contd.): related resources

� MatLab

� http://www.mathworks.com/academia/student_center/tutorials/launchpad.html

� AMPL/CPLEX optimization software package

� http://www.ampl.com/DOWNLOADS/cplex80.html

� http://www.ampl.com/BOOKLETS/amplcplex90userguide.pdf

� http://www.ampl.com/

� Tools for performance evaluation

� Network simulators: TOSSIM, ns-2, qualnet/glomosim, opnet

� NetEye sensor network testbed

� 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

What is this course NOT for?

� Technology tutorial

� Instead, we focus on 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

� Students in web section: watch webcasting after each lecture and ask questions via the course mailing list

� TinyExam

� Exercises

� Strongly encouraged; help understanding and quiz

� 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 exercises and project

� Ask questions!!!

Questions?

Student questionnaire

� Name (optional): E-mail (optional):

� Major: Degree/Expected Year:

� Previous coursework in computer networking:

� Previous coursework in calculus, linear algebra, probability theory, and statistics:

� 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?

hongwei zhang hzhanghzhang/courses/7290b/lectures/00 - course plan.pdfinternet packet forwarding...

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