Processor Credit Management for Backup Service Scheduling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In backup systems, processor credits are not always accrued efficiently due to reaching threshold credits, limiting computing capability and utilization, especially when backup jobs are infrequent, leading to reduced CPU performance and idle resources.
Innovation Solution
A method is introduced to manage services by determining a second time instant for operations based on historical processor credits and time periods, allowing for optimal utilization of processor credits to perform both periodic and non-periodic operations within extended time periods, ensuring maximum credits for operations and improving computing capability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If processor credits are accumulated until threshold is reached, then CPU performance is improved, but time loss increases due to infrequent backup jobs
Solution Approach 1:
The system performs preliminary actions by accumulating processor credits during idle periods before threshold is reached. The controller proactively manages credit accumulation and schedules operations in advance, ensuring that when backup jobs are infrequent, the system has already prepared the necessary computational resources to minimize time loss while maintaining performance.
Solution Approach 2:
The system dynamically adjusts operation scheduling based on real-time processor credit status. The controller monitors credit accumulation and dynamically determines optimal operation timing, allowing the system to adapt between credit-accumulation mode (when threshold not reached) and credit-spending mode (when threshold reached), thereby balancing CPU performance with time loss reduction.
2Ease of operation
If operations are scheduled based on fixed time periods, then ease of operation is improved, but productivity decreases due to inefficient credit utilization
Solution Approach 1:
The system implements feedback mechanisms where the controller continuously monitors processor credit status and adjusts operation scheduling accordingly. Historical data from previous credit utilization patterns is fed back into the scheduling algorithm, enabling the system to learn optimal timing for operations and improve both ease of operation through automated adaptive scheduling and productivity through efficient credit utilization.
Solution Approach 2:
The system performs self-service by automatically managing its own scheduling based on accumulated processor credits and historical patterns. The controller independently determines optimal operation timing without external intervention, using the system's own operational history to guide future scheduling decisions, thereby achieving both ease of operation and improved productivity.
3Adaptability or versatility
If processor credits are spent on non-periodic operations, then adaptability is improved, but reliability decreases due to uncertain credit availability
Solution Approach 1:
The system performs preliminary credit accumulation during stable periods before non-periodic operations are scheduled. By proactively building up processor credits in advance and using historical data to predict future credit availability, the system can confidently schedule adaptable operations knowing that sufficient credits will be available, thereby improving both adaptability and reliability.
Solution Approach 2:
The system uses feedback from historical credit utilization patterns and operational outcomes to refine future scheduling decisions. By analyzing past performance data, the controller can better predict when and how much processor credit will be available for non-periodic operations, reducing uncertainty and improving reliability while maintaining adaptability.
Data Source
AI summary
Embodiments of the present disclosure relate to a method, device and computer program product for managing a service. The method comprises in response to processor credits for the service reaching threshold credits at a first time instant (t1), determining a second time instant when a first operation for the service is to be performed. The method further comprises determining, based on a set of historical processor credits between the first time instant and the second time instant, first processor credits related to a second set of time periods which is between the first time instant and second time instant. The method further comprises determining, based on a first time length from the first time instant to the second time instant, a second time length of the first set of time periods and a third time length of the second set of time periods, second processor credits that can be obtained between a third time instant when the second set of time periods ends and the second time instant; in response to the first, second and third processor credits satisfying a predetermined condition, performing the second operation within the second set of time periods. The method may increase the time for performing the second operation without affecting the first operation.