A Simulation model for e-VLBI traffic on network links in the Netherlands

1. A Simulation model for e-VLBI traffic on network links in the Netherlands Julianne Sansa* * With Arpad Szomoru & Thijs van der Hulst 5th e-VLBI Workshop, 17-20 September 2006, Haystack Observatory

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. • CA ACK:Cwnd  Cwnd + 1/Cwnd DROP: Cwnd  Cwnd -1/2*Cwnd • Cwndoptimal = 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), www.isi.edu/nsnam/ns

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 Simulated Real

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

10. The e-VLBI data generation modelThe combined effect • ”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

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. Futurework • 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