Traffic Statistics

The investigation of network traffic using statistical analysis to gain insight into performance and behaviour.

Forecasting Full-Path Network Congestion Using One Bit Signalling

Conference paper
Proceedings of IEEE/ICC Conference

This paper looks at a mechanism related to Explicit Congestion Notification. It uses a single bit in the IP header to communicate the congestion at each hop in the path. Statistical estimators are used to work out the accuracy of the congestion estimation.

Criticisms of modelling packet traffic using long-range dependence (extended version)

Journal Paper
Journal of Computer and System Sciences, 77(5)

This paper looks at the phenomenon of long-range dependence. It shows that certain long-range dependent models give answers which contain infinities and also that this behaviour will not be detected by a naive modelling approach. The work is an extension of an earlier published PMECT paper.

Deep Diving into BitTorrent Locality

Ruben Cuevans -- Univ Carlos III de Madrid, Nikolaos Laoutaris, Xiaoyuan Yang, Georgos Siganos and Pablo Rodriguez

This paper looks at P2P traffic over bittorrent from a large database of torrents. The paper considers the effects of localising bittorrent traffic on performance and ISP cost saving.

Data: The data set is one of the impressive things about this paper. 100K torrents of which 40K active. Demographics from 3.9M concurrent users and 21M total users over a day from 11K ISPs. Speed test results from ookla and iplane.

On the predictability of large transfer TCP throughput

Qi He, Constantine Dovrolis and Mostafa Ammar

This paper looks at ways of predicting the TCP throughput of a connection. The assumption is that some information is available about the connection. A comparison is made between “formula based” (FB) prediction, that is using round-trip time and loss versus time series analysis prediction (referred to here as history based (HB)), that is using previous measurements on the same connection. Both approaches require some measurements from the connection already.

Improving content delivery using provider-aided distance information

Ingmar Poese, Benjamin Frank, Bernhard Ager, Georgios Smaragdakis and Anja Feldmann

This paper looks at CDN networks and, in particular, suggests Provider-aided Distance Information System (PaDIS), which is a mechanism to rank client-host pairs based upon information such as RTT, bandwidth or number of hops. Headline figure, 70% of http traffic from a major european ISP can be accessed via multiple different locations. “Hyper giants” are defined as the large content providers such as google, yahoo and CDN providers which effectively build their own network and have content in multiple places.

The power of prediction -- Cloud bandwidth and cost reduction

Eyal Zohar, Israel Cidon and Osnat Mokryn

This paper deals with reducing costs for cloud computing users. Cloud customers use “Traffic Redundancy Elimination” (TRE) to reduce bandwidth costs. Redundant data chunks are detected and removed – cloud providers will not implement middleboxes for this as they have no incentive. The paper gives a TRE solution which does not require a server to maintain client status. The system is known as PACK “Predictive ACKnowledgements” which is receiver driven.


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