File Request Clustering for Distributed File Operation Scheduling
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Solution Overview
Problem
Existing distributed file systems inefficiently schedule file operation tasks, leading to increased network communication overhead and reduced performance due to the lack of consideration for operation properties and clustering opportunities.
Innovation Solution
Implementing a file request manager that clusters file operation requests based on operation type and storage system, reducing remote process calls and optimizing task scheduling by grouping requests with common properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If file operation requests are processed individually without clustering, then each request can be handled independently, but network communication overhead increases and system performance decreases
Solution Approach 1:
The patent merges multiple file operation requests into a single clustered request when they share common properties (same operation type, same storage system, same priority). This combining approach reduces the number of separate network communications required, thereby decreasing network overhead and improving overall system throughput while maintaining efficient resource utilization
2Loss of energy
If file operation requests are clustered together, then network communication overhead is reduced, but the complexity of request management increases
Solution Approach 1:
The patent changes the parameter of request grouping by clustering requests based on specific properties such as operation type, storage system, and priority level. This parameter-based clustering approach systematically organizes requests into manageable groups, reducing the complexity of request management while effectively minimizing network communication overhead through intelligent grouping
3Loss of time
If file operation requests are processed in parallel without optimization, then response time may be reduced, but resource utilization becomes inefficient
Solution Approach 1:
The patent applies dynamic scheduling by adjusting the processing strategy based on request properties. Requests with identical operation types and storage systems are clustered and processed together, while diverse requests are handled individually. This dynamic approach optimizes both response time and resource utilization efficiency by adapting the processing method to the specific characteristics of the request batch
Data Source
AI summary
A method includes receiving, by a data processing apparatus, a plurality of file operation requests, each file operation request including a priority, a deadline, and an operation type and representing a request to perform an operation on at least one file maintained in a distributed file system; identifying, by the data processing apparatus, a group of file operation requests to be executed together from the plurality of file operation requests, the identification based at least in part on at least one of: the file operations in the group of file operations being directed to a same storage system, or file operations in the group of file operations sharing a common operation type; and sending a request to execute the group of file operation requests to a system configured to perform the group of file operation requests.