Cloud Event Priority Computation for Dynamic Bandwidth Allocation
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Solution Overview
Problem
Existing methods for marking event priorities on cloud platforms are time-consuming and labor-intensive, especially for high-priority events, and it is difficult for applications to quickly assess urgency due to limited cloud resources and bandwidth.
Innovation Solution
A method for automatic priority computation on a cloud platform using descriptive priority descriptions to dynamically determine the priority of each event based on its type, allowing for differentiated transmission bandwidths and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual priority marking is performed for each event in cloud applications, then event priority can be accurately assigned, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system enables self-service by allowing event data to automatically determine its own priority level through predefined rules and algorithms. The cloud platform autonomously analyzes event characteristics (such as event type, source device, data characteristics) and assigns priorities without requiring manual intervention from application developers, thus resolving the contradiction between accurate priority assignment and time-consuming manual configuration
Solution Approach 2:
The patent replaces the mechanical manual process of priority marking with an automated computational system. Instead of developers manually assigning priorities, the system uses algorithms and predefined rules to automatically compute event priorities based on event characteristics, substituting human labor with automated processing while maintaining or improving assignment accuracy
2Loss of energy
If cloud resources and bandwidth are limited, then resource allocation becomes constrained, but ensuring timely delivery of urgent events becomes more difficult
Solution Approach 1:
The system applies local quality by allocating cloud resources and bandwidth differently based on event priority levels. High-priority events receive allocated bandwidth and computational resources to ensure timely processing and delivery, while low-priority events receive minimal resources. This differentiated resource allocation based on local event characteristics resolves the contradiction between limited resources and reliable urgent event delivery
Solution Approach 2:
The system changes resource allocation parameters dynamically based on event priority. Instead of uniform resource distribution, the system adjusts bandwidth allocation, processing power, and queue priorities as parameters according to the computed event priority levels, enabling efficient resource utilization while ensuring urgent events receive sufficient resources for timely delivery
3Ease of operation
If each application marks priorities one by one, then specific priority control is achieved, but the process becomes labor-intensive and difficult to scale
Solution Approach 1:
The system achieves universality by implementing a single automated priority marking service that serves multiple cloud applications simultaneously. Instead of each application requiring separate manual priority configuration, the universal system processes events from multiple applications through unified algorithms and rules, maintaining precise priority control while enabling scalable processing across numerous applications without proportional increase in labor
Data Source
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AI summary
The present disclosure relates to a method for configuring a priority level, a cloud platform, a system, a computing device, and a medium. The method for configuring a priority level for data on a cloud platform comprises : determining the data type of received data; determining, according to the data type, a priority level specification used for describing the priority level of the data; and calculating the priority level of the data on the basis of the priority level specification of the data.