Policy Decision Point Resource Reservation via Account Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing resource reservation procedures in communication charging fail to consider variations in user account data, leading to poor customization and potential service delivery failures due to insufficient account balances.
Innovation Solution
A method where a policy decision point interacts with a charging system to obtain account data, including balance and credit limits, to make resource reservation policies, and re-makes policies when account data thresholds are reached, ensuring resource reservations are adjusted accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the PDP makes resource reservation policy in a fixed manner without considering account data variations, then the policy making process is simple, but the service delivery reliability deteriorates due to insufficient account balance
Solution Approach 1:
The PDP performs preliminary actions by proactively obtaining account data from the charging system before making resource reservation policies. This allows the system to anticipate potential charging failures and adjust policies in advance, improving service delivery reliability without adding complex real-time monitoring mechanisms
Solution Approach 2:
The system establishes a feedback loop where the PDP continuously monitors account data variations and receives notifications from the charging system. When account data changes exceed a threshold, the PDP re-evaluates and updates resource reservation policies, ensuring reliability while maintaining manageable complexity through event-driven updates
2Loss of information
If the PDP interacts with the charging system to obtain account data, then the resource reservation information becomes more comprehensive, but the system complexity increases
Solution Approach 1:
The PDP acts as an intermediary between the network element and the charging system. It obtains account data from the charging system through standardized interfaces, processes this information to determine policy adjustments, and then applies the policies at the network element. This intermediary role consolidates complexity in a single component while ensuring comprehensive information flow
Solution Approach 2:
The system monitors changes in account data parameters (such as balance thresholds) and triggers policy re-evaluation only when significant changes occur. This parameter-change-driven approach ensures comprehensive information utilization while avoiding unnecessary policy updates that would increase system complexity
3Adaptability or versatility
If the PDP re-makes resource reservation policy when account data varies, then the customization for users improves, but the processing time increases
Solution Approach 1:
The system implements periodic policy evaluation triggered by account data threshold notifications from the charging system, rather than continuous monitoring. This event-driven periodic action allows the PDP to re-make resource reservation policies only when necessary (when account data varies significantly), improving service customization while minimizing unnecessary processing time
Solution Approach 2:
The resource reservation policy becomes dynamic, adapting to user account data variations in real-time through automated threshold-based triggers. The system adjusts policy parameters (such as resource limits or service quality levels) based on current account status, providing personalized customization without requiring manual intervention or excessive processing time
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
A method for resource reservation, a method for handling a charging failure and a policy decision point are disclosed. A network element receives a service request of a user, and requests a resource reservation policy from the policy decision point. The policy decision point makes a resource reservation policy according to the account data of the user and returns the resource reservation policy to the network element. The network element executes the resource reservation policy and performs the resource reservation for the user. Because the policy decision point performs the resource reservation according to the account data of the user, the impact on the service provision due to the reason that the prior art does not take the variation in user's account data into consideration may be avoided. The information for resource reservation may be more comprehensive and the resource reservation procedure may be more customer-friendly.