The contents of this legacy page are no longer maintained nor supported, and are made available only for historical purposes.

Bibliography Details

S. Roughan, O. Sen, and N. Duffield, "Class-of-service Mapping for QoS", in ACM SIGCOMM IMC, Oct 2004.

Class-of-service Mapping for QoS
Authors: S. Roughan
O. Sen
N. Duffield
Published: ACM SIGCOMM IMC, 2004
URL: http://www.imconf.net/imc-2004/papers/p135-roughan.pdf
Entry Dates: 2009-02-06
Abstract: The ability to provide different Quality of Service (QoS) guarantees to traffic from different applications is a highly desired feature for many IP network operators, particularly for enterprise networks. Although various mechanisms exist for providing QoS in the network, QoS is yet to be widely deployed. We believe that a key factor holding back widespread QoS adoption is the absence of suitable methodologies/processes for appropriately mapping the traffic from different applications to different QoS classes. This is a challenging task, because many enterprise network operators who are interested in QoS do not know all the applications running on their network, and furthermore, over recent years port-based application classification has become problematic. We argue that measurement based automated Class of Service (CoS) mapping is an important practical problem that needs to be studied. In this paper we describe the requirements and associated challenges, and outline a solution framework for measurement based classification of traffic for QoS based on statistical application signatures. In our approach the signatures are chosen in such as way as to make them insensitive to the particular application layer protocol, but rather to determine the way in which an application is used for instance is it used interactively, or for bulk-data transport. The resulting application signature can then be used to derive the network layer signatures required to determine the CoS class for individual IP datagrams. Our evaluations using traffic traces from a variety of network locations, demonstrate the feasibility and potential of the approach.
Results:
  • datasets: four datasets 1)Waikato trace (use a serven day long packet header traces drawn from the Auckland-IV data set); 2)Application level session logs from a commerical streaming service. Over 185000 sessions for realmedia streaming objects, over a serven days period from Dec 13-19, 2001; 3)Gigascope trace 1: collect at a choke point in an access network on a T3 line from the 7th of May to the 16th of July,2003, using a Gigascope probe; 4)Collected using Gigascope which was placed on the span port of the major edge router of ATT Research's local network. Thus we see all of the traffic to and from the public Internet over a T3 connection, and also from our local network to other company sites via another T3 connection, and also a significant amount of internal LAN to LAN traffic;