5th e-vlbi workshop, 17-20 september 2006, haystack observatory 1 a simulation model for e-vlbi...
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5th e-VLBI Workshop, 17-20 September 2006, Haystack Observatory
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A Simulation model for e-VLBI traffic on network links in the
Netherlands
Julianne Sansa*
* With Arpad Szomoru & Thijs van der Hulst
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Outline
• Background
• Motivation
• Related Work
• Setup
• Results
• The model
• Conclusion & future work
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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.
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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
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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
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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
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CWND & RWND for real and simulated flows
Real Simulated
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Throughput for real and simulated flows
Real Simulated
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The e-VLBI data generation modelThe three factors
Large idle times Low throughput
More background traffic
Low throughput
maxCWND < 256 packets Increasing maxCWND
High throughputmaxCWND > 256 packets Increasing maxCWND
Constant throughput
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• ”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 modelThe combined effect
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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.
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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
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Questions