Likelihood-based assessment of dynamic networks
This paper used a likelihood based framework to create a rigorous way to assess models of networks. Network evolution is broken down into an operation model (it decides the 'type' of change to be made to the network, e.g. "add node" "add link" "remove node" "remove link") and an object model (that decides the exact change -- which node/link to add).
The system is shown to be able to recover known parameters on artificial models and to be useful in analysis of real data.
This work can generate graphs from a very large family with the aim of fitting those graph to parameters of real data sets.
This talk is essentially the same as that delivered in Cambridge two months earlier (alas no progress on this research for that period).
The research is based on two papers:
A longitudinal analysis of Internet rate limitations -- http://www.richardclegg.org/tcp_rate_infocom_2014
and
On the relationship between fundamental measurements in TCP flows -- http://www.richardclegg.org/tcp_limitations_icc_2013
The essential findings are that TCP is not working as we expect. The expected correlation between throughput and packet loss is not found. The correlation with delay (RTT) is as expected -- throughput proportional to 1/delay. A high correlation with flow length is found -- longer flows have higher throughput. However, this may be a sampling error due to the restricted length of the samples used.
The TCP flows studied are broken down by assumed cause where TCP mechanisms are thought not to be the primary cause for throughput:
1) Application limited -- an application decides to reduce its own flow by deliberately not sending data.
2) Host Window limited -- one or other host has a low maximum window size that restricts flow.
3) Advertised window limitation -- a middlebox or the receiver manipulates their advertised window size to reduce the flow.
More than half of TCP flows (and more than 80% of long flows) are limited by these mechanisms and not by traditional TCP mechanisms.