Local Agent Failover for Backend Connection Disturbances
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing communication systems face functional failures when a connection to the backend is disturbed, leading to undesired disruptions in services or data availability, particularly in environments with poor network coverage or infrastructure interference, affecting user experience.
Innovation Solution
A computer-implemented method where a local agent takes over the function of a global agent upon connection disturbance, utilizing local resources and learning from backend information to maintain functionality, supported by reinforcement learning and sensor data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system relies on backend connection for function provision, then resource utilization is optimized, but system reliability deteriorates when connection is disturbed
Solution Approach 1:
The system is divided into local and global agents with distinct responsibilities. The local agent handles function provision locally, while the global agent manages backend communication. This segmentation allows the local agent to maintain function availability independently when backend connection is disturbed, resolving the reliability-complexity contradiction.
Solution Approach 2:
The local agent acts as an intermediary between the user and the backend. It receives function provision requests, processes them locally using learned policies, and only communicates with the global agent when necessary. This intermediary role enables the system to maintain reliability during connection disturbances without requiring complete architectural redesign.
2Reliability
If the local agent operates independently without backend connection, then function availability is maintained, but learning effectiveness deteriorates
Solution Approach 1:
The local agent performs preliminary learning actions during periods when backend connection is available, storing learned policies and environmental models locally. When connection is disturbed, these pre-learned actions enable the local agent to continue functioning. This preliminary action approach maintains both reliability and learning effectiveness by preparing the local agent in advance.
Solution Approach 2:
The system implements feedback mechanisms where the local agent reports its operational status and learned information to the global agent, which then updates the central policy model. This feedback loop ensures that learning continues effectively even during intermittent connection disturbances, as the local agent's experiences are fed back to improve the global model when connection is restored.
3Adaptability or versatility
If the system switches between local and global agents, then adaptability to connection status is improved, but operational complexity increases
Solution Approach 1:
The system dynamically adapts its operation mode based on connection status. When backend connection is available, the global agent handles function provision; when connection is disturbed, the local agent takes over. This dynamic switching is automated through status detection mechanisms, improving adaptability without significantly increasing operational complexity as the transition is handled autonomously by the system.
Data Source
AI summary
A computer-implemented method for preventing loss of function in a local instance when there is a disturbance of a connection to a backend in a communication system that has a local instance having a local agent and a backend acting in part as a global agent, an agent designating a unit that is designed to achieve defined goals through autonomous behavior. The method includes, when there is a connection to the backend, the providing of the function by the global agent, which receives backend information from the backend during the providing of the function, and, if a connection to the backend is disturbed, the providing of the function by the local agent.