ALU Identifies the Chatty Mobile Apps

A new report by Alcatel-Lucent ",, examines the impact of leading mobile applications on service provider networks and on consumers’ data plan and device battery life .. The rankings in this report are derived from mobile network analytics provided by the Alcatel-Lucent Wireless Network Guardian [see "Softbank [Japan] Uses ALU for Better QoE" - here]. All measurements are based on actual app usage by more than 15 million subscribers on live 3G mobile networks in North America, APAC and the Middle East"

Key findings:

• Apps that impact the network due to their high data volume — a group that includes most video apps, along with iTunes®, Instagram, Pinterest, Apple Maps and Pandora — are targets for bandwidth optimization. One service provider reduced cell utilization by an average of 20% after introducing selective traffic optimization.
   
• The apps with the biggest impact on the consumer data plan are YouTube, Netflix, Facebook Video, Pandora and Video on Instagram.
   
• The apps in the High Signaling quadrant are perfect candidates for code design optimization aimed at reducing the number of times the device and network must establish communications
  
  
  

Bandwidth optimization success story: Selective traffic optimization

A service provider knew that the key to managing traffic cost was to manage the peak hour. The peak hour drives CAPEX investment, so logic dictated that reducing the load at that critical time would reduce the need for investment. Studies of  peak-hour traffic revealed a surprising fact: that the typical heavy users were not active during this period. Each day, a different set of users topped the peak-hour volume chart. Throttling certain users during a certain period of the day would not help the service provider reduce utilization.

The service provider selected a two-part mechanism to optimize traffic. The first part involved using network analytics (specifically, an algorithm relying on utilization and subscriber QoE metrics) to determine when congestion occurred, relay the severity of the congestion, provide a list of subscribers currently attached to the cell, and rank these subscribers by data volume. The second component was to use a policy manager to decide whether specific users should be throttled, how many users should be throttled and for what period of time they should be throttled. The service provider reduced cell bandwidth  by an average of 20% and reduced the amount of time cells spent in congested state each day by 60%.

See "Alcatel-Lucent Mobile Application Ranking Report" (registration required) - here