NFV PGW Routing for Mobile Network Capacity Optimization
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Solution Overview
Problem
Traditional mobile network capacity expansion methods lead to increased capital and operational expenses due to the need for additional physical infrastructure, as legacy equipment is designed with fixed capacity ratios, resulting in underutilization of other dimensions despite some resources being underutilized.
Innovation Solution
Implementing Network Function Virtualization (NFV) platforms with different capability and cost characteristics to direct users based on their usage patterns, allowing for optimized resource allocation and balancing of capacity usage across various dimensions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If additional physical infrastructure is added when a resource is at capacity, then the network capacity is expanded, but capital and operational expenses increase
Solution Approach 1:
The patent applies universality by making the PGW capable of multiple functions - it can dynamically switch between serving as a traditional PGW and an NFV PGW based on user requirements. This allows a single physical infrastructure to handle both traditional and virtualized network functions, eliminating the need for separate dedicated infrastructure for each function type and reducing overall capital expenses.
Solution Approach 2:
The patent implements dynamics by enabling the PGW to dynamically adapt its capacity allocation based on real-time user demands and resource utilization. The system can flexibly allocate resources between different network functions and user types, optimizing capacity utilization without requiring over-provisioning for peak loads, thereby reducing operational expenses.
2Adaptability or versatility
If legacy PGW with fixed capacity ratios is used, then device complexity is reduced, but adaptability to different user demands deteriorates
Solution Approach 1:
The PGW is designed with multi-functionality to serve both traditional and NFV roles within a single device. This universal design allows the system to adapt to different user demands without requiring separate specialized devices, thereby improving adaptability while actually simplifying the overall network architecture by reducing the number of different device types needed.
Solution Approach 2:
The system changes operational parameters dynamically by adjusting capacity allocation ratios based on user type and demand patterns. Instead of requiring different hardware configurations for different user types, the system achieves adaptability through software-based parameter adjustments, maintaining device simplicity while improving versatility.
3Adaptability or versatility
If NFV PGW with configurable capacity is deployed, then adaptability to user demands is improved, but device complexity increases
Solution Approach 1:
The patent merges the traditional PGW and NFV PGW functionalities into a single unified device. This consolidation combines the configuration management and virtualization capabilities with the existing PGW infrastructure, achieving high adaptability without the need for completely separate complex NFV infrastructure, thereby controlling device complexity.
Solution Approach 2:
The system introduces an intermediary configuration manager that handles the complexity of NFV capacity allocation and virtualization resource management. This intermediary component abstracts the complexity from the core PGW functions, allowing configurable capacity and adaptability while managing device complexity through a dedicated management layer.
4Productivity
If physical equipment with fixed capacity ratios is used, then ease of manufacture is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The system implements dynamic resource allocation that allows a single standardized PGW device to adapt its capacity ratios based on real-time user demands. This dynamic capability achieves high resource utilization efficiency without requiring multiple specialized device types, thereby maintaining ease of manufacture through standardized hardware while improving productivity through flexible software-based resource management.
Data Source
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AI summary
Systems and methods of optimizing capacity of network equipment in mobile networks. A computing device receives a user identification and a user attribute, the user identification corresponding to a characteristic of the mobile network user, the user attribute corresponding to at least one characteristic of mobile network usage by the mobile network user. The computing device generates a usage prediction based on the user identification and the user attribute, the usage prediction including information corresponding to anticipated future data usage of the mobile network user, the anticipated future mobile network usage corresponding to at least one mobile resource. The computing device transmits the usage prediction to a serving gateway (SGW) such that the SGW routes the mobile network user to one of a legacy packet data network gateway (PGW) and a network function virtualization (NFV) PGW based on the usage prediction.