Hybrid cloud and edge architecture to support multi-gigabit, low-latency environments

Market_trends

Hybrid cloud and edge architecture to support multi-gigabit, low-latency environments

Market_trends

How can a hybrid cloud and edge architecture support multi-gigabit, low-latency environments? Hear from Scott Stinson, our Head of Business Americas who joined a panel discussion at the CONNECTIONS session by Parks Associates.

Moving data and intelligence into the cloud can bring advantages to both the customer and service provider. From a customer point of view, new features and experiences can be provided that can only be created through cloud functionality – cloud backup would be a simple example. For service providers the cloud can bring cost savings by reducing the complexity of CPE, enable quicker time to market for new applications, as well as other operational efficiency benefits generated by cloud data analytics.

Due to such advantages, there have been growing calls over the years for greater and greater intelligence to be placed into the cloud, in some scenarios going as far as removing the need for CPE altogether, or at least reducing this to very basic connectivity devices. However, although cloud brings certain advantages, shifting all intelligence into the cloud also has its drawbacks. By utilizing more of a hybrid approach, maximizing both CPE and cloud functionality, numerous benefits can be realized, including:

  • Responsiveness. Storing intelligence and data for time-critical applications locally can reduce network latency and thus maximize the customer experience
  • Scalability and efficient use of cloud. It provides greater, more efficient use of cloud resources by making use of local CPE functionality where cloud capability is not required
  • Reliability. By placing specific intelligence locally, critical functions can continue to work, even when the broadband connection is down
  • Sustainability. Energy efficiency can be maximized by keeping some communications local and utilizing embedded processing
  • Privacy. Consumers have become wary of having all their data stored in the cloud, and thus enabling more sensitive data to be stored locally will reassure consumers and maintain trust.

When it comes to its Smart Wi-Fi platform, therefore, Airties’ approach is to split the functionality across the cloud and edge platforms – utilizing the cloud for AI data analytics that monitor and optimize the overall Wi-Fi experience, and then real-time edge software to provide a centralized controller for the home-wide network. This can then be used to optimize the data collection as well as providing real-time client roaming, mesh topology optimization, and QoS management.