Joint RAN, Core, and Cloud Resource Scheduling for V2X Services
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Solution Overview
Problem
Existing communication network solutions fail to jointly optimize radio access networks, core networks, and cloud resources, leading to inefficiencies and misutilization in handling services with time or spatial constraints, particularly in vehicle-to-everything (V2X) scenarios.
Innovation Solution
A method for scheduling network resources that considers joint optimization of radio access networks, core networks, and cloud resources by integrating service managers with RAN, CN, and cloud managers to determine optimal resource allocation based on availability and constraints, using optimization algorithms and cost functions to minimize impact on other network traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If separate management of RAN, CN, and cloud resources is used, then each component can be managed independently, but resource utilization efficiency deteriorates and bottlenecks occur
Solution Approach 1:
The patent merges separate RAN manager, CN manager, and cloud manager into a unified joint management framework. The service manager coordinates resource allocation across all three network components simultaneously, enabling holistic optimization of resource utilization while maintaining manageable complexity through structured interaction protocols.
2Productivity
If joint optimization of RAN, CN, and cloud resources is implemented, then resource utilization efficiency improves, but system complexity increases
Solution Approach 1:
The service manager acts as an intermediary that receives service requests, coordinates with RAN, CN, and cloud managers, and allocates resources jointly. This mediator approach enables complex joint optimization while shielding individual components from the full complexity of cross-domain coordination.
Solution Approach 2:
The joint optimization system is segmented into distinct manager entities (service manager, RAN manager, CN manager, cloud manager) with defined responsibilities. Each manager handles specific resource types while participating in coordinated decision-making, breaking down system complexity into manageable segments.
3Reliability
If resources are allocated without considering time and spatial constraints, then allocation simplicity is maintained, but service fulfillment reliability deteriorates
Solution Approach 1:
The system incorporates time and spatial constraints as explicit parameters in the resource allocation decision process. The service manager evaluates constraints such as service time windows, geographic coverage areas, and traffic conditions to dynamically adjust resource allocation, ensuring reliable service fulfillment while managing complexity through parameter-based control.
Data Source
AI summary
Methods and apparatus are disclosed, including in one example a method for scheduling resources, associated with a plurality of components of a communication network, for providing a network service to a user equipment (UE). The method comprises receiving a service request for providing the network service, wherein the service request includes one or more service constraints. The method also comprises, for each of the plurality of network components, determining component resources that are needed to fulfill the service request according to the service constraints, sending, to a manager function associated with the particular component, a resource request that includes identification of the determined component resources and information related to the service constraints, and receiving, from the manager function, service information associated with the particular component. The method also includes, based on the service information and a cost function, determining a resource schedule for the plurality of network components that fulfils the service request.