Resource-Aware Job Scheduling Using User Utilization Scores
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Solution Overview
Problem
Existing job schedulers in cloud environments allocate resources based on predefined policies like fair-share, leading to inefficiencies due to varying job characteristics, resulting in wasted resources and suboptimal utilization.
Innovation Solution
Implement a job scheduler that considers resource utilization efficiency at the job level by calculating a utilization score for each user, adjusting resource allocation decisions based on these scores to optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If job schedulers allocate resources based on predefined policies like fair-share, then resource allocation is simple and predictable, but resource utilization efficiency deteriorates due to varying job characteristics
Solution Approach 1:
The job scheduler dynamically adjusts resource allocation based on real-time job characteristics and resource utilization metrics. Instead of static predefined policies, the system continuously adapts allocation decisions by evaluating job type, resource requirements, and current system state, thereby resolving the contradiction between allocation simplicity and utilization efficiency.
Solution Approach 2:
The system changes allocation parameters dynamically based on job characteristics. By introducing multiple dimensions for resource allocation (job type, priority, resource demands, historical performance) and adjusting these parameters in real-time, the scheduler optimizes resource utilization while maintaining manageable complexity through structured parameter management.
2Reliability
If resources are allocated uniformly to all users, then fairness is maintained, but resource utilization efficiency worsens due to mismatch between allocation and actual job needs
Solution Approach 1:
The job scheduler applies different allocation strategies to different users and jobs based on their specific characteristics. Instead of uniform allocation, the system evaluates each job's resource requirements, user priorities, and historical performance to determine optimal allocation, achieving both fairness through consistent evaluation criteria and efficiency through customized allocation decisions.
Solution Approach 2:
The system dynamically adjusts allocation fairness based on real-time conditions. Fairness is not static but adapts to current system state, job characteristics, and user needs, allowing the scheduler to maintain fairness while optimizing utilization by allocating more resources to jobs that can utilize them effectively.
3Ease of manufacture
If job schedulers use predefined resource allocation policies, then implementation is straightforward, but resource waste increases due to inability to adapt to varying job characteristics
Solution Approach 1:
The job scheduler performs preliminary evaluation of job characteristics and resource requirements before allocation decisions. By pre-assessing job type, expected resource consumption, and user priorities, the system prepares allocation strategies in advance, reducing resource waste while maintaining implementation simplicity through structured pre-evaluation protocols.
Solution Approach 2:
The system implements feedback mechanisms that monitor resource utilization and allocation effectiveness. This feedback loop allows the scheduler to learn from past allocations, identify waste patterns, and continuously improve allocation decisions, reducing resource waste while maintaining manageable system complexity through data-driven refinements.
Data Source
AI summary
Computer-implemented methods, systems and computer program products for job scheduling in a computing system are provided. The computing resources of the computing system is allocated to one or more users of the computing system using a predefined policy. The method comprises receiving, by a job scheduler associated with the computing system one or more resource utilization scores of the one or more users, each of the one or more resource utilization scores indicating resource utilization efficiency over time at a job level for the one or more users. The method comprises receiving, by the job scheduler, one or more jobs submitted by the one or more users. The method further comprises scheduling, by the job scheduler, the received one or more jobs based on the predefined policy and further on the received one or more resource utilization scores of the one or more users.