Dynamic Virtual Network Function Assignment for Latency and Power Optimization
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Solution Overview
Problem
Current 5G networks face challenges in optimizing latency, power consumption, and quality of service due to the static assignment of virtualized network functions, which can lead to suboptimal performance in meeting varying requirements across different network slices.
Innovation Solution
Dynamic assignment of virtualized network functions across a data center hierarchy based on latency, power, and quality of service requirements, allowing for real-time reconfiguration of network slices to ensure optimal performance and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If virtualized network functions are assigned to computing resources in a centralized cloud location, then resource utilization and management efficiency are improved, but data communication latency increases
Solution Approach 1:
The patent segments virtualized network functions into different deployment locations within a data center hierarchy. Some VNFs are deployed at edge locations closer to user equipment for low-latency services, while others are centralized for resource efficiency. This segmentation allows the system to simultaneously achieve low latency for time-sensitive operations and high resource utilization for non-time-sensitive functions.
Solution Approach 2:
The patent applies local quality by deploying virtualized network functions at specific locations within the data center hierarchy based on service requirements. Edge-located VNFs provide fast local processing for latency-sensitive services, while centralized VNFs handle resource-intensive tasks. Each location has optimized qualities appropriate to its function, resolving the contradiction between centralized efficiency and distributed speed.
2Loss of time
If virtualized network functions are deployed at the edge of the network closer to user equipment, then data communication latency is reduced, but energy consumption of computing resources increases
Solution Approach 1:
The patent implements dynamic assignment of virtualized network functions to computing resources based on real-time requirements. When low latency is required, VNFs are dynamically deployed to edge locations; when energy efficiency is prioritized, VNFs are consolidated at centralized locations. This dynamic reconfiguration allows the system to adapt between latency optimization and energy conservation based on current operational needs.
Solution Approach 2:
The patent changes deployment parameters of virtualized network functions based on service requirements. For latency-sensitive services, VNFs are deployed with parameters optimized for speed (edge locations). For energy-efficient operations, parameters are adjusted to consolidate workloads at centralized locations with better cooling and power management. This parameter adjustment resolves the contradiction between latency reduction and energy consumption.
3Device complexity
If static assignment of virtualized network functions is used, then system complexity is reduced, but adaptability to varying network slice requirements deteriorates
Solution Approach 1:
The patent transitions from static to dynamic assignment of virtualized network functions. The system continuously monitors network slice requirements and dynamically reconfigures VNF deployment to match varying latency, power, and quality of service demands. This dynamic approach maintains adaptability while using automated algorithms to manage complexity, allowing the system to respond to changing requirements without proportionally increasing operational complexity.
Solution Approach 2:
The patent implements feedback mechanisms that monitor network slice performance and requirements in real-time. Based on this feedback, the system automatically adjusts virtualized network function assignments to optimize for the current set of requirements. This closed-loop control provides adaptability to varying demands while using automated feedback processing to prevent complexity from escalating, as the system self-regulates based on observed conditions.
Data Source
AI summary
Methods and apparatuses for improving telecommunications services using virtualized network functions are described. The virtualized network functions may be deployed across different data centers of a data center hierarchy that electrically connect one or more user devices with one or more data networks. A set of virtualized network functions may be assigned to computing resources within a particular data center based on latency requirements, power requirements, and/or quality of service requirements for one or more network slices supported by the set of virtualized network functions. The set of virtualized networks functions may include a set of shared core network functions that are shared by two or more network slices.