Abstract:
The disclosure provides activation of end to end virtual network services, along with various validations. This technology uses model driven architecture to convert the configurations to VNF/PNF specific commands and abstract the complexity of different types of syntax & command lines. This technology also provides test and diagnostic functionality including service connectivity check, performance, rate-limiting at each step of configuration at virtual infrastructure and functional level. Once the VNS is successfully applied, the configuration will be updated in database which can be referred for any future updates.
Abstract:
A method and/or system for Artificial Intelligence assisted service catalogue generation for network service provisioning is disclosed. The method comprising receiving input data which comprises either or combination of one or more specification documents or one or more configuration changes in network functions and/or network components. The entities and attributes of the entities are extracted from the input data which are then reconciled with graph database representing network function model to determine modifications in the input data. The graph database is updated based on the modifications identified in the input data, and recommendations comprising model elements are generated using AI engines which are displayed at the service modeler interface for generation of the service catalogue for network service provisioning.
Abstract:
A method, non-transitory computer readable medium and device that manage network elements include interacting with one or more network elements to determine one or more non-functional ones of the network elements. A network diagnostic information is obtained from the determined one or more non-functional network elements. Based on the obtained network diagnostic information, one or more snapshots of the determined one or more non-functional network elements are generated. The management server is provided with the generated one or more snapshots of the determined one or more non-functional network elements.
Abstract:
A method and/or system for Artificial Intelligence assisted service catalogue generation for network service provisioning is disclosed. The method comprising receiving input data which comprises either or combination of one or more specification documents or one or more configuration changes in network functions and/or network components. The entities and attributes of the entities are extracted from the input data which are then reconciled with graph database representing network function model to determine modifications in the input data. The graph database is updated based on the modifications identified in the input data, and recommendations comprising model elements are generated using AI engines which are displayed at the service modeler interface for generation of the service catalogue for network service provisioning.
Abstract:
Embodiments of the present disclosure discloses a method and an interoperability system. The present disclosure aims to provide interoperability between SD-WANs of different vendors. The interoperability system uses information from an agent (software or hardware) installed in network terminals such as routers of each SD-WAN to configure control and management plane signals and configures the agent associated with one SD-WAN to share data with agent associated with another SD-WAN. Therefore, the present disclosure helps in interoperability between SD-WANs from different vendors. Hence, operations are efficient, and cost is reduced.