Job Allocation via Node Risk Scores
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Solution Overview
Problem
Node failures in computing environments lead to resource wastage and potential job data corruption, as rebooting a partially failed node can interrupt ongoing jobs and result in data loss.
Innovation Solution
A management node allocates jobs among nodes based on risk scores calculated from historical data, assigning more sensitive jobs to nodes with lower failure likelihoods and less sensitive jobs to nodes with higher failure likelihoods, thereby minimizing the impact of node failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a failed node is rebooted to release computing resources, then resource availability is improved, but job data corruption and interruption occur
Solution Approach 1:
The system performs preliminary actions by allocating jobs to nodes based on predicted failure risks before failures occur. The management node continuously monitors node health and pre-allocates sensitive jobs to lower-risk nodes, preventing data loss before it happens rather than reacting after failure occurs.
Solution Approach 2:
The management node acts as an intermediary between job allocation and node execution. It introduces a layer of intelligence that monitors node risk scores and mediates job placement decisions, preventing direct assignment of critical jobs to high-risk nodes and thus avoiding data loss during reboots.
2Productivity
If jobs are allocated to nodes with higher failure risks, then resource utilization is improved, but job reliability deteriorates
Solution Approach 1:
The system applies local quality by differentiating job allocation strategies based on node-specific risk profiles. Instead of uniform treatment, the management node assigns different types of jobs to different nodes according to their individual risk scores, matching job sensitivity to node reliability characteristics.
Solution Approach 2:
The system changes the allocation parameter from purely resource-based to risk-aware resource allocation. The management node incorporates node risk scores as a dynamic parameter in job allocation decisions, adjusting which nodes receive which jobs based on real-time risk assessments rather than static resource availability alone.
3Loss of energy
If node failures are not addressed promptly, then resource wastage is minimized, but job completion time increases
Solution Approach 1:
The system implements continuous feedback loops where the management node monitors node health metrics and risk scores in real-time. This feedback enables dynamic job reassignment when nodes deteriorate, ensuring failures are addressed promptly while maintaining resource utilization and minimizing both wastage and completion delays.
Data Source
AI summary
Node failures in a computing environment can be managed. For example, a computing device can determine a risk score for a node in the computing environment. The risk score can indicate a likelihood of the node failing. The computing device can also determine a risk-tolerance score for a job to be executed in the computing environment by analyzing job data associated with the job. The risk-tolerance score can indicate a susceptibility of the job to a failure of one or more nodes in the computing environment. The computing device can cause the job to be at least partially executed on the node based on the risk score for the node and the risk-tolerance score for the job.