1. Student Projects in Computer Networking: Simulation versus Coding Leann M. Christianson Kevin A. Brown Cal State East Bay

2. Introduction Computer networking is an integral part of computer science education Network protocols involve many entities Creating practical and compelling student assignments in networking is challenging Cal State East Bay

3. Challenges… Protocols differ in how they respond to corruption, errors, and loss, and replication of results difficult Algorithm performance may only be apparent under high load, negatively impacting other users of the network Cal State East Bay

4. Challenges (cont’d)… The differences in the performance of transport algorithms may only be apparent if the transmitter and receiver nodes are separated by large distances or if a large number of machines are linked to the network Routing algorithms require communication with tens to hundreds of other nodes Cal State East Bay

5. Challenges (cont’d)… Security concerns within a university may make it difficult to provide access to live servers with which to interact Super-user access may be needed to use commands that report on network performance Much network code is at the kernel-level requiring recompilation of the kernel in order to modify Cal State East Bay

6. Networking Algorithms are complex It is beneficial to provide more than a description and explanation Students learn by experimentation The ability to experiment may be provided in (at least) two ways Cal State East Bay

7. Experimentation Two Methods Provide a simulation environment Allow the students to implement the algorithm themselves and run it on real machines Cal State East Bay

8. Coding Benefits Computer Science is similar to engineering – Computer Scientists need experience applying what they learn by building workable modules or programs that implement a key concept – Coding skills enhance career opportunities Cal State East Bay

9. Coding Issues Dedicated equipment is needed – For security – Multiple nodes at great distances must be available Testing – Difficult to duplicate conditions such that all students see identical results – Inducing errors, loss and excess delay is difficult even with a traffic generator – Internet traffic, error, and loss patterns are not reproducible Cal State East Bay

10. Simulation Software Benefits Allows for rapid configuration - WANs, LANs, intermediary, and host nodes Protocols can be easily interchanged and tested Large distances and multiple nodes can be simulated Errors, losses, and delay rates can be defined to follow a chosen distribution pattern Results are reproducible Dedicated equipment and super user access not required Long time periods can be simulated quickly Cal State East Bay

11. Simulation Software Issues Requires investment of class time Simulation model may not accurately reflect real traffic patterns May be difficult to reproduce a particular event as some simulation applications do not allow the user to modify all simulation entities Students will not gain experience writing actual networking code and interacting with live standards- based servers Cost, support, and license management must be considered Cal State East Bay

12. Simulation Software OPNET University Program provides – Free IT Guru software for each student – Runs on Windows XP – Unix version for university – www.opnet.com Cal State East Bay

13. Example 1 TCP vs UDP packet delay Simulate client/server communication over an IP network Observe the effect of packet size on delay for both TCP and UDP transport layer protocols for file transfer

14. OPNET: FTP client and server Cal State East Bay

15. TCP vs UDP Results Simulation can be rerun with different packet sizes Results can be graphed for easy comparison TCP packet delay is longer than UDP packet delay due to the added complexity of the protocol Delay to process each TCP packet increases with packet size

16. TCP vs UDP FTP: Packet Delay Cal State East Bay

17. TCP vs UDP Simulation Benefits Students can easily change parameters such as link speed, packet size, and background traffic load and observe how these affect their initial results A variety of background application traffic (web, database, or email) can be chosen Easy to view and compare results graphically

18. Cal State East Bay TCP vs UDP Simulation Disadvantages Students do not gain valuable coding and testing experience

19. Cal State East Bay TCP vs UDP Coding Write a client and server program that sends a small packet back and forth via a TCP socket 10,000 times Run program 100 times, noting the round trip time for a round of 10,000 sends Graph delay times Repeat with a pair of programs using UDP sockets

20. Cal State East Bay TCP vs UDP Coding Benefits Provides experience with socket programming – Often a first for CS majors Allows students experience with the software lifecycle – develop, run, test, and document results

21. Cal State East Bay TCP vs UDP Coding Disadvantages Difficult to generate a consistent level of background traffic Inability to control the actions of other users competing for network resources Programming languages (C++ or Java) and operating systems (Unix or Windows) will affect delay times Takes additional time to import results to Excel and create graphs

22. Example 2 Routing Convergence Time Convergence is the time it takes for routes between network nodes to stabilize after start up or after a link has gone down Common routing algorithms such as Open Shortest Path First (OSPF), the Routing Information Protocol (RIP), or others can be used Cal State East Bay

23. RIP Routing Convergence Simulation Create a network of router nodes configured to use a particular routing algorithm (RIP) Evaluate the routing tables created by the routing algorithm and trace a path between two nodes. Break a link and run the simulation again Determine the routing table convergence time after a link is broken Cal State East Bay

24. OPNET: Routing Convergence Cal State East Bay

25. Routing Table: node 0 after 8 sec Cal State East Bay

26. Routing Simulation Benefits Rapid and easy configuration Routing tables are automatically created Can “break” links and rerun the simulation easily Simulation runs quickly Cal State East Bay

27. Routing Convergence Simulation Disadvantages Students do not gain experience implementing a routing algorithm on their own Difficult to calculate the exact convergence time due to timing of simulation events Some routing protocols are not offered Cal State East Bay

28. Routing Convergence Coding Provide an input file with nodes, distances, and weights for initial topology Implement a routing algorithm on the topology and run the program until convergence Output routing tables after convergence Write an additional program to trace routes through the tables Cal State East Bay

29. Routing Convergence Benefits Substantial assignment provides a great coding experience Allows students experience with the software lifecycle – develop, run, test, and document results Students who complete the project successfully understand convergence and the way the routing protocol works Cal State East Bay

30. Routing Convergence Disadvantages Problem is complex and requires a large time investment Students get bogged down with the coding details and lose sight of the purpose of the assignment Many give up or fail to write programs that generate correct results Cal State East Bay

31. Conclusions Simulation software allows more concentration on the performance of the protocol and allows for an easier visualization of results Students are more apt to “play” with their simulations and experiment beyond the bounds of the assignment Cal State East Bay

32. Conclusions Programming, though viewed by the students as more difficult, allows them to practice and gain skills that will be useful in their future careers The authors feel that a balance of both programming and simulation activities is the best practice Cal State East Bay

33. THANK YOU! OPNET Lab Manuals – Brown & Christianson, Lab Manual for Data and Computer Communications 7/E by William Stallings,Prentice Hall, 2005 – Christianson & Brown, Lab Manual for Business Data Communications 5/E by William Stallings, Prentice Hall, 2005 – Brown & Christianson, The Networking and Data Communications Laboratory Manual, Labs 5-8, edited by Frances Grodzinsky, Prentice Hall, http://www.prenhall.com/grodzinsky. Cal State East Bay

34. Contact Us… Leann.Christianson@csueastbay.edu Kevin.Brown@csueastbay.edu Cal State East Bay