Dealing with Mobile Data: How Much Is Too Much?
Relieving mobile congestion with network edge intelligence complements existing strategies
By: Chris Hill
Mar. 31, 2010 11:45 PM
The Federal Communications Commission (FCC) recently announced a 10-year, $15.5 billion broadband deployment plan to help produce what may be the fastest nationwide broadband network in the world. It set a lofty goal of 1Gbps to shore up connectivity at government buildings, schools and hospitals, and to offer "affordable" 100Mbps service to some 100 million U.S. homes by 2020.
This plan will surely spur even more rampant growth in access to the Web via mobile devices, especially as networks begin their migration to 4G technologies such as WiMAX and Long Term Evolution (LTE). Clearly growth in smartphone usage, especially among young people, is placing unprecedented demands on mobile data flow.
The exponential growth in data flow is causing significant congestion that is threatening network performance and degrading service to subscribers. Voracious user appetites for mobile access to online information is causing network congestion, dropped calls, slower connection speeds and growing dissatisfaction among subscribers.
Potential growth aside, two factors have significantly contributed to the increase of mobile data. First, mobile broadband usage is replacing or complementing landline connections, which are often more expensive or less accessible than DSL or cable connections in places such as Western Europe and Asia. Second is the availability of more sophisticated, affordable, wildly compelling and data-hungry smartphones. In a recent Business Week article David Sutphen, co-chairman of the Internet Innovation Alliance said, "In a year and a half from now when networks switch over to 4G, you could do almost anything you want whether it's ordering groceries, paying parking tickets or applying for jobs online." But these services come with a price and will exhaust even more network resources. Network operators thus find themselves in desperate need of viable solutions to help manage the mobile data flow that threatens to choke their networks.
Content adaptation and optimization solutions including compression, video optimization and caching are increasingly being deployed to relieve networks. While useful, they are not without their limitations. These solutions can often create inefficiencies that limit network performance and degrade subscribers' experiences. For example, compression can decrease image and video fidelity, creating a down-level experience that often upsets subscribers.
Some optimization solutions introduce compatibility issues within the network. Optimization solutions that create "tunneled" connections can often disrupt the implementation of deep packet inspection (DPI) and policy strategies. For example, a DPI solution that has been deployed to differentiate and manage network traffic may not be able to process some compressed or "tunneled" connections. There are certainly "workarounds" to manage some of these challenges, but these illustrate the growing complexity and interdependencies of deploying different technologies to address congestion.
Another method to address issues with the overflow of mobile data is the migration to LTE. While this solution may enable faster download speeds and has greater capacity, many experts warn that the benefits of LTE may not be instant. In addition, the cost to deploy LTE is very high. Because 2G and 3G frequencies cannot host LTE, governments will need to sell new frequency bands - a process that can be long and complicated.
A Solution at the Edge
Network-edge intelligence enables transparent transport layer optimization, which has the ability to address inefficiencies that transmission control protocol (TCP) introduces on wireless networks. It can accelerate data sessions, which would enhance network resources, and also help with congestion by increasing utilization. Perhaps more important, the solution can be deployed as a truly transparent, layer-4 implementation - which means it will complement other optimization solutions and provide additive increases in efficiency. TCP also allows for interworking with network intelligence solutions such as DPI, policy and even compression. The net result is an efficient solution for managing congested networks that can be deployed quickly with no negative subscriber impact.
Optimization is only one example of leveraging intelligence at the network edge. There is much more that can be achieved, including enhancing DPI systems, more efficient policy enforcement, and the collection of additional network information. With a grand deployment presented by the FCC's proposal, and the predicted growth in mobile data networks, massive congestion is a real possibility. Globally, operators are beginning to see the advantage of turning to software and the very devices that are creating the problem into the basis of an eloquent solution.
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