Computing Task Allocation Using Node and Network Status
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Solution Overview
Problem
Existing MEC networks improperly allocate computing tasks, leading to inefficiencies in computing load management, particularly for services like VR, AR, and AI inference.
Innovation Solution
A computing task processing method that determines target computing nodes by considering task requirements, node computing power status, and network status, enabling proper task allocation through a management unit deployed at various levels, including terminal devices, access networks, and core networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If computing tasks are directly allocated to available computing nodes without comprehensive analysis, then task allocation speed is improved, but task allocation accuracy deteriorates
Solution Approach 1:
The management unit pre-collects and maintains computing power status information, network status information, and task requirement information before actual task allocation occurs. This preliminary preparation enables rapid accurate allocation when tasks arrive, resolving the contradiction between allocation speed and accuracy.
Solution Approach 2:
The system continuously monitors computing node status and task execution outcomes, using this feedback to dynamically adjust task allocation decisions. This ensures both timely response to current conditions and accurate matching of tasks to suitable nodes.
2Measurement precision
If comprehensive analysis of task requirements and node status is performed, then task allocation accuracy is improved, but system complexity increases
Solution Approach 1:
The allocation system is divided into distinct functional modules: a collection unit for gathering status and requirement information, a determination unit for analyzing and matching tasks to nodes, and an allocation unit for executing assignments. This segmentation manages complexity while maintaining comprehensive analysis capabilities.
Solution Approach 2:
The management unit acts as an intermediary between computing nodes and task sources, centralizing the complex analysis and decision-making processes. This intermediary approach simplifies the overall system architecture by consolidating complexity in a dedicated management layer.
3Ease of operation
If computing tasks are allocated without considering network status, then allocation simplicity is maintained, but task execution efficiency deteriorates
Solution Approach 1:
Network status information is collected and evaluated in advance before task allocation decisions are made. This preliminary assessment of network conditions enables the system to simple yet informed allocation decisions that account for transmission efficiency.
Solution Approach 2:
The system dynamically adjusts task allocation based on changing network status parameters, such as bandwidth availability and latency. By monitoring and responding to these parameter changes, the system maintains simple allocation procedures while adapting to network conditions that affect execution efficiency.
Data Source
AI summary
The technology of this application includes a management unit that determines, based on task requirement information and/or task characteristic information of N computing tasks and a computing power status and/or a network status of at least one computing node, one or more target computing nodes in the at least one computing node and at least one computing task to be executed by each target computing node, where Nis an integer greater than or equal to 1. The management unit sends identification information of the corresponding at least one computing task to each target computing node in the one or more target computing nodes. During computing task allocation, the task requirement information and/or the task characteristic information, and the computing power status and/or the network status of the at least one computing node are comprehensively considered, which helps make computing task allocation more proper.