1. By Manish Jain and Constantinos Dovrolis 2003
End-to-End Available Bandwidth: Measurement Methodology, Dynamics, and Relation With TCP Throughput By
Manish Jain and
Constantinos Dovrolis
2003
Presented by Caroline Williams
End-to-End Available Bandwidth
Rosa Williams

2. Purpose
The authors are not satisfied with the current definition of available bandwidth nor the tools to measure available bandwidth.
The authors propose:
A concise available bandwidth definition
A methodology to measure available bandwidth
A tool that implements the methodology
Several bandwidth estimation tools have been developed: pathchar, clink, pchar bprobe, nettimer, pathrate…. These measure end-to-end capacity.
Cprobe and pipechar attempted to measure avail-bw, but the basis for their approach has been discredited.
The list goes on and on, with problems arising in each measurement.
End-to-End Available Bandwidth
Rosa Williams

3. Motivation Available bandwidth is an important metric for:
Congestion control
Streaming applications
Quality-of-service verification
Server selection
Overlay networks
As such, the definition should be agreed upon, the measurements accurate and nonintrusive.
End-to-End Available Bandwidth
Rosa Williams

4. Definition End-to-end Avail-bw
The narrow link is the link with the minimum capacity. The tight link is the link with the minimum avail-bw. The tight link determines the avail-bw of the path.
End-to-End Available Bandwidth
Rosa Williams

5. Methodology Self-Loading Periodic Streams (SLoPS)
A stream consists of K packets of size L, sent at constant rate R
One-way delays (OWD) of successive packets at RCV show an increasing trend when R > A
A is converged upon through an iterative algorithm at RCV. RCV notifies SND of new R. The “algorithm will converge to a range [Rmin, Rmax] that includes A.”
End-to-End Available Bandwidth
Rosa Williams

6. Implementation Pathload
Process SND generates fleets of timestamped packet streams for R
Process RCV determines the OWD trend for the fleet. Then, adjusts Rmin or Rmax according to the SLoPS algorithm. A new R (halfway between Rmin and Rmax) is fed back to SND.
Continue the above two steps until Rmax – Rmin £ a user defined resolution
[Rmin, Rmax] can be calculated in less than 15 seconds using default parameters
End-to-End Available Bandwidth
Rosa Williams

7. Verification (NS Simulation)
Remember, the tight link is the link with the minimum avail-bw, and it determines the avail-bw of the path. This shows just the positive results. The authors have found that when the path includes several tight links, pathload underestimates the avail-bw. While they have a good understanding of the cause, they have not provided a solution/workaround.
End-to-End Available Bandwidth
Rosa Williams

8. Verification (Experimental)
Note that the pathload estimate falls within the MRTG range in ten out of the twelve runs, while the deviations are marginal in the two other runs.
End-to-End Available Bandwidth
Rosa Williams

9. Dynamics: Variability and Load Conditions
Look at the 75th percentile. Variability of the avail-bw increases significantly as the utilization of the tight link increases. For users, this suggests that a lightly loaded network will not only provide more avail-bw, but also a more predictable and smooth throughtput – especially important for applications such as streaming audio/video.
End-to-End Available Bandwidth
Rosa Williams

10. Dynamics Variability and Statistical Multiplexing
Statistical multiplexing is the number of flows that simultaneously use the tight link. The degree of statistical multiplexing is ranked A, B, C. “we observe that the variability of the avail-bw decreases significantly as the degree of statistical multiplexing increases”. For users, this implies that with the same level of utilization, choose the wide pipe. Network providers, however, should aggregate traffic in a higher-capacity trunk than in muliple parallel links of lower capacity.
End-to-End Available Bandwidth
Rosa Williams

11. Dynamics: Effect of the Stream Length
Observe that avail-bw variablity decreases as the stream duration increases.
End-to-End Available Bandwidth
Rosa Williams

12. Dynamics Effect of the Fleet Length
N is the number of streams in a fleet. I expected that this would have the same effect as number of packets in a stream. Not true. Increasing the packets in a stream, causes only a short increase in duration many times. Increasing the number of streams in a fleet, increases the overall duration, increasing probability that Amin and Amax will go to their extremes.
End-to-End Available Bandwidth
Rosa Williams

13. TCP and Avail-BW
From this experiment, the authors want to know: 1. can a bulk TCP connection measure the avail-bw in a path and how accurate is such an avail-bw measurement approach 2. what happens then to the rest of the traffic in the path - how intrusive is a TCP based avail-bw measurement?
In period B and D, the authors performed a bulk transfer capacity (BTC) connection. The RTT measurements were gathered with ping.
Observations: 1. the BTC connection manages to saturate the path (look at avail-bw) in B&D.
RTT increases significantly during B&D
The BTC connection gets an avg throughput during B&D that is 20-30% more than the avail-bw in intervals A, C and E. It must be grabbing part of the throughput of other TCP connections.
Conclusion, TCP flows are probably not good ways to measure avail-bw. It steals from other flows and increases RTT (thus intrusive).
End-to-End Available Bandwidth
Rosa Williams

14. Intrusiveness Pathload
This experiment was run similarly to the previous. Instead of doing a BTC, they run pathload in periods B and D. Note that there is no appreciable drop in avail-bw. Also, note that the RTT are below half of the maximum on the BTC test. Also, RTT seems to be faily constant across a-b-c-d-e. The authors conclude that pathload is non-intrusive.
End-to-End Available Bandwidth
Rosa Williams

15. Conclusion Available bandwidth is elusive
Jain and Dovrolis have provided a methodology that reports a range of rates that includes avail-bw
Their tool is nonintrusive and reliable in a “wide range of load conditions and path configurations”.
End-to-End Available Bandwidth
Rosa Williams

16. References
Information Sciences Institute. ns October 21, 2007.
M. Jain, C. Dovrolis. End-to-end available bandwidth: measurement methodology, dynamics, and relation with TCP throughput. IEEE/ACM Trans. Netw. 11(4): (2003)
T. Oetiker. MRTG - The Multi Router Traffic Grapher. October 21, 2007.
End-to-End Available Bandwidth
Rosa Williams