Telecom vendors and operators are extensively focusing on 5G and IoT. The aggressive push to commercialize 5G services requires the development of emerging technologies to help transform networks toward more operational improvement and efficiency. The networks need to be more intelligent, flexible, reliable, and scalable to handle exponential growth in connected devices, while maintaining very low latency that is required in many of today’s and future IoT and 5G related applications, such as autonomous and connected vehicles.

The concept of Edge Computing is becoming a reality now and is an important component of such intelligent, advanced and complex networks.

“Interactor” with its patented platform for Edge Computing, provides data processing, protocol translation, process automation, advanced execution logic and easy interface and integration at the edge of the network. This makes Interactor a real market differentiator to any of existing and future cutting-edge technology solutions. It provides capabilities that eliminate technology silos and optimizing operations by simplifying interoperability between devices, network equipment, and systems.

Data Modeling

Collect data in real-time, or the server where collected data is provided

  • Input data is streaming data from multiple network elements
  • Data can be in any format, standard or custom. Interactor capable of handling it
  • Data is filtered and sorted per user specification (per NE, NE type, application or use case dependent)
    Ex. type of Network Element, Router, Server, Base Station, Optical Switch, etc.
    Data is modeled for further processing

Data Normalization and Aggregation

  • Analyze, Filter and Normalize data based on expected output model/format, schema and model identification keys

Apply solution logic and applicable policy and rules

  • Apply the solution logic, business logic and any client-specific policy to map and create the output data in the expected format. Interactor has the capability to handle complex scenarios, as well as the speed and scalability that is required for large and multi-vendor networks

Application and Data Output

  • Output the final data or data model to any user-defined application/server
  • Create API and make data available in northbound Interface for external application/systems (OSS/BSS)
Analytics, Predictive Analytics

Collect data in real-time, or the server where collected data is provided

  • Input data is streaming data from multiple network elements
  • Data can be in any format, standard or custom. Interactor capable of handling it
  • Data is filtered and sorted per user specification (per NE, NE type, application or use case dependent)
    Ex. type of Network Element, Router, Server, Base Station, Optical Switch, etc.
    Ex. Data, service assurance data, network configuration data
    Data is modeled for further processing

Data Normalization and Aggregation for analytics and predictive analytics

  • Analyze, Filter and Normalize data, and where needed, aggregate data to a more relevant performance indicator
  • Apply solution logic, business logic and applicable policy and rules for the analytics solution
    Ex. Correlate real-time performance data with historical data (readable from data base)
  • The policy could be a defined threshold (based on historical data) for expected variance (range) in the value of current performance data
    Rule ex. If the current value is outside the expected range, notification/alarm needs to be prepared to check the system, and/or an indication created for the operations team for follow up or fixing the issue

Application and Data Output

  • Realtime and Historical performance Data (and expected rage) for each NE, or for NEs located in a defined geographical area can be sent to a dashboard for visualization. Also stored in the database.
  • Data is sent to other telco services (managed services,…)
  • APIs are created for use by any application/systems (OSS/BSS)