Cloud Maintenance Scheduling Using Hash-Based Time Distribution
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Solution Overview
Problem
Existing cloud computing environments face challenges in efficiently scheduling system maintenance operations, leading to resource constraints and spikes in utilization, which can impact stability and reliability.
Innovation Solution
A system uses a hash function to distribute execution times for system maintenance operations semi-randomly within a specified time period, allowing customers to choose preferred times while avoiding resource constraints and spikes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If system maintenance operations are scheduled without distribution, then maintenance can be performed efficiently, but resource constraints and spikes in utilization occur impacting stability and reliability
Solution Approach 1:
The patent segments maintenance operations by distributing them across different time periods using hash-based scheduling. Instead of concentrating all maintenance at once, the system divides maintenance tasks into multiple time slots, ensuring no single resource is overwhelmed while maintaining overall maintenance efficiency and system reliability.
2Device complexity
If all maintenance operations are performed at the same time, then scheduling is simple, but resource constraints and utilization spikes occur
Solution Approach 1:
The patent introduces dynamic scheduling where maintenance operations are automatically assigned to different time periods based on hash functions of resource identifiers. This dynamic distribution adapts to the specific characteristics of each resource, preventing uniform timing while maintaining systematic scheduling without complex manual intervention.
3Reliability
If maintenance operations are distributed across time, then resource stability is maintained, but scheduling complexity increases
Solution Approach 1:
The patent implements self-service scheduling where the system automatically determines optimal time distributions for maintenance operations based on hash functions. The scheduling mechanism is autonomous and requires minimal external intervention, reducing operational complexity while achieving stable resource utilization through automated time distribution.
Data Source
AI summary
Techniques for scheduling system maintenance operations in a cloud environment are disclosed. A system receives a first request to execute a first system maintenance operation within a first time period. The system selects a first plurality of candidate execution times within the first time period for execution of the first system maintenance operation. The system executes a hash function on a first attribute associated with the first request to select a first execution time within the first plurality of candidate execution times. The system schedules the execution of the first system maintenance operation at the first execution time.