Cache Service Prioritizing Data Requests by Quality of Service
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Solution Overview
Problem
Deploying data-intensive distributed applications across clusters of virtual machines is impractical due to latency issues when handling large data sets, and prioritization of processing jobs is necessary to allocate computing resources effectively.
Innovation Solution
A system and method for prioritizing data requests based on quality of service, where data requests from processing jobs are identified, prioritized based on assessed quality of service, and cache memory is assigned accordingly to ensure efficient data retrieval and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data requests are processed in a virtualized environment with multiple processing jobs, then resource utilization is improved, but latency increases due to competing data requests
Solution Approach 1:
The patent segments data requests into different priority levels based on quality of service assessments. The cache service divides the processing queue into high-priority and low-priority segments, allowing critical data requests to be processed separately from less urgent ones, thereby reducing latency for important operations while maintaining high resource utilization across all jobs.
Solution Approach 2:
The system dynamically changes the processing parameters of data requests by assigning priority levels and adjusting cache memory allocation based on quality of service metrics. This parameter change allows the system to optimize resource distribution in real-time, improving both productivity and latency performance by allocating more resources to high-priority requests.
2Ease of operation
If cache memory is allocated equally to all data requests, then fairness is improved, but processing efficiency deteriorates due to lack of prioritization
Solution Approach 1:
The patent implements local quality by allocating cache memory and processing resources differently based on the specific needs and priority of each data request. Instead of uniform allocation, the cache service assigns resources locally optimized for each job's quality of service requirements, ensuring that critical operations receive preferential treatment while maintaining overall system fairness.
Solution Approach 2:
The system dynamically adjusts cache memory allocation and processing priority based on real-time quality of service assessments. The allocation is not static but changes adaptively as job priorities and system conditions evolve, allowing the system to maintain both fairness and efficiency by responding to changing requirements.
3Adaptability or versatility
If multiple processing jobs are distributed across virtual machine clusters, then scalability is improved, but resource allocation complexity increases
Solution Approach 1:
The patent introduces a cache service as an intermediary layer between the virtual machine clusters and data requests. This intermediary automatically assesses quality of service, determines priorities, and manages cache memory allocation, thereby simplifying resource allocation complexity while maintaining the scalability benefits of distributed virtual machine architecture.
Data Source
AI summary
Systems, methods, and software described herein facilitate servicing of data requests based on quality of service assigned to processing jobs. In one example, a method of prioritizing data requests in a computing system based on quality of service includes identifying a plurality of data requests from a plurality of processing jobs. The method further includes prioritizing the plurality of data requests based on a quality of service assessed to each of the plurality of processing jobs, and assigning cache memory in the computing system to each of the plurality of data requests based on the prioritization.