I/O Scheduler Virtual Time Adjustment for Processing Efficiency
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Solution Overview
Problem
Existing distributed data processing systems face challenges in efficiently scheduling I/O operations across multiple sources in a memory drive, leading to potential data loss and availability issues due to misalignment between estimated and actual processing times.
Innovation Solution
A method and system that utilize a scheduling algorithm to determine estimated processing deadlines for I/O operations based on memory drive characteristics and pre-determined processing bandwidth, with an operations scheduler that adjusts virtual time based on actual processing times to ensure timely and efficient processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a scheduling algorithm is used to manage I/O operations from multiple sources, then processing efficiency and bandwidth allocation are improved, but the complexity of the system increases due to the need to track and adjust virtual time and processing deadlines
Solution Approach 1:
The patent introduces a scheduling algorithm as an intermediary component that manages I/O operations between multiple sources and the memory drive. This algorithm acts as a mediator that translates complex scheduling requirements into manageable virtual time slots and processing deadlines, thereby improving processing efficiency without directly increasing the complexity of the underlying memory drive hardware.
Solution Approach 2:
The patent transforms the scheduling problem by changing parameters from physical time to virtual time. The scheduling algorithm uses virtual time slots and adjusted processing deadlines as parameters to manage I/O operations, which simplifies the scheduling decisions while maintaining processing efficiency. This parameter transformation allows the system to handle multiple I/O sources effectively without proportionally increasing system complexity.
2Loss of time
If estimated processing times are used to schedule I/O operations, then data availability and access time are improved, but data loss risk increases when actual processing times deviate from estimates
Solution Approach 1:
The scheduling algorithm incorporates feedback mechanisms by monitoring actual processing times of I/O operations and using this information to adjust future virtual time slot allocations and processing deadlines. This feedback loop allows the system to learn from deviations between estimated and actual processing times, thereby maintaining data availability while reducing data loss risk through adaptive scheduling decisions.
Solution Approach 2:
The patent implements dynamic scheduling where virtual time slots and processing deadlines are not fixed but are adjusted based on actual system performance. The scheduling algorithm dynamically modifies processing parameters in response to changing conditions, allowing the system to adapt to varying I/O workloads and processing speeds, thus balancing access time improvements with data loss prevention.
3Measurement precision
If virtual time adjustment is implemented based on actual processing times, then processing deadline accuracy is improved, but the complexity of time management increases
Solution Approach 1:
The scheduling algorithm performs self-adjustment by automatically modifying virtual time slots and processing deadlines based on observed actual processing times. This self-service capability allows the system to improve deadline accuracy without requiring external intervention or complex manual time management mechanisms. The algorithm autonomously learns and adapts its timing parameters, reducing the operational complexity despite the sophistication of the time management system.
Data Source
AI summary
An operations scheduler and a method of scheduling I/O operations to be processed by a memory drive are disclosed. The method includes receiving I/O operations, and for each one of them determining an estimated processing time, and an estimated processing period indicative of an estimated deadline. The method also includes determining a scheduled order of I/O operations based on the respective estimated deadlines. The method also includes monitoring an actual processing time for the I/O operations and adjusting a virtual time of the operations scheduler if a given actual processing time is above a given estimated processing time of a given I/O operation.