Decentralized Agent Network for Scalable Event Data Migration
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Solution Overview
Problem
Traditional centralized event management architectures face scalability issues, become bottlenecks, and are expensive to replicate, struggling to manage complex network environments effectively, leading to increased costs and manageability gaps.
Innovation Solution
A decentralized data and event management network model where agents interact randomly to diffuse and migrate event data, eliminating the need for a central server and allowing for cost-effective, scalable global system monitoring and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a centralized event management architecture is used, then system management is simplified and centralized control is achieved, but the system becomes a bottleneck and cannot scale to handle millions of systems
Solution Approach 1:
The patent divides the centralized management system into multiple distributed agents deployed across different locations. Each agent independently manages events in its local region, eliminating the single centralized bottleneck while maintaining coordinated control through peer-to-peer communication and shared data structures.
2Loss of information
If a centralized event management architecture is used, then global system event monitoring is achieved, but the central location becomes a single point of failure
Solution Approach 1:
The patent implements local event monitoring and processing capabilities at each distributed agent, allowing agents to autonomously handle events in their local environments. This local autonomy ensures that the failure of any single agent does not compromise global monitoring, as other agents continue to function independently.
3Device complexity
If the traditional centralized management structure grows linearly, then management costs increase, but it cannot keep pace with the geometric growth of network complexity
Solution Approach 1:
The patent implements a dynamic, adaptive agent-based system where agents can be automatically deployed, instantiated, and configured based on network growth and complexity requirements. This dynamic approach allows the management infrastructure to scale elastically with the network, avoiding the linear cost growth associated with traditional centralized structures.
Data Source
AI summary
In one embodiment, a method and apparatus for a mechanism for data migration across networks is disclosed. The method includes: randomly selecting a template from a local cache at an agent, the template indicating one or more characteristics of event data entities the agent is searching for; querying, via random connections from the agent, one or more other connected agents for the event data entities matching the template; if a matching event data entity for the template is found, returning the matching event data entity to the local cache of the agent; and if a matching event data entity for the template is not found, diffusing the template to the one or more other connected agents via a data diffusion process. Other embodiments are also disclosed.