Natural Language Processing Interface for Network Device Configuration
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Solution Overview
Problem
The complexity of managing and configuring multi-vendor networking equipment in data centers is exacerbated by the need for administrators to learn various vendor-specific command line interfaces and APIs, leading to increased costs and a significant learning curve, making it difficult to introduce new equipment and perform on-the-fly configuration changes efficiently.
Innovation Solution
A natural language processing (NLP) system is developed to provide a universal, easy, and vendor-agnostic interface for configuring and managing networking devices, using a lemmatization database and command template database to convert natural language inputs into proper CLI/API requests, allowing for a single point of administration across a network and enabling human-like interaction with devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If vendor-specific CLIs and APIs are used for configuring networking equipment, then device configuration capability is achieved, but the learning curve and operational complexity increase significantly
Solution Approach 1:
The patent introduces a natural language processing interface as an intermediary layer between the network administrator and vendor-specific CLIs/APIs. This mediator translates human-like language commands into the appropriate vendor-specific commands, eliminating the need for administrators to learn multiple proprietary interfaces while maintaining full device configuration capability.
Solution Approach 2:
The system creates a universal natural language interface that can interact with multiple vendor-specific devices through a single standardized method. This universal interface supports configuration and management of heterogeneous networking equipment from different vendors without requiring vendor-specific knowledge, achieving multi-vendor compatibility through a common communication paradigm.
2Adaptability or versatility
If multiple vendor-specific interfaces are learned and used, then comprehensive device management capability is achieved, but training costs and operational time increase
Solution Approach 1:
The natural language processing system serves as a mediator that handles the complexity of multiple vendor interfaces internally, allowing administrators to interact with all vendors through a single, consistent natural language interface. This eliminates the time required to learn and switch between multiple vendor-specific CLIs and APIs.
Solution Approach 2:
The system creates a simplified copy or abstraction of the complex vendor-specific interfaces through natural language commands. Instead of requiring users to master the actual proprietary command structures, the system captures their intent through natural language and translates it to the appropriate vendor commands, effectively copying the functionality through a more accessible interface.
3Reliability
If manual configuration methods are used for each device, then precise control is achieved, but efficiency and scalability decrease
Solution Approach 1:
The natural language processing system enables self-service configuration where administrators can independently configure devices using conversational commands without requiring manual step-by-step procedures or deep technical knowledge. The system handles the complexity of translation and execution automatically, maintaining precision while improving efficiency.
Solution Approach 2:
The NLP interface acts as an intelligent intermediary that receives high-level natural language instructions and automatically translates them into precise vendor-specific configuration commands. This mediator layer ensures that the simplicity of natural language input does not compromise the precision required for accurate device configuration.
Data Source
AI summary
Aspects of the present invention provide a more universal, easy, natural, and vendor-agnostic interface to configure, manage, and/or monitor devices in networks. In embodiments, a user-friendly natural language interface, such as a chat or messaging interface, may be used to “live chat” with one or more devices. In embodiments, a natural language input from a user intended for a target device is received and converted into one or more properly formed commands that are target-specific for the target device and may be executed by the target device. In embodiments, results from the execution of the one or more commands may be appropriately formatted for presentation to the user.


