AI-Based Dynamic Service Binding for Client-Server Compatibility
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Solution Overview
Problem
Existing systems require clients to be hardwired to a specific server-side service version, necessitating mandatory upgrades when the server version changes, limiting flexibility and efficiency in service binding.
Innovation Solution
Implementing a cognitive analysis system using artificial intelligence at both client and server sides to dynamically determine client capabilities and bind the appropriate service version, allowing loose coupling and avoiding the need for client upgrades during server-side version updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the server-side service version is updated, then the service functionality is improved, but the client must also be upgraded to maintain compatibility
Solution Approach 1:
The patent implements dynamic service version binding where the client is not fixed to a specific service version. Instead, the system dynamically determines which service version to bind based on real-time capability assessment. The cognitive engine evaluates client capabilities and automatically selects the appropriate service version, allowing the binding to adapt when server versions are updated without requiring mandatory client upgrades.
Solution Approach 2:
The system changes the binding parameter from a static client-side version number to a dynamic capability-based selection. The cognitive agent and cognitive engine exchange capability information and use this data to determine the appropriate service version binding, transforming the rigid version matching into a flexible parameter-based selection process.
2Stability of the object's composition
If the client is hardwired to a specific service version, then the service binding is stable, but the client cannot adapt to server-side version updates
Solution Approach 1:
The patent introduces a cognitive agent as an intermediary between the client and the service version binding process. This agent assesses client capabilities and communicates with the cognitive engine to determine appropriate bindings. The intermediary layer decouples the direct hardwired connection between client and service version, allowing stable bindings to be maintained while enabling adaptability through capability-based selection.
Solution Approach 2:
The system performs preliminary capability assessment through the cognitive agent before establishing service bindings. By evaluating client capabilities in advance and selecting appropriate service versions based on this assessment, the system ensures stable bindings are formed initially while maintaining the ability to adapt when conditions change, such as server version updates.
3Reliability
If mandatory client upgrades are required, then service compatibility is maintained, but system complexity and upgrade burden increase
Solution Approach 1:
The patent implements a self-service mechanism where the cognitive engine automatically determines appropriate service version bindings based on client capability assessments. The system autonomously selects and binds appropriate service versions without requiring manual upgrade management or forcing clients to upgrade. This self-service approach maintains compatibility while eliminating the complexity of mandatory upgrade processes.
Data Source
AI summary
Cognitive analysis, including artificial intelligence, is implemented to dynamically determine service discovery and service binding. Specifically, cognitive analysis is used to determine a client's capabilities and based on the capabilities, a service version is selected and coupled/bound to the client. As a result of such loose coupling/binding with service signatures, service version upgrade at the client is not mandatory in the event of a server-side service version upgrade.