Control Plane Task Distribution for Mobile Network Services
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Solution Overview
Problem
Existing methods struggle to efficiently distribute computational and communication resources across multiple devices, including mobile terminals, cloud devices, and network components, to provide high-quality communication and computing services, especially for resource-intensive applications like AI and augmented reality.
Innovation Solution
A method involving control plane functions in a mobile communication network that receives computational and communication availability information, selects a service provision profile for task distribution between mobile terminals, other computing devices, and network devices, and requests the necessary resources from distributed computing management and user plane components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If computational tasks are processed only on mobile terminal, then device complexity is reduced, but computational power and energy efficiency deteriorate due to limited computational resources
Solution Approach 1:
The patent segments the computational tasks of the communication and computing service into multiple parts that can be distributed across different devices. The control plane function divides task execution between the mobile terminal, other computing devices, and network devices based on their respective computational capabilities and availability, allowing each device to handle appropriate portions of the workload.
Solution Approach 2:
The patent transitions from a single-device processing model to a multi-dimensional distributed processing architecture. By introducing spatial distribution across multiple devices and network components, the system achieves higher computational power while managing complexity through coordinated resource allocation rather than concentrating all processing in one device.
2Power
If computational tasks are distributed over multiple devices including cloud devices, then computational power is improved, but resource coordination complexity worsens
Solution Approach 1:
The patent introduces a control plane function as an intermediary that coordinates resource allocation and task distribution among multiple computing devices. This mediator receives computational availability information from various devices, determines optimal task distribution, and manages the coordination complexity centrally, preventing the system from becoming unmanageably complex while still leveraging distributed computational power.
Solution Approach 2:
The patent dynamically adjusts task distribution parameters based on computational availability information received from different devices. By changing the allocation parameters according to real-time device capabilities and resource availability, the system optimizes computational power utilization while adapting to varying system conditions without requiring complex static coordination mechanisms.
3Use of energy by moving object
If tasks are distributed between mobile terminal and cloud devices, then energy efficiency is improved, but communication overhead increases
Solution Approach 1:
The patent applies local quality by executing certain computational tasks locally on the mobile terminal when energy efficiency is prioritized, while offloading other tasks to cloud devices when computational power is more critical. The control plane function determines the optimal location for each task based on service requirements, device capabilities, and current system state, balancing energy consumption against communication overhead on a per-task basis.
4Loss of time
If service provision is optimized for low latency, then communication quality is improved, but energy consumption worsens
Solution Approach 1:
The patent implements dynamic service provision profiles that can be adjusted based on current system conditions and service requirements. The control plane function selects between different task distribution strategies - using profiles that prioritize low latency when communication quality is critical, and profiles that prioritize energy efficiency when power consumption is the main concern. This dynamic adaptation allows the system to optimize for different objectives depending on the specific service context.
Data Source
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AI summary
According to various embodiments, a method for providing a communication and computing service session is described, comprising receiving, by the one or more control plane functions, computational availability information including, communication availability information including information and selecting a service provision profile which specifies a distribution of tasks of the communication and computing service between a mobile terminal, one or more other computing devices and one or more devices of the mobile communication network depending on the computational availability information and the communication availability information.