Job Process Allocation via Accommodation Data Analysis
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Solution Overview
Problem
In large scale processing environments, inefficiencies arise in the allocation of virtual nodes and job processes to host computing systems due to increasing complexity, as existing methods fail to effectively utilize accommodation data for optimal resource distribution.
Innovation Solution
An administration system identifies job processes and obtains accommodation data for host computing systems, using this data to initiate or allocate virtual nodes based on physical and software configurations, as well as data access attributes, to efficiently distribute processing jobs across multiple hosts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If virtual nodes are allocated to host computing systems without considering accommodation data, then allocation speed is maintained, but resource utilization efficiency deteriorates
Solution Approach 1:
The system performs preliminary actions by obtaining and analyzing accommodation data (host attributes, data access attributes, data retrieval information) before allocating virtual nodes. This advance preparation enables informed allocation decisions that optimize resource utilization while managing complexity through structured data collection and analysis procedures.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring host computing system attributes, data access attributes, and data retrieval information. This feedback loop allows the allocation system to adapt to changing conditions and optimize resource utilization dynamically, balancing efficiency improvements with complexity management through iterative refinement.
2Measurement precision
If accommodation data is obtained and analyzed for each host computing system, then allocation accuracy is improved, but processing time increases
Solution Approach 1:
The accommodation data is segmented into distinct components: host attributes (CPU, memory, storage), data access attributes (read/write speeds, access patterns), and data retrieval information (network latency, bandwidth). This segmentation enables parallel processing and analysis of different data types, improving allocation accuracy while reducing overall processing time through divided computational tasks.
Solution Approach 2:
The system dynamically adjusts the depth and detail of accommodation data analysis based on job requirements, host capacity, and system state. By changing parameters such as which attributes to prioritize or the granularity of analysis, the system achieves high allocation accuracy when needed while reducing processing time during low-demand periods or for less critical allocations.
Data Source
AI summary
Systems, methods, and software described herein facilitate the allocation of large scale processing jobs to host computing systems. In one example, a method of allocating job processes to a plurality of host computing systems in a large scale processing environment includes identifying a job process for the large scale processing environment, and obtaining accommodation data for a plurality of host computing systems in the large scale processing environment. The method further provides identifying a host computing system in the plurality of host computing systems for the job process based on the accommodation data, and initiating a virtual node on the host computing system for the job process.