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RUCKUS EquiFlex helps boost network capacity, especially in high-density environments
Frequent communications between access points (APs) and clients about management traffic can burden a network to the point where network capacity is reduced.
For example, when clients actively scan for available APs, access points must respond to these probe requests regardless of whether they’re the closest AP. When enough clients request and all nearby APs respond, management traffic can needlessly consume network bandwidth and reduce the amount of available airtime for clients that are already connected.
EquiFlex leverages the power of AI to intelligently reduce this type of network congestion. The smart evolution of RUCKUS Airtime Decongestion, EquiFlex is managed through IntentAI to address these connection requests, delivering as much as 20% improvement in connection outcomes for clients.
运作方式
Focusing on pertinent communications
EquiFlex works by empowering every AP with localized data on RF conditions and the status of its neighboring APs. A machine learning model runs on every AP to determine which probe requests it should respond to and which it should ignore. For example, an AP may choose to ignore a probe request because it has determined a neighboring AP to be better suited to respond based on relative signal strengths.
Leveraging advanced algorithms
EquiFlex employs a machine learning architecture referred to as hybrid federated machine learning (HFML) that utilizes a cutting-edge method of merging both centralized and edge-deployed machine learning models working in concert. The result is dramatically improved and more intelligently managed probe responses, thereby freeing up network capacity for data traffic without reducing the ability for legitimate client connections.
优点
Better client connections
In high-density environments, such as sports stadiums or other large public venues, connecting to the network can become a waiting game. EquiFlex helps improve the connection experience by managing the enormous flood of management traffic occurring simultaneously from hundreds or thousands of clients. Connected clients experience better signal strength, which translates to higher throughput.
Improved user experience
By reducing management traffic overhead, more network capacity becomes available for connected clients and applications. This, in turn, minimizes potential latencies due to congestion, improving the overall user experience.
Lower OpEx
EquiFlex manages client connections across the entire network, requiring little to no human intervention. Prior to EquiFlex, the admin would have to set RSSI thresholds for all APs across the whole network. For networks with hundreds or thousands of APs, this would be difficult to manage. EquiFlex reduces the IT burden of optimizing the network for reducing management frame traffic.
Discover the power of EquiFlex
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常见问题解答
RUCKUS EquiFlex is a technology that leverages AI to intelligently manage network traffic, particularly in high-density environments. It reduces unnecessary management traffic, freeing up network capacity for data traffic and improving connection outcomes for clients.
HFML is an advanced machine learning architecture used by EquiFlex that combines centralized and edge-deployed models. This approach enhances the management of probe responses, improving network capacity and client connection quality.
Integrating EquiFlex into existing infrastructure delivers cost-saving benefits by optimizing resource allocation, reducing network congestion, and decreasing maintenance costs. It boosts network efficiency, cutting operational expenses and enhancing performance. EquiFlex’s scalability reduces the need for costly hardware upgrades, providing a future-proof solution for expanding network requirements.