Event-Triggered Goal Change in Network Control Loops
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Solution Overview
Problem
Current control loops in network environments have fixed goals that cannot adapt to changing circumstances, leading to suboptimal performance as consumer needs vary over time, requiring manual reconfiguration which reduces automation benefits.
Innovation Solution
Implementing event-triggered goal changes in control loops that associate trigger conditions with adjustable goals, allowing dynamic adjustments based on detected events or conditions within the network, such as time of day or network load, to optimize performance indicators like energy usage and quality of experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed goals are used in control loops, then device complexity is reduced and ease of operation is improved, but adaptability to changing network conditions deteriorates
Solution Approach 1:
The control loop goals are transformed from static fixed values to dynamic adjustable parameters. The system now allows goals to be modified based on changing network conditions, time of day, and operational circumstances, enabling the control loop to adapt its optimization targets dynamically while maintaining the same basic control structure.
Solution Approach 2:
The invention changes the parameter values (goals) of the control loop based on detected conditions. Different goal values are applied depending on network load, time of day, and other operational parameters, allowing the system to optimize for different priorities (e.g., energy saving vs. quality of experience) without changing the fundamental control loop architecture.
2Extent of automation
If manual reconfiguration is required to change goals, then control precision is maintained, but extent of automation is reduced and loss of time increases
Solution Approach 1:
The control loop system performs self-configuration by automatically detecting network conditions and adjusting its own goals without human intervention. The system monitors parameters such as network load, time of day, and operational state, then autonomously selects and applies appropriate goal values, eliminating the need for manual reconfiguration.
Solution Approach 2:
The system implements feedback mechanisms where the control loop continuously monitors network conditions and operational parameters, uses this information to determine appropriate goal adjustments, and automatically applies the new goals. This closed-loop feedback enables automatic adaptation to changing conditions without manual intervention.
Data Source
AI summary
A method and apparatus are provided, in which execution of a managed entity is controlled. A control loop that is operated relative to the managed entity is established (1102), which links at least one monitored criteria to an assigned goal having a defined target value. Performance of the managed entity within the control loop is adjusted (1104), based upon a difference between a current value of the monitored criteria and the defined target value. One or more trigger conditions are associated (1106) with the control loop. A detection (1108) is then made as to whether a trigger condition associated with the control loop has been met. Upon detecting that the trigger condition associated with the control loop has been met, the goals assigned to the monitored criteria, that is linked to the control loop, which has the trigger condition that has been met is changed (1110).