Object Cache Framework Matching Rule-Set Objects
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Solution Overview
Problem
Business rules engines face inefficiencies in evaluating and executing rule-sets due to the lack of a systematic method for matching rule-sets with appropriate computing resources, leading to high costs and suboptimal utilization of resources.
Innovation Solution
A method is introduced that utilizes an object cache framework to select and match rule-sets with rules engines based on criteria such as processing power, cost, and availability, allowing for efficient allocation and execution of rule-sets across a distributed network, leveraging technologies like IBM ObjectGrid for high-performance caching and transactional capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a systematic method for matching rule-sets with appropriate computing resources is implemented, then resource utilization efficiency is improved, but system complexity increases
Solution Approach 1:
An object cache framework is introduced as an intermediary layer between rule-sets and rules engines. The framework contains rule-set objects with criteria that automatically match with suitable rules engines, eliminating the need for complex manual matching logic while improving resource utilization efficiency.
Solution Approach 2:
Rule-sets are represented as copyable rule-set objects that can be stored in the object cache framework. These objects contain all necessary criteria and can be replicated and distributed to multiple rules engines, simplifying the matching process while maintaining efficiency.
2Loss of energy
If rule-sets are executed on distributed rules engines with optimized matching, then execution cost is reduced, but matching time increases
Solution Approach 1:
Rule-set objects are pre-configured with execution criteria (such as cost constraints, performance requirements) before being submitted to the object cache framework. This preliminary preparation enables rapid matching against pre-registered rules engines without requiring complex real-time analysis, thus reducing both matching time and execution cost.
Solution Approach 2:
The matching process utilizes configurable parameters within rule-set objects (such as cost thresholds, performance levels) that can be adjusted to balance matching time versus execution cost. By changing these parameters, the system can optimize for different operational requirements without fundamental redesign.
Data Source
AI summary
An object cache framework client selects a rule-set object in an object cache framework. The rule-set object comprises a rule-set (set of business rules). The object cache framework client evaluates criteria of the rule-set against properties of a plurality of rules engines. The object cache framework client determines if the properties of a rules engine, from a plurality of rules engines, satisfy the criteria of the rule-set. The object cache framework client supplies the rule-set object to the rules engine for execution of the rule-set.


