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ENGS4 2004 Lecture 7 ENGS 4 - Lecture 7 Technology of Cyberspace Winter 2004 Thayer School of Engineering Dartmouth College Instructor: George Cybenko, x6-3843 gvc@dartmouth.edu Assistant: Sharon Cooper (“Shay”), x6-3546 Course webpage: www.whoopis.com/engs4www.whoopis.com/engs4
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ENGS4 2004 Lecture 7 Today’s Class Wrap-up routing basics from Lecture 6 Sam’s’s mini-lecture Break State-based methods for “Predicting the Future”
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ENGS4 2004 Lecture 7 Circuit Switching Reserve a “circuit” and that “guarantees” services for each user Requires significant “setup time” Good for telephones, bad for web browsing!!!!
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ENGS4 2004 Lecture 7 Packet Switching Send “packets” into the network, routing each packet individually, like the post office. Packets are “routed” through the network, sorted at “switches”. Requires no setup time but no guarantee of service!! Bad for telephones, good for web browsing!!!!
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ENGS4 2004 Lecture 7 Circuit vs Packet Switching Call setup time – s seconds Bandwidth - b bits per second Packet routing overhead – p seconds per hop Message of B bits Distance between end points - d EG Circuit switching requires: s + B/b + d/c seconds EG Packet switching requires: B/b + p*h + d/c seconds Which is better depends on values of parameters!!!
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ENGS4 2004 Lecture 7 B=50,000 b=1,000,000 p=0.005 h=10 Circuit switching is better Packet switching is better
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ENGS4 2004 Lecture 7 IP Packets and routing IP is Internet Protocol (also Intellectual Property sometimes) IP addresses consist of four numbers between 0 and 255 How many possible IP addresses are there in total? What is www.dartmouth.edu’s IP address? Router Network 1 Network 2 A router can be a dedicated piece of hardware or a computer with several network interfaces. Cisco, 3Com, etc sell routers. ?
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ENGS4 2004 Lecture 7 Resolving internet addresses Your computer LAN DHCP Server DNS Server 1. Can I get an IP address, etc? 2. Here is a temporary address and other information. 3. What is the address of www.cnn.com? 4. www.cnn.com is 207.25.71.82 Rest of the world Bridge or gateway or router or switch 5. Send packets to 207.25.71.82
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ENGS4 2004 Lecture 7
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Time vs Frequency Division Multiple Access (TDMA vs FDMA) TDMA – Divide a communications resource or channel using time slots. Users take turns using the same resource by using it only in their allotted slots. FDMA – Divide a communications resource or channel using frequency division. Users simultaneously use the channel but at different frequencies. Space Division Multiple Access (Cellular phone) Code Division Multiple Access (Spread spectrum) Examples?
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ENGS4 2004 Lecture 7 Network routing Routing table in a router looks like..... PatternNext node on path 129.170.*.*host 1 125.*.*.*host 2 105.121.5.21host 3 defaulthost 4 Router 1 2 3 4
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ENGS4 2004 Lecture 7 Bellman-Ford Routing A E C D B F 2 1 3 1 4 1 8 Computer/host Distance/cost/delay between hosts
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ENGS4 2004 Lecture 7 A E C D B F 2 1 3 1 4 1 8 A 0 B 1 C * D 2 E * F * A 2 B * C 1 D 0 E 4 F * A 1 B 0 C 3 D * E * F * A * B 3 C 0 D 1 E * F 1 A * B * C 1 D * E 8 F 0 A * B * C * D 4 E 0 F 8 Initial table has distance to each host one hop away and * otherwise.
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ENGS4 2004 Lecture 7 A E C D B F 2 1 3 1 4 1 8 A 0 0 B 1 1 C * 4 D 2 2 E * 6 F * * A 2 2 B * 3 C 1 1 D 0 0 E 4 4 F * 2 A 1 1 B 0 0 C 3 3 D * 3 E * * F * 4 A * 3 B 3 3 C 0 0 D 1 1 E * 5 F 1 1 A * * B * 4 C 1 1 D * 2 E 8 8 F 0 0 A * 6 B * * C * 5 D 4 4 E 0 0 F 8 8 newdistance to X = min( distance to neighbor + distance from neighbor to X) where min is over all neighbors
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ENGS4 2004 Lecture 7 A E C D B F 2 1 3 1 4 1 8 A 0 0 0 B 1 1 1 C * 4 3 D 2 2 2 E * 6 6 F * * 4 A 2 2 2 B * 3 3 C 1 1 1 D 0 0 0 E 4 4 4 F * 2 2 A 1 1 1 B 0 0 0 C 3 3 3 D * 3 3 E * * 7 F * 4 4 A * 3 3 B 3 3 3 C 0 0 0 D 1 1 1 E * 5 5 F 1 1 1 A * * 4 B * 4 4 C 1 1 1 D * 2 2 E 8 8 6 F 0 0 0 A * 6 6 B * * 7 C * 5 5 D 4 4 4 E 0 0 0 F 8 8 6 Repeat it!!!
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ENGS4 2004 Lecture 7 A E C D B F 2 1 3 1 4 1 8 A 0 0 0 0 B 1 1 1 1 C * 4 3 3 D 2 2 2 2 E * 6 6 6 F * * 4 4 A 2 2 2 2 B * 3 3 3 C 1 1 1 1 D 0 0 0 0 E 4 4 4 4 F * 2 2 2 A 1 1 1 1 B 0 0 0 0 C 3 3 3 3 D * 3 3 3 E * * 7 7 F * 4 4 4 A * 3 3 3 B 3 3 3 3 C 0 0 0 0 D 1 1 1 1 E * 5 5 5 F 1 1 1 1 A * * 4 4 B * 4 4 4 C 1 1 1 1 D * 2 2 2 E 8 8 6 6 F 0 0 0 0 A * 6 6 6 B * * 7 7 C * 5 5 5 D 4 4 4 4 E 0 0 0 0 F 8 8 6 6 Repeat it...stop when the table does not change.
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ENGS4 2004 Lecture 7 A E C D B F 2 1 3 1 4 1 8 A 0 0 0 0 A B 1 1 1 1 B C * 4 3 3 D D 2 2 2 2 D E * 6 6 6 D F * * 4 4 D A 2 2 2 2 A B * 3 3 3 A C 1 1 1 1 C D 0 0 0 0 D E 4 4 4 4 E F * 2 2 2 C A 1 1 1 1 A B 0 0 0 0 B C 3 3 3 3 C D * 3 3 3 A E * * 7 7 A F * 4 4 4 C A * 3 3 3 D B 3 3 3 3 B C 0 0 0 0 C D 1 1 1 1 D E * 5 5 5 D F 1 1 1 1 F A * * 4 4 C B * 4 4 4 C C 1 1 1 1 C D * 2 2 2 C E 8 8 6 6 C F 0 0 0 0 F A * 6 6 6 D B * * 7 7 D C * 5 5 5 D D 4 4 4 4 D E 0 0 0 0 E F 8 8 6 6 D The min neighbor determines the paths
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ENGS4 2004 Lecture 7 A E C D B F 2 1 3 1 4 1 8 A 0 A B 1 B C 3 D D 2 D E 6 D F 4 D A 2 A B 3 A C 1 C D 0 D E 4 E F 2 C A 1 A B 0 B C 3 C D 3 A E 7 A F 4 C A 3 D B 3 B C 0 C D 1 D E 5 D F 1 F A 4 C B 4 C C 1 C D 2 C E 6 C F 0 F A 6 D B 7 D C 5 D D 4 D E 0 E F 6 D Only need the total distances and the next neighbor
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ENGS4 2004 Lecture 7 A E C D B F 2 1 3 1 4 1 8 A 0 A B 1 B C 3 D D 2 D E 6 D F 4 D A 2 A B 3 A C 1 C D 0 D E 4 E F 2 C A 1 A B 0 B C 3 C D 3 A E 7 A F 4 C A 3 D B 3 B C 0 C D 1 D E 5 D F 1 F A 4 C B 4 C C 1 C D 2 C E 6 C F 0 F A 6 D B 7 D C 5 D D 4 D E 0 E F 6 D Ooops...what if the network changes?? 2 Have enough information to keep updating the table until it stops changing
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ENGS4 2004 Lecture 7 Sam’s Mini-lecture
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ENGS4 2004 Lecture 7 Break
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ENGS4 2004 Lecture 7 “Predicting the Future” Newtonian revolution (late 1600’s) : F=ma Concept of “state” introduced The “state” of a system is all that is needed to predict it’s future states. Having additional information about the system’s past states does not help to predict it’s future. This defines the notion of “state”.
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ENGS4 2004 Lecture 7 Example A cannonball shot from a canon. Where will it fall? ??? position + momentum of the canonball is the “state”
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ENGS4 2004 Lecture 7 States transition rules for a cannonball Four state variables: horizontal position at time i: x(i) vertical position at time i: y(i) horizontal momentum at time i: xm(i) vertical momemtum at time i: ym(i) Update rules to go from time i-1 to time i x(i)=x(i-1)+dt*xm(i-1) if (y(i-1) > 0 ) y(i)=y(i-1)+dt*ym(i-1) xm(i)=xm(i-1) ym(i)=ym(i-1)-dt*g
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ENGS4 2004 Lecture 7 Matlab demo
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ENGS4 2004 Lecture 7 Game of Life http://www.math.com/students/wonders/life/life.html Rules are very simple Rules describe how to go from one “state” to the next No simple mathematical theory for predicting what state will exist in the future….must simulate in general.
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ENGS4 2004 Lecture 7 State-based Prediction What are examples of state-based prediction? Weather - http://www.ecmwf.int/http://www.ecmwf.int/ Astronomy - http://science.nasa.gov/RealTime/jtrack/Spacecraft.html http://science.nasa.gov/RealTime/jtrack/Spacecraft.html Chemistry - http://polymer.bu.edu/java/java/movie/index.html http://polymer.bu.edu/java/java/movie/index.html Biology - http://arieldolan.com/ofiles/JavaFloys.aspx http://arieldolan.com/ofiles/JavaFloys.aspx Physics - http://otrc93.ce.utexas.edu/~waveroom/Applet/WaveKinematics/WaveKinematics.html http://otrc93.ce.utexas.edu/~waveroom/Applet/WaveKinematics/WaveKinematics.html Medicine - http://www.esg.montana.edu/meg/notebook/example1.html http://www.esg.montana.edu/meg/notebook/example1.html Others?
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