Output-Decision Negative Feedback Control for Heterogeneous Functional Equivalents
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Solution Overview
Problem
The existing cyberspace environment faces security threats due to unknown vulnerabilities and backdoors in software and hardware apparatuses, which can lead to network security breaches if not timely detected or addressed.
Innovation Solution
An output-decision-based negative feedback control method and system that schedules heterogeneous functional equivalents in a network system by receiving and analyzing output responses, determining credibility, and generating scheduling policies to replace or reconfigure faulty or low-credibility components, thereby maintaining consistent output responses and enhancing security and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If heterogeneous functional equivalents are deployed in the network system, then system reliability and security are improved through redundancy, but device complexity and difficulty of managing multiple components increase
Solution Approach 1:
The system segments the functional equivalents into different credibility groups based on their output responses. The output decider divides functional equivalents into at least one set according to their output responses, and determines credibility of each set using decision algorithms. This segmentation allows the system to manage complexity by organizing redundant components into structured groups with different trust levels.
Solution Approach 2:
The system implements a feedback control mechanism where the output decider continuously monitors output responses from functional equivalents, determines their credibility, and sends this information to the feedback controller. The feedback controller then generates scheduling policies based on this credibility information, creating a closed-loop system that automatically adjusts to maintain security while managing complexity.
2Reliability
If credibility assessment and scheduling policies are implemented, then faulty components are detected and replaced timely, but processing time and computational overhead increase
Solution Approach 1:
The system performs preliminary credibility assessment by continuously monitoring output responses and determining credibility before faults manifest. The output decider divides functional equivalents into sets and determines their credibility in advance, allowing the feedback controller to proactively generate scheduling policies that replace or reconfigure components before they cause system failures, thus reducing overall processing time despite the added assessment step.
Solution Approach 2:
The system implements self-service through automated credibility determination and scheduling policy generation. The decision algorithms automatically assess credibility based on output responses, and the feedback controller autonomously generates scheduling policies without manual intervention. This automation reduces the time cost by eliminating human analysis and decision-making processes.
3Measurement precision
If decision algorithms are used to determine credibility, then accurate identification of faulty components is achieved, but computational complexity and processing overhead increase
Solution Approach 1:
The system uses multiple heterogeneous functional equivalents as copies that perform the same function but may have different credibility levels. By comparing their output responses, the decision algorithms can identify faults without needing complex analysis of individual components. The redundancy provides natural copies for comparison, simplifying the detection algorithm while maintaining high accuracy.
Solution Approach 2:
The system changes the parameter being monitored from internal component state to external output response. Instead of analyzing complex internal states of functional equivalents, the decision algorithms simply compare output responses, which are easier to measure and analyze. This parameter change reduces algorithmic complexity while maintaining detection accuracy through the negative feedback mechanism.
Data Source
AI summary
An output-decision-based negative feedback control method and system. The method includes: receiving, by an output decider, output responses of at least two heterogeneous functional equivalents, and dividing numbers corresponding to the at least two heterogeneous functional equivalents into at least one set according to the output responses; determining, by the output decider, credibility of each set according to the output responses, and sending the at least one set and the credibility corresponding to each set to a feedback controller via decision information; generating, by the feedback controller, a first scheduling policy and/or a second scheduling policy according to the decision information; and sending, by the feedback controller, the first scheduling policy to an input proxy, and/or sending a change instruction to the heterogeneous functional equivalent indicated by the second scheduling policy. The method can prevent in advance and process a heterogeneous functional equivalent that may be faulty.