ISSUE 05 2014
DIAMETER SIGNALLING
23
L
TE subscription numbers are exploding. Earlier this year, Everything Everywhere (EE) announced that its 4G subscriber numbers had hit two million and with network access being rolled out on a continual basis, the ‘next generation’ network is very much here.
LTE is delivering on its promise of providing users with a quicker, more data-centric mobile broadband service, but the backbone of the network is struggling to cope, with Diameter signalling becoming the bottleneck in LTE performance.
The problem with Diameter is not Diameter itself, but rather its underlying transport protocol. Today’s commonly available SCTP is simply not up to the task of handling tens of thousands of very active connections every second. Embedded Linux SCTP may seem like the more convenient and economical (it’s free) solution but it cannot keep up with the multitude of connections and constant user activity that is the very essence of the new, flat, all-IP networks.
Generic transport protocol rendered ‘insufficient’ The hard truth is that the generic transport protocol that Diameter runs over, Stream Control Transmission Protocol (SCTP), is largely insufficient and just cannot cope with the specific signalling needs that the LTE network demands. Larger volumes of data transfer and consumption mean that the strain on the network is being felt at various levels, and critical, evolved signalling and transport solutions are needed to match the demands that are being placed on the network.
The emergence of new technology usually breeds other new technologies, largely by way of support, but with recent network developments and the uptake of LTE, current signalling transport technology is no longer sufficient. This is due to the data pressures that are being placed on the network and tens of thousands of connections that it now needs to handle. Transport protocols such as SCTP, in their existing form, are insufficient and operators have to address the problem that this will pose on LTE performance and find a more reliable and robust solution.
Keeping up with constantly evolving user habits In September of last year, Oracle surmised that service providers must factor in subscriber profiles and behaviour to successfully predict traffic and signalling patterns. This is an imperative issue for operators that seek to stay ahead or at least on top of ever-changing user tendencies.
While it’s clear there are deficiencies in the standard SCTP protocol, the problem is far greater than signalling transport technology. Operators are running the very real risk of failing to keep up with their network subscribers’ habits, especially when it comes to data consumption analytics.
This isn’t a case of replacing the entire transport protocol; it’s more a case of implementing upgraded solutions that recognise the changing data consumption landscape. Unlike previous networks, operators are experiencing an unparalleled volume of simultaneous connections on the LTE network. The number of Diameter transactions is on a sharp increase and its underlying transport layer SCTP is critical to maintaining a high level of customer experience on the network. SCTP must be enhanced to meet this demand or the benefits of LTE won’t be realised by operators or end-users.
The emergence of new technology usually breeds other new technologies, largely by way of support, but with recent network developments and the uptake of LTE, current signalling transport technology is no longer sufficient
The challenges of data analysis A creaking SCTP infrastructure is also having a huge impact on operators’ ability to analyse data. A reliable and robust transport layer, which can cope with thousands of signalling messages, is a fundamental part of the analytics process for operators. In a sense, it is one of the primary steps in the data analytics sequence. Data has to be delivered to operators on time, accurately and reliably. Unstable signalling will have a negative effect on network behaviour and distort analytic data. A weak SCTP can lead to many issues for analytics including data delivery and poor performance metrics. Failure to transport data effectively and efficiently will result in a backlog of data items for engineers to retrieve and analyse and, in a worst case scenario, the oversight of mission critical information.
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