Dynamic Network Update Scheduling via Dependency Graph
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Solution Overview
Problem
Existing network update methods face reliability and efficiency issues due to variations in device update times, leading to service interruptions and failures, as they fail to adapt to run-time conditions and dependencies between devices.
Innovation Solution
A dynamic scheduling approach using an update dependency graph that adjusts update operations based on feedback and constraints, ensuring reliable network transitions from an observed state to a target state by dynamically reordering operations and respecting resource availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network updates are implemented across multiple devices simultaneously, then update speed is improved, but network reliability deteriorates due to service interruptions and failures
Solution Approach 1:
The patent implements dynamic scheduling of update operations based on real-time feedback from devices. The system continuously monitors device states and adjusts the update schedule accordingly, transitioning from static to dynamic control. This allows the system to maintain high update speed while adapting to runtime conditions that affect reliability, such as device readiness and dependency satisfaction.
Solution Approach 2:
The system employs feedback mechanisms where devices report their update status and the scheduler adjusts subsequent update operations based on this feedback. The feedback loop enables the system to detect delays or failures and respond by reordering or rescheduling updates, thereby maintaining reliability without sacrificing overall update speed.
2Device complexity
If update operations are scheduled statically without considering runtime conditions, then scheduling complexity is reduced, but adaptability deteriorates due to inability to handle device-specific update times
Solution Approach 1:
The patent segments the update process into discrete update operations that can be independently scheduled and monitored. Each device update is treated as a separate operable unit, allowing the system to manage complexity through modular organization while maintaining adaptability to individual device conditions.
Solution Approach 2:
The scheduling system transitions from static to dynamic operation, where the update schedule is continuously adjusted based on runtime feedback. This dynamic approach enables the system to adapt to device-specific conditions without requiring complex pre-planning, balancing simplicity with adaptability.
3Ease of operation
If update dependencies between devices are not considered, then update process simplicity is improved, but network reliability deteriorates due to cascading failures from unsuccessful updates
Solution Approach 1:
The system performs preliminary actions by establishing update dependencies and determining the correct update order before execution. This preliminary planning ensures that updates are applied in the correct sequence, preventing cascading failures while maintaining operational simplicity through automated dependency management.
Solution Approach 2:
The patent introduces an intermediary scheduling system that manages update dependencies between devices. This intermediary layer handles the complexity of dependency tracking and coordination, allowing individual device updates to proceed simply while ensuring overall network reliability through centralized dependency management.
Data Source
AI summary
The techniques and/or systems described herein are configured to determine a set of update operations to transition a network from an observed network state to a target network state and to generate an update dependency graph used to dynamically schedule the set of update operations based on constraint(s) defined to ensure reliability of the network during the transition. The techniques and/or systems dynamically schedule the set of update operations based on feedback. For example, the feedback may include an indication that a previously scheduled update operation has been delayed, has failed, or has been successfully completed.