1. CSE 30264 Computer Networks Prof. Aaron Striegel Department of Computer Science & Engineering University of Notre Dame Lecture 19 – March 23, 2010

2. Today’s Lecture Project 2 –Q&A Project 3 –Overview Transport –TCP Congestion Control Spring 2010CSE 302642 Physical Data Network Transport Application

3. Project 2 Last questions? Spring 2010CSE 302643

4. Project 3 Flex your network socket muscles Peer to peer system –Search / share binary files Two components –Client –Tracker Spring 2010CSE 302644 Due: Tuesday, April 13 @ 5 PM

5. Project 3 Operational order –Client starts up irishP2P ServerIP ServerPort MaxPeers –Client connects to tracker –Client gets list of other clients (IPs, ports) –Client connects to a subset of other clients (MaxPeers) –Client can search for / retrieve files Spring 2010CSE 302645

6. Project 3 - Tracker Who are the people in my neighborhood? –Simple list IP, Port –Supports two operations –Client can retrieve the list of other clients –Client can join the list at the server Spring 2010CSE 302646 Optional / EC: Make a keep alive between the client and the tracker

7. Project 3 - Client Key functionality –Bootstrap Figure out who other clients are Connect to the server –Command prompt Take commands from user Search –Try to find a file at the other locations Get –Download the file from the other locations –Server for other clients Respond to their search requests Spring 2010CSE 302647

8. Project 3 - Search Simple search dynamics –Search only immediate peers –Look only at file name Assume file name is descriptive Spring 2010CSE 302648 > search *Peas*.mp3 Searching for *Peas*.mp3 Querying Peer 1: Yes, successful! Track 1 – Peas.mp3 Track 2 – Peas.mp3 Querying Peer 2: No results

9. Project 3 - Retrieval Request a file for transfer from the client –Transfer via binary –Up to you how to transfer Spring 2010CSE 302649 > get “Track 1 - Peas.mp3” 1 Contacting Peer 1 for information Success – file exists, 1278920 bytes File downloaded, 789.5kB / sec >

10. Project 3 - Client Multiple pthreads –Main thread watching the command prompt –Thread watching for new client requests (new conns) –Thread handling existing clients Spring 2010CSE 3026410 Need to demonstrate three active clients

11. Project 3 – Extended Features 5% of project grade Several features ideas –Keep alive with tracker –Tracker notification of client leaving –Search / fetch option –Ability to fetch only part of a file from a client –Ability to queue requests while continuing to work –Health / status of existing peers –Prevention of freeloading Spring 2010CSE 3026411

12. Spring 2009CSE3026412 Congestion Control Outline Congestion Avoidance RED TCP Vegas

13. Spring 2009CSE3026413 Congestion Avoidance TCP’s strategy –Control congestion once it happens –Repeatedly increase load in an effort to find the point at which congestion occurs, and then back off Alternative strategy –Predict when congestion is about to happen –Reduce rate before packets start being discarded –Call this congestion avoidance, instead of congestion control Two possibilities –Router-centric: DECbit and RED Gateways –Host-centric: TCP Vegas

14. Spring 2009CSE3026414 DECbit Add binary congestion bit to each packet header Router –Monitors average queue length over last busy+idle cycle –Set congestion bit if average queue length >= 1 –Attempts to balance throughput against delay

15. Spring 2009CSE3026415 End Hosts Destination echoes bit back to source Source records how many packets resulted in set bit If less than 50% of last window’s worth had bit set –increase CongestionWindow by 1 packet If 50% or more of last window’s worth had bit set –decrease CongestionWindow by 0.875 times

16. Expedited Congestion Notification ECN – Expedited Congestion Notification –DECbit realized –Two bit congestion notification Enabled bit Actual setting –Support in Linux kernel –What does it say? Spring 2010CSE 3026416 Are there any problems with it?

17. Spring 2009CSE3026417 Random Early Detection (RED) Notification is implicit –just drop the packet (TCP will timeout) –could make explicit by marking the packet Early random drop –rather than wait for queue to become full, drop each arriving packet with some drop probability whenever the queue length exceeds some drop level

18. Spring 2009CSE3026418 RED Details Compute average queue length AvgLen = (1 - Weight) * AvgLen + Weight * SampleLen 0 < Weight < 1 (usually 0.002) SampleLen is queue length each time a packet arrives

19. Spring 2009CSE3026419 RED Details (cont) Two queue length thresholds if AvgLen <= MinThreshold then enqueue the packet if MinThreshold < AvgLen < MaxThreshold then calculate probability P drop arriving packet with probability P if MaxThreshold <= AvgLen then drop arriving packet

20. Spring 2009CSE3026420 RED Details (cont) Computing probability P TempP = MaxP * (AvgLen - MinThreshold)/ (MaxThreshold - MinThreshold) P = TempP/(1 - count * TempP) Drop Probability Curve

21. Spring 2009CSE3026421 Tuning RED Probability of dropping a particular flow’s packet(s) is roughly proportional to the share of the bandwidth that flow is currently getting MaxP is typically set to 0.02, meaning that when the average queue size is halfway between the two thresholds, the gateway drops roughly one out of 50 packets. If traffic is bursty, then MinThreshold should be sufficiently large to allow link utilization to be maintained at an acceptably high level Difference between two thresholds should be larger than the typical increase in the calculated average queue length in one RTT; setting MaxThreshold to twice MinThreshold is reasonable for traffic on today’s Internet

22. Spring 2009CSE3026422 TCP Vegas Idea: source watches for some sign that router’s queue is building up and congestion will happen too; e.g., –RTT grows –sending rate flattens

23. Spring 2009CSE3026423 Algorithm Let BaseRTT be the minimum of all measured RTTs (commonly the RTT of the first packet) If not overflowing the connection, then ExpectedRate = CongestionWindow/BaseRTT Source calculates sending rate ( ActualRate ) once per RTT Source compares ActualRate with ExpectedRate Diff = ExpectedRate - ActualRate if Diff <  increase CongestionWindow linearly else if Diff >  decrease CongestionWindow linearly else leave CongestionWindow unchanged

24. Spring 2009CSE3026424 Algorithm (cont) Parameters  = 1 packet  = 3 packets