Bucket-Based File System Action Control for Tenant Priority
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Solution Overview
Problem
File system environments experience latency and failure in performing actions due to excessive tenant demands exceeding computational capacity, leading to unfair service distribution among tenants.
Innovation Solution
Implementing a control API that manages actions using buckets, including an aggregated bucket and tenant-specific buckets, prioritized by token allocation based on tenant priority, to ensure fair and efficient service delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the file system environment serves all tenant requests without prioritization, then the system appears to provide universal service, but larger tenants overwhelm smaller tenants causing latency and service degradation
Solution Approach 1:
The patent segments the tenant base into different priority groups (first priority tenants and second priority tenants) and creates separate execution queues for each group. This segmentation allows the system to serve different tenant categories differently, preventing larger tenants from monopolizing system resources and causing latency for smaller tenants, while still maintaining comprehensive service coverage across all tenants.
2Reliability
If the file system environment processes all requested actions equally, then fairness is maintained, but the computational capacity is exceeded leading to action failures
Solution Approach 1:
The patent applies local quality by giving different treatment to different tenant groups based on their priority status. First priority tenants receive preferential processing with their actions executed before second priority tenants when computational capacity is constrained. This localized differentiation in service quality ensures that critical actions from high-priority tenants are reliably completed while managing the overall productivity within available computational capacity.
3Reliability
If the system allows unlimited actions from high-priority tenants, then their service quality is maximized, but smaller tenants experience resource starvation
Solution Approach 1:
The patent implements dynamic resource allocation where the system continuously monitors computational capacity and adjusts the execution schedule accordingly. When capacity is available, first priority tenant actions are executed preferentially. When capacity is constrained, the system dynamically switches to executing second priority tenant actions or delaying them, ensuring that high-priority tenants receive maximum service quality while still maintaining service availability for smaller tenants through opportunistic execution when resources are free.
Data Source
AI summary
A method can include receiving requests to perform actions in a file system environment. The method can include populating a first bucket with first tokens. The first bucket can be associated with actions in the file system environment. The method can include populating second buckets, which can correspond to different tenants, with corresponding second tokens based on priorities of the tenants. The second tokens may correspond to allowable actions on behalf of the tenants. Each token of the first tokens and the second tokens may be in one-to-one correspondence with a single action. The method can include prioritizing the second buckets. The method can include generating an execution list for executing the requests. The method can include executing the execution list based on the first tokens and the second tokens.