Network Resource Discovery via Concurrent Task Scheduling
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Solution Overview
Problem
Current network management systems are inefficient in discovering and processing data from network devices, leading to wastage of computing and human resources due to time-consuming and costly execution of discovery tasks, which also result in poor utilization of computing resources.
Innovation Solution
A network management system utilizing a concurrent discovery model and capacity scheduler model to process network data, determining schedules based on weights for executing discovery tasks, and efficiently managing queues to conserve resources by executing tasks in parallel or sequentially, thereby optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If discovery tasks are executed sequentially in traditional network management systems, then task execution is simple, but resource utilization is poor and time consumption increases
Solution Approach 1:
The patent segments discovery tasks into multiple queues (first queue for first discovery tasks, second queue for second discovery tasks) and further divides them into batches. This segmentation enables parallel execution of tasks while maintaining manageable complexity through structured organization, directly resolving the contradiction between improved productivity and scheduling complexity.
Solution Approach 2:
The patent performs preliminary actions by pre-processing network data to identify and categorize discovery tasks before execution. Tasks are organized into queues and batches in advance, allowing the system to execute multiple tasks concurrently without increasing operational complexity during execution, thus improving resource utilization efficiency.
2Loss of time
If all discovery tasks are executed concurrently without scheduling, then discovery speed increases, but computing resources are wasted
Solution Approach 1:
The patent implements dynamic scheduling by adjusting task execution based on real-time conditions. The capacity scheduler dynamically determines which batches to execute and when, adapting to varying network conditions and resource availability. This dynamic approach reduces discovery time while preventing computing resource waste by only executing tasks when resources are available and needed.
Solution Approach 2:
The patent changes execution parameters by varying the concurrency level and batch size based on system capacity. The capacity scheduler modifies parameters such as the number of simultaneous tasks and resource allocation dynamically, optimizing the balance between discovery speed and resource utilization, thereby reducing both time loss and energy waste.
3Productivity
If discovery tasks are executed in batches with capacity scheduling, then resource utilization improves, but task execution time increases
Solution Approach 1:
The patent ensures continuity of useful action by maintaining multiple queues of discovery tasks that can be executed continuously as resources become available. The capacity scheduler continuously monitors system capacity and launches batches of tasks without idle periods, ensuring that computing resources are continuously utilized productively while minimizing total execution duration through overlapping task execution.
Data Source
Figure 1A
Figure 1B
Figure 1C
AI summary
A device may receive network data associated with network devices, and may process the network data, with a first model, to determine a first queue identifying first discovery tasks to execute for the network devices and a second queue identifying second discovery tasks to execute for the network devices. The device may process the first queue and the second queue, with a second model, to determine a schedule for executing the first and second discovery tasks, and may execute the first and second discovery tasks based on the schedule. The device may calculate progress of the executions of the first discovery tasks and the second discovery tasks, and may estimate time intervals associated with completions of the executions of the first discovery tasks and the second discovery tasks. The device may provide, to a user device, information identifying the progress and the time intervals.