Predicate Logic Extensible Cluster System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional cluster architectures are complex and rigid, making it difficult to adapt to changing environments and adding new capabilities, which can lead to errors and inefficiencies in information storage and processing.
Innovation Solution
A predicate logic extensible cluster system and method that includes an engine process for managing resources, a resource interaction process for directing resource requests, and a separate predicate logic process for determining conditions using information from resource interactions, allowing for flexible and scalable logic operations with minimal changes to existing mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional cluster architecture mechanisms are used, then resource management can be performed, but the system becomes complex and rigid, making it difficult to adapt to changing environments and add new capabilities
Solution Approach 1:
The cluster architecture is segmented into distinct functional components: an engine that issues requests, resource interaction agents that interact with resources, and predicate logic agents that evaluate conditions. This segmentation allows each component to be independently modified and extended without affecting the entire system, thereby improving adaptability while managing complexity.
Solution Approach 2:
Predicate logic agents serve as intermediaries between the engine and resource interaction agents. These agents evaluate predicate logic conditions based on resource states and forward results to the engine, enabling flexible logic operations without requiring changes to the core engine or resource interaction mechanisms.
2Adaptability or versatility
If traditional cluster architecture mechanisms are used, then resource management can be performed, but the system is rigid and susceptible to errors when modifications are attempted
Solution Approach 1:
By dividing the system into separate engine, resource interaction agents, and predicate logic agents, the patent enables independent extension of cluster functionality through new predicate logic agents without modifying the core engine. This reduces error susceptibility because modifications are isolated to specific components rather than affecting the entire system.
Solution Approach 2:
The system uses predicate logic agents that can be replicated and configured with different logic conditions. Instead of modifying existing engine code to add new capabilities, new predicate logic agents can be created as copies with customized logic, ensuring reliability while enabling extensibility.
3Adaptability or versatility
If complex engine processes are used to handle new capabilities, then functionality can be enhanced, but the engine becomes more complicated and difficult to modify
Solution Approach 1:
The patent extracts logic evaluation functionality from the engine and places it in separate predicate logic agents. The engine retains its core function of issuing requests and monitoring resources, while predicate logic conditions are evaluated by external agents. This extraction prevents engine complexity from increasing while maintaining extensibility through new predicate logic agents.
Solution Approach 2:
Predicate logic agents act as intermediaries that handle the complexity of logic evaluation outside the engine. The engine simply issues requests and receives results, while the intermediate predicate logic agents perform the complex condition evaluation, keeping the engine itself simple and easy to modify.
Data Source
AI summary
Information cluster systems and methods are presented. In one embodiment, a cluster method comprises: performing an engine process including issuing requests to bring a resource online, offline, and monitor the resources, wherein the engine process is performed by an engine; performing a resource interaction process including interacting with a resource and directing a resource to comply with the request from the engine process, wherein the resource interaction process is performed by a resource interaction agent; performing a predicate logic process including performing predicate logic operations to determine if a predicate logic condition associated with the resource is satisfied and forwarding an indication of the results of the predicate logic operations to the engine process, wherein the predicate logic process is performed by a predicate logic agent that is separate from the engine performing the engine process.