Multi-Agent Anomaly Management via Shared Sentinel Agents
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Solution Overview
Problem
Existing multi-agent system (MAS) fault management schemes are inefficient in large systems due to high communication overhead, making it difficult to manage anomalies effectively when a large number of agents interact, particularly in wireless network environments where device-level faults and version discrepancies cause disruptions.
Innovation Solution
A scalable anomaly management system where agents report performance issues to anomaly management agents, which diagnose and remediate faults by generating reports, processing causal conditions, and implementing corrective actions such as replacing faulty agents or service components, while maintaining a balanced load of anomaly management agents across the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a one-to-one mapping of application agents to fault management agents (Sentinel agents) is used, then each agent can be monitored individually, but the communication overhead becomes onerous in large MAS systems
Solution Approach 1:
Multiple Sentinel agents are merged into a single shared Sentinel agent that monitors a group of application agents. This consolidation reduces the number of Sentinel agents from one-per-agent to one-per-group, significantly decreasing communication overhead while maintaining collective monitoring capability through the shared agent's access to interaction logs.
Solution Approach 2:
The shared Sentinel agent is designed to monitor multiple different application agents simultaneously, making it a universal monitoring entity. This multi-functional approach allows one Sentinel agent to perform the fault detection role for an entire group of agents, reducing redundancy while preserving monitoring coverage.
2Device complexity
If multiple Sentinel agents are shared across agent groups, then communication overhead is reduced, but load balancing becomes more difficult to manage
Solution Approach 1:
The system implements dynamic load balancing where the administrator can flexibly assign and reassign application agents to different Sentinel agents based on current system conditions and workload. This dynamic configuration allows the system to adapt to changing demands, ensuring that no single Sentinel agent becomes overloaded while maintaining efficient communication.
Solution Approach 2:
The system allows modification of operational parameters such as the grouping of agents under Sentinel agents, the assignment of specific agents to Sentinels, and the configuration of monitoring thresholds. These parameter changes enable flexible load distribution and can be adjusted to optimize performance under different system conditions.
3Quantity of substance
If the MAS includes several thousand or more agents, then system capability and coverage are improved, but known fault management schemes become unsuitable due to onerous communication overhead
Solution Approach 1:
The large population of agents is segmented into multiple groups, each monitored by a shared Sentinel agent. This hierarchical segmentation organizes thousands of agents into manageable clusters, reducing the monitoring overhead from O(n) to O(n/k) where k is the number of groups, making fault management scalable to large MAS systems.
Solution Approach 2:
Shared Sentinel agents act as intermediary entities between the application agents and the fault management system. Instead of each agent communicating directly with the central management system, the Sentinel agents aggregate monitoring data and communicate on behalf of their groups, reducing communication overhead while maintaining centralized oversight capability.
Data Source
AI summary
An anomaly management method is provided for a multi-agent system (MAS) in which a plurality of application agents are arranged to be capable of interacting with each other over a communications network. The MAS has a plurality of anomaly management agents arranged to receive reports from a referring agent regarding a referred agent when a referring agent has determined an interaction anomaly has occurred which was potentially caused by one or more conditions associated with a referred agent. The anomaly management agent is arranged to determine one or more conditions associated with the referred agent which have caused the interaction anomaly. The anomaly management agent is also arranged to remedy the condition. The method comprises at least one of said plurality of anomaly management agents receiving a message containing information related to the interaction with the referred agent from the referring agent. The message comprises information identifying the referred agent and other information related to the interaction anomaly. One or more possible conditions associated with the referred agent which may have caused the interaction anomaly are determined from the information provided by the referring agent. A plurality of tests is then performed to determine at least one condition associated with the referred agent. Finally, the condition associated with the referred agent is remedied. The referring agent may then be provided with feedback information to enable the interaction to be resumed.