Service Plan Design and Device Management via Automated Provisioning
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Solution Overview
Problem
Current systems for managing service user discovery and service launch on devices face challenges in efficiently provisioning and activating services, particularly in adapting to user preferences and network neutrality while ensuring privacy and security.
Innovation Solution
The development of a system that utilizes a device-assisted approach for service policy implementation, including automated device provisioning, adaptive ambient services, and secure data management, which integrates user preference management, network neutrality, and enhanced billing mechanisms to ensure seamless service delivery and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated device provisioning is implemented, then service delivery efficiency is improved, but system complexity increases
Solution Approach 1:
The system implements self-service provisioning where the device automatically discovers available services, selects appropriate service plans, and configures itself without manual intervention. The device agent autonomously interacts with the service provider system to complete provisioning, eliminating the need for complex manual configuration processes while maintaining high efficiency.
Solution Approach 2:
A device agent serves as an intermediary component that simplifies the interaction between the device and the service provider system. This agent handles the complexity of service discovery, selection, and provisioning processes, shielding the user from system complexity while enabling efficient automated service delivery.
2Adaptability or versatility
If adaptive ambient services are implemented, then user preference adaptation is improved, but processing requirements increase
Solution Approach 1:
The system implements partial adaptation by focusing on adapting only the most relevant service parameters based on user preferences and context, rather than attempting to adapt all possible service aspects. This selective approach maintains high adaptability while reducing unnecessary processing overhead and energy consumption.
Solution Approach 2:
User preferences and service configurations are pre-adapted based on historical data and typical usage patterns before actual service execution. This preliminary adaptation reduces real-time processing requirements while maintaining high adaptability to user preferences during service delivery.
3Reliability
If secure service launch mechanisms are implemented, then service security is improved, but authentication time increases
Solution Approach 1:
Security credentials and service permissions are pre-authenticated and cached during initial device provisioning or previous valid sessions. This preliminary authentication enables faster service launch while maintaining security, as the system can verify pre-stored credentials rather than performing full authentication cycles for each service launch.
Solution Approach 2:
The system creates and stores copies of authentication credentials and service tokens that can be rapidly verified without requiring repeated interaction with the authentication server. These credential copies enable fast service launch while maintaining security through cryptographic verification of the stored authentication data.
Data Source
AI summary
Disclosed herein are methods, systems, and apparatuses to enable subscribers of mobile wireless communication devices to view, research, select and customize service plans; to create and manage device groups, share and set permission controls for service plans among devices in device groups; to manage communication services through graphical user interfaces; to sponsor and promote service plans; and to design, manage, and control communication services through application programming interfaces.