Network Device Provisioning via Connectivity Type Lookup
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Solution Overview
Problem
Determining the complete set of parameters for network devices in a service provider network to establish secure and reliable connectivity with an external network is time-consuming, complex, and often inaccurate, requiring a large quantity of manual input such as access type, encapsulation type, data transmission speed, and Quality of Service (QoS) parameters.
Innovation Solution
A system and method that determines a complete set of provisioning parameters for network devices based on a reduced set of information received from a party associated with the external network, using a network connectivity type to automatically provision network devices, thereby reducing the need for manual determination and improving accuracy and speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual determination of complete provisioning parameters is used, then accuracy of network device provisioning can be maintained, but time consumption and complexity increase significantly
Solution Approach 1:
The system enables self-service provisioning by automatically determining the complete set of provisioning parameters using a reduced set of input parameters and a lookup mechanism. The network device autonomously queries the network for connectivity type information and assembles the complete provisioning parameters without manual intervention, thereby reducing both time consumption and process complexity while maintaining accuracy.
Solution Approach 2:
The system performs preliminary action by pre-configuring the relationship between reduced parameters and complete provisioning parameters in a lookup table or database. This preliminary structuring of information allows the network device to quickly retrieve and assemble complete provisioning parameters during the actual provisioning process, significantly reducing time consumption and complexity while ensuring accuracy through pre-validated parameter sets.
2Measurement precision
If manual determination of provisioning parameters is used, then completeness of parameters can be ensured, but accuracy decreases due to human error
Solution Approach 1:
The system replaces the mechanical human manual determination process with an automated electronic system. The network device automatically queries the network for connectivity type information, retrieves the corresponding complete set of provisioning parameters from a predefined set, and configures the network devices without human intervention. This substitution eliminates human error while maintaining parameter completeness and significantly reducing determination time.
Solution Approach 2:
The system uses copying by maintaining a predefined set of accurate provisioning parameters associated with different connectivity types. Instead of manually determining parameters each time, the system copies the appropriate pre-validated parameter set from the predefined collection based on the detected connectivity type, ensuring accuracy through replication of proven configurations while reducing time consumption.
3Productivity
If a reduced set of provisioning information is used, then provisioning speed increases, but the quantity of information available for configuration decreases
Solution Approach 1:
The system applies segmentation by dividing the provisioning information into two distinct layers: a reduced set of input parameters provided by the customer (e.g., connectivity type) and a complete set of provisioning parameters retrieved from the network. This segmentation allows the customer to provide minimal information while the system automatically supplements it with the complete configuration data needed for provisioning, thereby increasing speed without sacrificing completeness.
Solution Approach 2:
The system transitions from a single-dimension manual provisioning approach to a multi-dimensional automated approach. By adding the dimension of automatic network querying and parameter retrieval, the system enables the network device to obtain complete provisioning information from multiple sources (customer input + network database) based on a reduced initial input, thus increasing provisioning speed while maintaining full information availability through dimensional expansion of the information gathering process.
Data Source
AI summary
A device may receive a request to establish a connection between a first device and a second device. The request may include information identifying a network connectivity type. The device may determine one or more network devices to provision based on the network connectivity type; determine, based on the network connectivity type, provisioning parameters used to provision the one or more network devices; and provision the one or more network devices in accordance with the provisioning parameters to establish the connection between the first device and the second device.