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Virtualized networks, real problems: How NFV needs network intelligence to address QoE concerns

Cam Cullen, VP Global Marketing at Procera Networks Cam Cullen-VP Global Marketing-Procera Networks

The networking game has changed, and the challenges faced by mobile and broadband operators are greater (and more complicated) than ever before. Mobile subscribers are using more data, especially due to high bandwidth video streaming, and have higher expectations of network quality. They also have a fundamental reliance on mobile data access being “always on” to power their lives – from navigation to social media. Maintaining a consistent QoE in this environment has become the sword operators live or die by and are measured by every second of every day. This is not a new threat to their revenues - this problem has been faced for some time, particularly with mobile operators where the move from 3G to 4G, and with 5G now a reality on the horizon, has exacerbated this further. There is no doubt this issue will continue to grow as it isn’t going away any time soon. And while steps have been taken to address it there’s still a rocky road ahead – especially because the underlying infrastructure is changing to virtualization from the current hardware-based paradigm. Network virtualization is not a cure for all the ills experienced for mobile users, but it is a huge enabler for the operator to address issues far faster than they can today. Alleviating QoE challenges for good depends on having visibility into what’s happening on the network at any given time, which is a whole different ballgame in a virtualized environment – far easier than in the current network deployments.

Network virtualization: The current state of play

Both SDN and NFV make it easier for operators to roll out new services, making changes to the network in minutes rather than days or weeks. Although there’s clear potential for this technology to address network scalability concerns in the long-term and also reduce OPEX costs, data throughput requirements and performance demands are constantly growing and pose a pressing challenge right now. Initial virtualized network instances couldn’t always keep up with this, which slowed the growth and ultimate rollout of virtualized technology. Fortunately, many vendors are increasingly pushing the boundaries of what’s possible when it comes to virtualized network performance. In the past few years alone we’ve regularly seen industry headlines of more than 1Tb/ps of data throughput on a virtualized network. In February, Procera pushed the envelope even further by hitting over 1.8Tbp/s. Unsurprisingly, operators are now sitting up and paying attention to the reality of network virtualization. Yet the extra complexity associated with virtualized networks, and the additional internetworking challenges of this technology running on COTS equipment, is both a blessing and a curse. It’s threatening operator efforts to protect the subscriber experience, resulting in a far more difficult environment for identifying the applications behind high volumes of traffic that can cause all manner of issues for the network.

The other side to network virtualization

Tackling this much greater problem depends on a number of different factors. First and foremost, operators need end-to-end visibility into all new services and platforms likely to cause a surge in demand on their networks, alleviating concerns with poor network performance driving subscriber churn. It’s also important for operators to know when and where a network surge is likely to occur, which comes back to the pressing need to be able to identify specific applications on virtualized networks. After all, it’s only by having this powerful level of actionable data they will be able to start meeting the needs of today’s subscribers en masse rather than simply serving a small heavy data usage subset of their overall user base. Network intelligence and traffic management tools, supported by Deep Packet Inspection technology, are therefore vital. Granted, this has always been the case, but if anything they’re now all the more important in a virtualized network environment. Not only is network intelligence essential for unlocking the data needed to make this a reality, it makes it possible for operators to see what data is flowing across their networks in real-time, to prioritize traffic where appropriate, and to identify where the network is congested in order to take steps towards addressing it. What’s changed in a virtualized environment, however, is how network intelligence technology needs to be deployed.

New networks, virtualized insights

The ultimate goal of any SDN or NFV environment is to deliver an infrastructure capable of being configured on the fly for dynamic service delivery. As mentioned, making this a reality depends on network operators having access to analytics to identify traffic in real-time. Yet network intelligence in its current, physical form factor can only go so far.   In order to maintain the end-to-end visibility required for application identification to function, network intelligence tools must also become virtualized in order to have the same level of speed and efficiency as the virtualized networks they’re deployed on. But, even then, it’s not enough to simply restore network visibility - Applications evolve quickly in the new internet economy. A change made by a major service (Netflix, YouTube, Skype, etc) could cause huge inaccuracies in analytics or throw off QoE management if network traffic associated with that application wasn’t accurately classified.

End-to-end virtualized intelligence

As has long been the case, performance is of paramount importance when it comes to QoE management. Taking the right approach to virtualized networking by putting the right tools in place to identify traffic in real-time makes this easier than ever before, although unlocking end-to-end visibility into data traffic is only scratching the surface of what’s possible with network intelligence.   Combining this technology with the flexibility and scale of virtualized networks has the potential to tip the scales back in the operator’s favour, but once the fundamental application identification challenges have been solved several new opportunities open up. For example, subscribers can be reached with real-time offers in response to their usage habits and adjustments can be made to network policies on the fly. Ultimately, on their own, virtualization technologies such as SDN and NFV aren’t a magic bullet for operators to tackle the QoE challenges they’re faced with. But combine the scale and performance benefits of this with analytics technology that can keep up, and operators have access to a host of new opportunities to keep subscribers happy, better manage network capacity issues, and access new revenue streams.

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