Fair Resource Allocation for 5G Virtualized Network Slices
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Solution Overview
Problem
5G wireless networks face challenges in dynamically managing resources across virtualized network slices without disrupting traffic flows, as existing methods often require creating or terminating computing instances, which can disrupt network traffic and are inefficient in resource allocation.
Innovation Solution
A method and system for fair resource allocation in 5G networks using a fairness algorithm to adjust resource allocations for virtual computing instances based on demand and weights of network slices, allowing for dynamic growth or shrinkage of computing instances on existing servers to prioritize traffic loads, thereby optimizing resource distribution without disrupting traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If computing instances are created or terminated to manage resources across virtualized network slices, then resource allocation flexibility is improved, but network traffic disruption increases
Solution Approach 1:
The patent implements dynamic resource allocation by allowing computing instances to grow or shrink their resource capacity continuously based on real-time demand, rather than creating or terminating instances. This dynamic adjustment mechanism enables resource flexibility while maintaining instance continuity, thus preventing traffic disruption.
Solution Approach 2:
The system changes resource allocation parameters (CPU, memory, storage) of existing computing instances dynamically based on demand signals from network slices. By adjusting parameters rather than instance count, the system achieves adaptability while maintaining service continuity and avoiding traffic disruption.
2Productivity
If resource allocations are adjusted dynamically based on demand, then resource utilization efficiency is improved, but system complexity increases
Solution Approach 1:
The patent employs a feedback mechanism where demand signals from network slices are continuously monitored and fed back to the resource allocation system. This feedback loop enables automatic dynamic adjustment of resource allocations, improving utilization efficiency while the automated nature of the system prevents complexity from becoming unmanageable.
Solution Approach 2:
The resource allocation system operates autonomously by automatically detecting demand changes and adjusting resource allocations without manual intervention. This self-service capability improves efficiency through continuous optimization while reducing operational complexity by eliminating the need for complex manual management procedures.
3Reliability
If fairness algorithms are used to allocate resources across multiple network slices, then allocation fairness is improved, but computational overhead increases
Solution Approach 1:
The patent applies fairness algorithms selectively and incrementally, adjusting resource allocations in small steps rather than performing complete reallocations. This partial action approach maintains fairness while reducing computational overhead and processing time by avoiding exhaustive calculations for every allocation change.
Data Source
AI summary
A system and method for fair resource allocation includes a method. The method includes determining demand for a plurality of communications features of a network. The method further includes determining resource allocations for virtual computing instances hosted by a plurality of servers. The virtual computing instances serve the communications features. The method further includes adjusting the resource allocations for the virtual computing instances according to the demand for the communications features and a fairness algorithm.