5th e-VLBI Workshop, September 2006, Haystack Observatory 1 A Simulation model for e-VLBI traffic on network links in the Netherlands Julianne Sansa* * With Arpad Szomoru & Thijs van der Hulst

2 Outline Background Motivation Related Work Setup Results The model Conclusion & future work

3 Background TCP Congestion Control algorithm (AIMD) on LFN Cwnd = max. # packets that TCP sender injects into network before receiving ACK. CAACK:Cwnd  Cwnd + 1/Cwnd DROP: Cwnd  Cwnd -1/2*Cwnd Cwnd optimal = Bandwidth *RTT Evaluation of proposed TCP algorithms that address the challenge and specifically in e-VLBI setting.

4 Motivation Need for a model that can be used to test & relate suggested improvements of the underlying transport protocols to the e-VLBI data in the ns-2 environment. ns-2 is a publicly available network simulator Breslau et.al.(2000), Nicol D.M.(2003),

5 Related Work General TCP/IP data generation models: Danzig et.al.(1992) and Paxson & Floyd (1994) Application specific data generation models: Crovella et.al.(1998) - web, Hernandez-Campos F. et.al. (2001) - FTP & SMTP Various methods used to trace the data: –Embedding instrumentation software in the client –Installing specialised software and hardware in the network –Installing publicly available packet capture tools on off-the- shelf hardware

6 Setup TCPdump used to gather network statistics. ns-2 simulator used to simulate various scenarios, each simulation is run for a period of 80 s and repeated five times. High performance options set and also simualated: MTU-8192 Bytes, TCP Buffers-4 MB, txqueuelen-20,000

7 CWND & RWND for real and simulated flows Real Simulated

8 Throughput for real and simulated flows Real Simulated

9 The e-VLBI data generation model The three factors Large idle timesLow throughput More background traffic Low throughput maxCWND < 256 packets Increasing maxCWND High throughput maxCWND > 256 packets Increasing maxCWND Constant throughput

10 ”on/off” bursty data generation, initially with data bursts of 500 ms and idle times of 500 ms. Receiver limitation simulated with the maximum CWND to 64 packets (0.06 Mbytes) and RWND to the 50 packets (0.05 Mbytes). background traffic composed of –10 normal sized TCP flows from the reverse direction –25 small TCP flows in the same direction –5 small TCP flows flowing in the opposite direction, –110 web sessions starting randomly during the flow, 100 in the same direction,10 in the opposite direction The e-VLBI data generation model The combined effect

11 Conclusions By comparing results of a real flow against those of a simulation, the best approximation for the e-VLBI data generation follows a bursty pattern i.e. large bursts separated by idle periods. The 3 factors seen to affect the flow’s throughput are idle periods (most significant), receiver limitation & background traffic.

12 Future work Future work will include designing data generation models for the other commonly used Mark5 transfer modes such as In2Net-Net2Out, In2Net-Net2Disk,etc. Validating of data generation model by conducting experiments elsewhere to guard against biases due to local network conditions such as hardware and local usage patterns Explore models that eliminate or shorten the idle time between data bursts by using these models in evaluation of transport protocols through simulation

13 Questions