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Creating accurate forecasts depends on understanding how different phones and apps interact and how those interactions affect the network. Phone manufacturers make a variety of design decisions about, for instance, how the device will maintain its connection to a network or load an app. As a result, one phone may signal the network 60 percent more often than another running the same app.

Nokia Siemens runs tests to figure out the demands imposed by every combination of phone and app, then feeds those numbers into its predictive models. It also analyzes the packets of data being sent across networks to find out how many users with a particular phone run a particular app. All that helps project how sales of new phones and new apps will affect traffic.

Sheer demand isn’t the only source of traffic problems. Modelers must also account for failures in the network backbone—problems resulting from software glitches, fiber-optic cables that get cut by construction projects, or hackers launching denial-of-service attacks. Sometimes unusual things happen at the worst times. For several hours heading into so-called “Cyber Monday,” on November 29, many Comcast customers in the Northeast lost Internet access. The problem turned out to lie with Comcast’s domain name servers, which translate the website names that people type into their browsers into the strings of numbers that computers read.

Some fixes, like providing extra equipment, might be more reliable but more expensive, whereas adding certain software might be cheaper but might not protect against as many failures. Gordon Bolt, associate vice president of engineering at OPNET in Bethesda, Maryland, says his company’s predictive models can figure out which types of failure are more likely and suggest the most cost-effective combinations of protective measures.

Savioli believes that as more carriers start to understand the impact of smart phones, issues like dropped calls at football games will become a thing of the past. But he says predictive modeling will still be needed when the next new device or an as-yet-unknown application places new demands on the network. “We still have operators all around the world that have not changed what they’re doing, that haven’t accepted the paradigm of the smart phone,” he says. “I do believe that this problem we see now will be taken into account in the future. But what kinds of new problems we will see in the future, I cannot tell you.”

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Credit: OPNET

Tagged: Business, Business Impact, Predictive Modeling

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