Access Management Permission Scoring for NFS Conflict Reduction
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Solution Overview
Problem
In Network File Systems (NFS), the high time consumption of reclaiming access management permissions due to potential conflicts degrades server performance, especially when handling a large number of files, and existing solutions like machine learning are resource-intensive and time-consuming.
Innovation Solution
A method that calculates a current score for each file to determine the probability of conflicting access requests, assigning access management permissions only if the score is greater than or equal to a threshold, thereby avoiding high-conflict files and improving server performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If access management permissions are assigned to clients in NFS, then file sharing efficiency is improved, but server performance degrades due to high time consumption from reclaiming permissions caused by conflicts
Solution Approach 1:
The system calculates a conflict probability score for each file in advance, before permission assignment occurs. This preliminary scoring allows the server to predict which files are likely to generate conflicts and adjust permission assignment strategies accordingly, preventing time-consuming reclamation operations before they happen.
Solution Approach 2:
The system dynamically adjusts the permission assignment decision based on the conflict probability score parameter. By changing the assignment strategy according to the score threshold, the system optimizes the balance between file sharing efficiency and server performance, avoiding assignments that would lead to high time consumption.
2Measurement precision
If machine learning methods are used to predict access conflicts, then accuracy of conflict prediction is improved, but resource consumption and time cost increase
Solution Approach 1:
Instead of using complex machine learning models that consume significant resources, the system employs a lightweight scoring mechanism based on simple statistical calculations of historical access patterns. This disposable, low-cost approach provides sufficient prediction accuracy without the heavy resource overhead of traditional machine learning methods.
Solution Approach 2:
The system uses its own historical access data to generate conflict probability scores without requiring external machine learning models or additional training data. The scoring mechanism is self-contained and automatically adapts to the specific access patterns of the NFS system, eliminating the need for resource-intensive external prediction systems.
Data Source
AI summary
Techniques process an access management permission. Such techniques involve: receiving, from a client, a first request for obtaining an access management permission of a file. The techniques further involve: obtaining a current score of the file, wherein the current score indicates a probability of receiving, after the access management permission is assigned to the client, a second request conflicting with the first request. The techniques further involve: assigning the access management permission to the client if it is determined that the current score is greater than or equal to a threshold score. Such techniques alleviate the need to assign, to a client, the access management permission of a file with a high probability of an access conflict, thus enhancing the performance of the server as well as the user experience.