Task Dispatch Utility for Deterministic Batch Processing
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Solution Overview
Problem
Current software development systems face inefficiencies in resource utilization, determinism, and reproducibility due to batch jobs being tied to real-world time, leading to unexpected and irreproducible system operations from transient events like excess processing demand or system outages.
Innovation Solution
Implementing a system that coordinates non-interactive processing jobs based on minimum and maximum latencies, periodicities, and other triggers not connected with real-time, allowing tasks to be executed when appropriate computer resources become available, rather than on a fixed schedule, thereby optimizing resource allocation and ensuring deterministic operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If batch jobs are tied to real-world time schedules, then system operations can be planned and predicted, but transient events like excess processing demand or system outages cause batch jobs to take longer than normal or to begin after their scheduled times, resulting in unexpected and irreproducible system operations
Solution Approach 1:
The patent applies dynamics by transitioning from static real-time scheduling to dynamic event-driven scheduling. The system dynamically adjusts job execution timing based on computational triggers and resource availability rather than fixed wall-clock schedules, allowing the system to adapt to transient events while maintaining deterministic behavior through consistent trigger-based execution semantics.
Solution Approach 2:
The patent changes the scheduling parameter from absolute time references to relative computational metrics. Instead of scheduling jobs at specific wall-clock times, the system uses computational triggers (such as data availability, resource thresholds, or prior job completion) as the scheduling basis, fundamentally changing how time and execution timing are parameterized in the batch processing system.
2Productivity
If batch jobs are executed on a fixed schedule, then resource allocation can be planned in advance, but resource utilization efficiency decreases when transient events cause jobs to be delayed or executed outside scheduled times
Solution Approach 1:
The patent implements self-service by enabling the batch processing system to automatically monitor its own state and trigger job execution based on internal computational conditions rather than external time schedules. The system serves itself by detecting resource availability and data readiness, then autonomously initiating appropriate batch jobs without requiring complex external scheduling coordination.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously monitors computational state, resource availability, and job completion status. This feedback drives the trigger-based scheduling decisions, creating a closed-loop system that adjusts job execution timing based on actual system conditions, thereby optimizing resource utilization while maintaining manageable complexity through rule-based responses.
3Productivity
If multiple batch jobs compete for system resources on a fixed schedule, then resource allocation follows predetermined patterns, but resource contention increases during busy or maintenance periods leading to inefficiencies
Solution Approach 1:
The patent applies preliminary action by pre-defining computational triggers and execution rules that determine job scheduling decisions. Rather than reacting to resource contention in real-time through complex dynamic allocation, the system has pre-established trigger conditions and response protocols that guide job execution timing, ensuring reproducible behavior while adapting to actual system state.
Solution Approach 2:
The patent segments the batch processing system into independent trigger-based job units that can be executed autonomously when their specific computational triggers are met. This segmentation allows different jobs to have different execution criteria and resource requirements, reducing contention by staggering execution based on actual readiness rather than forcing synchronized time-based scheduling that creates resource conflicts.
Data Source
AI summary
Computer resource management techniques involving receiving notification of an available resource, generating a set of tasks that could be performed by the resource, and dispatching one of the tasks on the resource. Related systems and software are also discussed. Some techniques can be used for automatic software building and testing.