Traffic Management Detection Methods & Tools
The Internet is increasingly becoming central to the lives of citizens, consumers and industry. It is a platform for accessing content; and exchanging information, views and opinions. It has also become a cornerstone for business and e-commerce, and the means to deliver public services.
As consumers use more 'bandwidth hungry' Internet services such as video, existing access networks are likely to experience congestion problems. One way for Internet service providers (ISPs) to manage congestion is to increase the capacity of their networks. Yet, even in the longer term, congestion problems are still likely to persist as demand continues to rise; in particular on wireless networks. Alternatively, ISPs can adopt traffic management (TM) techniques to alleviate network congestion. These techniques allow ISPs to handle traffic more efficiently, thus extracting greater utility and value from their existing networks. In practice, this is achieved through the use of differential traffic management which can better match network resources to quality of service (QoS) demands exhibited by content delivery services and applications.
Whilst TM potentially can offer benefits to consumers, there are concerns that ISPs could use TM anti-competitively. For example, an ISP could make their ‘in-house’ services more attractive by allocating a higher priority/capacity to their own video services and conversely lower the priority/capacities to similar services offered by rivals. In addition, the increasing use of TM also raises questions about consumers' awareness and understanding of the impact that TM has on their broadband service, including restrictions or prohibitions on access to content or applications.
It is envisaged that a practical TM detection mechanism could be a useful part of the regulatory toolkit for helping the communications market deliver online content and services that meet consumer expectations. For example, such a mechanism could potentially help to increase transparency for consumers, visibility for the regulator, and benefits for online service providers. For a practical solution, an effective TM detection mechanism should operate with a sufficient degree of precision, repeatability, reproducibility, scalability and validity of tests percentage. It should take into consideration the different ways by which access networks are architected and the variations in the digital delivery chain (peering and transit); and be able to locate the position in the digital delivery chain where TM is being applied.
This literature review was commissioned by Ofcom to better understand the techniques that could be potentially used to detect traffic management.
The literature review set out in the research report found that practical traffic management detection techniques fall into two general categories, active and passive. Active techniques inject test traffic into the network for the purpose of measurement. Passive techniques do not rely upon introducing additional traffic into the network, and hence are more likely to be suitable for TM detection over capacity constrained mobile networks.
The literature review also identified that whilst a gap exists for effective detection of the presence of traffic management along the digital delivery chain, an emerging network analysis technique, known as ‘network tomography’, appears to provide the potential for a practical and effective solution.
Further work is required to develop a practical TM detection solution, which meets the various requisites of an effective TM detection mechanism described above.
For further information or to discuss the Ofcom research activity on traffic management contact: email@example.com
Ofcom's technical programme enables us to keep up to date with technologies and trends, so that we can be in the best possible position to execute our regulatory duties. In many cases, we do not conduct investigations in-house but make use of external resources, such as private commercial organisations, university departments and government funded research institutions. These reports present the findings of technical work conducted on Ofcom’s behalf. The opinions and conclusions stated within these reports are those of the organisations who conducted the work and may not reflect the view of Ofcom or imply any future policy work in related areas. Ofcom is not responsible for the content or accuracy of these reports.