Opanga Networks releases machine learning platform capable of identifying large data flows
Opanga Networks, an industry-leading provider of Big Software innovations for mobile network densification, announced the next-generation N2000, which will provide even greater financial efficiencies to mobile operators via a software update, enabled quickly within a maintenance window. N2000 is the lowest cost mobile capacity expansion in the world and the newest generation is increasing network efficiencies by an additional 50 percent.
Opanga’s N2000 is a machine learning platform capable of identifying large data flows such as video streams—Elephant Flows—and enabling them to self-organize intelligently in the mobile core, preventing them from overwhelming the wireless network. These video applications are the primary driver of RAN CAPEX, OPEX and network quality for mobile operators today.
“Operators need to embrace new strategies to densify their networks and maintain customer experience,” said Dave Gibbons, CEO, Opanga. “Big Software-enabled machine learning technology deployed in the mobile core is the answer. Most mobile operators are spending a lot of their shareholders’ money trying to absorb the impact of video on their networks by building more network. Software is a much more effective cure to the impact of video on mobile networks. Video is a software problem that is best addressed with a software solution.”
The Seattle-based company’s first-generation solution has been deployed globally in 3G and 4G networks, providing operators with vital network efficiency improvements, and will be equally applicable to operators who are paving the way for 5G. Operators have consistently measured on average a 50 percent increase in user throughput over existing network infrastructure where N2000 is deployed, and with this new release those increases reach up to 75 percent faster throughput.
“Our customers have launched N2000 and immediately reduced their network build plan,” said Gibbons. “They have realized keeping up with growing traffic demands and providing better experience and data speeds can be achieved in short order at massively lower costs using software intelligence in the mobile core.”
Opanga’s solution comes at a time when the market is ripe with inefficiency, creating the opportunity for competitive disruption by deploying machine learning Big Software. Traditional network deployment strategies to deal with traffic growth have been to add network infrastructure, sizing networks to current and expected traffic load by adding cell sites and deploying additional spectrum, which is both an expensive and time-consuming endeavor.
In an environment where ARPU is in decline while costs are on the rise, traditional strategies are unsustainable and CFOs are demanding CAPEX containment and EBITDA growth to satisfy stock valuation and dividend performance.
“Operators need to make their capital dollars go further by increasing the efficiency of their already deployed wireless network assets,” said Gibbons. “Our customers are becoming more and more focused on reducing CAPEX and the associated OPEX of the never-ending RAN build outs. They are demanding software solutions which allow more traffic to be delivered over the network and spectrum they have already deployed.”
As mobile operators shift their culture and mindset away from building bigger physical networks to using Big Software for managing data growth, they open the door to achieving next-level financial performance. Ultimately, Big Software supplants the “build bigger networks” strategy of the past and opens the door to massive efficiency gains and the financial benefits of CAPEX containment and EBITDA growth.