Crypto Device Work Request Queue Management
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Solution Overview
Problem
Crypto devices face challenges in efficiently managing and prioritizing multiple work requests from different applications without interruption, leading to potential delays and inefficiencies in processing confidential information.
Innovation Solution
A method is implemented where a prediction table is generated to assign initial execution times to request types, and credit values are determined for each application, allowing work requests to be queued and processed based on predicted execution times, with updates made after completion to refine predictions and manage service level agreements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple work requests from different applications are queued to be processed subsequently without interruption, then processing efficiency is improved, but managing and prioritizing requests becomes more complex
Solution Approach 1:
The patent segments work requests into different priority levels and categories, organizing them in a structured queue system. Each request is classified and assigned to specific processing stages, transforming the complex management of multiple applications into manageable segments that can be handled systematically without interruption to processing flow.
Solution Approach 2:
The patent implements preliminary classification and prioritization of work requests before they enter the processing queue. By pre-organizing requests according to their type, priority, and resource requirements, the system eliminates the need for complex real-time decision-making during processing, thereby improving efficiency while keeping management complexity controlled.
2Loss of time
If work requests are processed without interruption, then execution time is reduced, but performance management and service level agreement establishment become more difficult
Solution Approach 1:
The patent incorporates feedback mechanisms that continuously monitor processing performance, execution times, and resource utilization. This feedback is used to dynamically adjust service level agreements and performance thresholds, enabling the system to maintain reliable performance management even while processing requests without interruption. The feedback loop ensures that service level commitments are met and can be verified.
Solution Approach 2:
The patent establishes service level agreements and performance criteria in advance, before processing begins. By pre-defining execution time targets, priority levels, and performance thresholds, the system can process requests continuously without interruption while still maintaining reliable performance management, as the criteria are already set and can be automatically measured against actual performance.
3Reliability
If credit values and prediction tables are used to manage work requests, then service level agreement establishment is improved, but the initial setup and configuration become more complex
Solution Approach 1:
The patent implements self-service mechanisms where the system automatically generates prediction tables and calculates credit values based on observed processing patterns and historical data. Rather than requiring manual configuration of complex parameters, the system learns from actual performance and self-adjusts the service level agreements, thereby improving reliability while reducing the burden of initial setup and ongoing configuration.
Solution Approach 2:
The patent uses feedback from actual processing performance to automatically refine prediction tables and credit value assignments. By continuously monitoring execution times and resource usage, the system self-optimates the service level agreement parameters, making the initial configuration simpler while maintaining high reliability through adaptive learning and adjustment based on real-world performance data.
Data Source
AI summary
Multiple work requests from different applications are queued to be processed subsequently without interruption by a crypto device. A prediction table is generated for each application to be processed by the crypto device. An initial credit value is determined for each incoming work request. The work request is an entry in an ordered queue in the order of time using respective time stamps. The next work request to be processed is selected from the entries in the queue by using the first entry in the queue for which the credit values for the corresponding application is greater than or equal to the predicted execution time for the corresponding request type in the prediction table. The selected next work request is processed.