Proximal Computing Capability Table for Cloud RAN Resource Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current communication networks face challenges in efficiently managing computing resources across cloud-based Radio Access Network (RAN) entities, particularly in terms of computing capability and availability, which hinders effective offloading and handover decisions for applications with high computing and low latency requirements.
Innovation Solution
The introduction of a proximal computing capability and availability table, which is a neighbor relation table based on the capability and current availability of computing resources, allows for the derivation and provision of dynamic information about nearby cloud-based RAN entities, enabling informed offloading and handover decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If computing resources are distributed across multiple cloud-based RAN entities, then resource utilization and application mobility are improved, but the complexity of managing computing capability and availability information increases
Solution Approach 1:
The patent introduces a proximity analysis function and capability table as an intermediary mechanism that automatically collects, analyzes, and stores computing resource information from multiple cloud-based RAN entities. This mediator handles the complexity of distributed resource management, allowing applications to benefit from improved mobility and resource utilization without directly dealing with the underlying management complexity.
Solution Approach 2:
The system performs preliminary analysis of computing capability and availability information before applications need to make offloading or handover decisions. By pre-processing and storing this information in structured tables, the system eliminates the need for complex real-time queries during critical decision moments, thus improving application mobility while managing complexity through advance preparation.
2Reliability
If real-time computing resource information is tracked across proximal RAN entities, then offloading and handover decisions are improved, but the information retrieval and processing overhead increases
Solution Approach 1:
The proximity analysis function performs preliminary collection and organization of computing resource information, storing it in structured capability tables. This advance preparation ensures that when offloading or handover decisions are needed, the information is already processed and readily available, improving decision accuracy without incurring real-time processing overhead.
Solution Approach 2:
The system dynamically updates the capability tables with current computing resource information, balancing the need for real-time accuracy with processing efficiency. By maintaining updated but not continuously queried information, the system achieves reliable offloading decisions while avoiding excessive information retrieval overhead.
3Measurement precision
If detailed capability analysis of computing resource types is performed, then resource matching for specific applications is improved, but the computational overhead for analysis increases
Solution Approach 1:
The patent segments computing resources into distinct resource types with specific capabilities, organizing them in structured tables. This segmentation allows the system to perform detailed capability analysis only when needed for specific application requirements, rather than continuously analyzing all resources. The segmented organization enables precise resource matching while reducing overall computational overhead through selective analysis.
Data Source
AI summary
A method includes retrieving information comprising at least one of configuration management, CM, data and performance management, PM, data of predetermined cloud based Radio Access network, RAN, entities or functions, or resource types in the predetermined cloud based RAN entities or functions, or capabilities of resource types in the predetermined cloud based RAN entities or functions, or location information of the predetermined cloud based RAN entities or functions; from the retrieved information and from among the predetermined cloud based RAN entities or functions, deriving a proximal computing capability table for a source cloud based RAN entity or function in a proximity of target cloud based RAN entities or functions, the derivation based on a proximity analysis; and providing the derived proximal computing capability table, wherein the proximal computing capability table is a neighbour relation table.