Service Invocation Chain Monitoring for Remuneration Optimization
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Solution Overview
Problem
Computer service invocation chains in distributed data processing systems are opaque, leading to inefficiencies in remuneration, where consumers incur higher than necessary costs due to lack of visibility into downstream dependencies, resulting in redundant payments for the same services.
Innovation Solution
A computing tool, SICOR, monitors and tracks service invocation chains using a directed acyclic graph (DAG) to identify dependencies and optimize remuneration by minimizing costs through an optimization algorithm applied to the cost function, updating usage metrics to reflect the least cost path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If service invocation chains are monitored with full visibility, then remuneration optimization is achieved, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary component (service invocation chain monitor) that sits between service consumers and providers to track invocations and calculate optimal remuneration. This mediator captures invocation data, maintains invocation chains, and determines cost optimizations without requiring changes to the underlying services, thus achieving visibility without proportional complexity increase in the core service infrastructure.
Solution Approach 2:
The patent replaces manual remuneration negotiation and tracking with an automated computational system that uses algorithms to analyze invocation chains and calculate optimal costs. This substitution of mechanical/negotiation-based processes with automated information processing reduces the complexity burden by making the monitoring system self-managing through standardized data collection and algorithmic optimization.
2Loss of energy
If downstream dependencies are made visible, then redundant payments are eliminated, but information processing complexity increases
Solution Approach 1:
The patent performs preliminary action by pre-establishing service registries that contain information about service dependencies and remuneration structures before actual service invocations occur. This advance preparation allows the monitoring system to quickly match invocations with known dependency relationships, eliminating redundant payments without requiring complex real-time analysis of dependency graphs during service execution.
Solution Approach 2:
The patent creates simplified copies or representations of service dependency relationships in the form of invocation chain data structures. Rather than processing the full complexity of actual service dependencies, the system maintains streamlined representations that capture essential remuneration-relevant information, making dependency visibility achievable with reduced information processing overhead.
3Productivity
If service invocation chains are tracked in detail, then cost optimization is achieved, but data processing requirements increase
Solution Approach 1:
The patent extracts only the essential remuneration-relevant information from service invocations, such as service identifiers, invocation counts, and dependency relationships. By filtering out unnecessary detailed data and focusing only on elements that impact cost calculation, the system achieves detailed tracking capability with reduced data processing volume, processing only what is needed for optimization rather than all possible invocation details.
Data Source
AI summary
Mechanisms are provided for optimizing remuneration for computing services. Computing services are registered which stores registration data comprising remuneration associations between computing services and consumers. A hierarchical computer model is generated based on the registration data, where the model represents dependencies between consumers and providers of computing services. For a service request from a consumer, each transaction with each computing service in a service invocation chain associated with the service request is identified and a cost of each transaction is calculated. The calculated cost of the service invocation chain is optimized based on applying an optimization algorithm to a cost function applied to a selected portion of the hierarchical computer model corresponding to the service invocation chain.