Page 9 - Telecom Reseller October-November 2016

October/November 2016
Telecom Reseller 9
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Virtualized Instrumentation Empowers Operators to Embrace the Third Network
We are in the midst of a transitional period for mobile network operators and their use of virtualized performance assurance tools. One driver of the changes now underway is that, especially for new services such as voice over LTE (VoLTE), quality of experience (QoE) is proving to
be more critical than ever, and also more challenging to achieve using conventional tools and methodologies.
Operators like Telefonica, SK Telecom, T-Mobile, and Colt are moving rapidly to adopt virtualized instrumentation—in some cases, so ware-only solutions covering hundreds of thousands of base stations— because it is very a ordable and can be deployed in a matter of weeks or a few months, a pace unheard-of with traditional hardware approaches.
e role of performance monitoring is changing. It’s no longer an a erthought, but instead a strategic investment in network intelligence, especially from the backhaul network, needed for end-to-end network planning, service design & roll-out, and quality of experience management & optimization.
Such comprehensive achievements
GOLD
by Ken Gold, Director Solutions Marketing at Accedian (www.accedian.com)
are possible by integrating virtualized instrumentation with big data analytics platforms and so ware-de ned networking (SDN) controllers, turning the performance data collected into actionable insights.
e virtualization of performance monitoring illustrates the type of innovation required for the mobile networks progression to LTE, 5G and the ird Network. Next- generation mobile equipment will demand accurate information in a minimal or no hardware format, with no staging or setup time.
Rapid test and turn-up is the only way to achieve the pace required, while the ability to test between any physical or virtual location in the network facilitates the move to virtual Evolved Packet Core, cloud RAN and other
key technologies that require multi-site coordination (e.g., coordinated multipoint access/CoMP) and automated interference control/ICIC).
VoLTE is a good example of how this new dynamic will play out and what’s needed to support it. Many VoLTE roll-outs are based
on highly virtual platforms. Operators tend
to expect that in such situations networks and services will behave as they did in the static world of hardware-based networks. But, reality suggests otherwise.
Not only is the virtualization layer hard
to manage, but it interacts on new levels almost like a living entity. Many di erent network functions talk to each other, and
to some degree they are self-organizing and autonomous. Inevitably, a lot of micro-issues emerge and while each on its own is no big deal, together they can cascade with a knock- on e ect and cause a large-scale network or service failure.
More than one operator has been caught o -guard by these issues. e measurements and metrics used for traditional packet- based transport, backhaul assurance, or voice services are just not enough to see what’s happening in these newer, more dynamic
networks.
Put another way, traditional performance
monitoring methods are mismatched for next- generation, dynamic, virtualized networks and services.
Some of the things operators need now and are achieving through the use of virtualized instrumentation, include:
l A wider range of performance indicators l Much more granular metrics resolution l A statistical reporting-based approach to
identifying root causes
One last piece of this puzzle is worth
mentioning: distributed packet brokering, another newcomer to the performance monitoring state.
It complements virtualized instrumentation, opening up many options to operators because end-user QoE is a key to long-term success and di erentiation against non-Carrier Ethernet providers.
Operators need a simple, cost-e ective way to capture data at the edge of the network and then process this information in a central location. Distributed packet brokering empowers operators with QoE results based on data at the edge of the network as close as possible to the end-user. n