Management Task Metadata Model Simulation for Computing Systems
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Solution Overview
Problem
Administrators face challenges in scheduling management tasks on computing systems with diverse devices, as they lack advance knowledge of task success and execution time, leading to potential failures and incorrect scheduling assumptions due to non-representative test devices.
Innovation Solution
A metadata model is simulated against the characteristics of a computing system to generate a simulation model, which predicts task success and execution time, considering system performance and running components, thereby providing more accurate predictions than traditional methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If administrators perform management tasks on a small number of test devices to assess task performance, then they can obtain some sense of task success and execution time, but the selected devices may not be representative of the computing system as a whole, leading to false confidence and incorrect extrapolation
Solution Approach 1:
The patent performs simulation of management tasks before actual execution on the computing system. The simulation model is created by simulating the metadata model against system characteristics in advance, allowing administrators to assess task performance and identify potential failures before committing to a scheduling plan, thus preventing false confidence from unrepresentative test devices.
Solution Approach 2:
The patent creates a simulation model that copies the essential characteristics of the computing system including device types, software versions, hardware resources, and task metadata. This virtual copy allows for accurate performance assessment without needing to physically test on representative devices, solving the problem of unrepresentative sampling.
2Ease of operation
If administrators schedule management tasks without advance knowledge of execution time, then they can maintain scheduling flexibility, but they cannot accurately determine when to schedule tasks to minimize service degradation
Solution Approach 1:
The patent simulates management task execution and determines expected completion times before actual scheduling. By having this advance knowledge of execution duration, administrators can strategically schedule tasks during periods of minimal usage (such as overnight or weekends) to minimize service degradation, while still maintaining the flexibility to adjust schedules based on system characteristics.
3Productivity
If administrators execute management tasks without simulating first, then they can perform tasks immediately, but they risk task failures due to version mismatches, hardware resource insufficiency, or other system-specific issues
Solution Approach 1:
The patent simulates management task execution before actual deployment to identify potential failures related to version mismatches, hardware resource insufficiency, or other system-specific issues. This preliminary simulation step ensures task success by validating compatibility and resource requirements, while the simulation can be performed efficiently using automated processing of system characteristics and task metadata.
Data Source
AI summary
A metadata model includes metadata of selected management tasks to be performed on components of a computing system. The metadata of each management task includes task requirements and historical task performance of the task. A simulation model for the computing system corresponds to the metadata model, and is determined by simulating the metadata model against characteristics of the computing system to generate simulation results.