Context-Aware Service Orchestration for Dynamic Resource Placement
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Solution Overview
Problem
Existing service orchestration and management systems face challenges with static deployment schemes, resource bottlenecks, and inefficient resource utilization, requiring manual intervention and creating unnecessary computational overhead.
Innovation Solution
A system and method for dynamic orchestration and management of services using context and capability data, stored in repositories, to automatically adjust service configurations and placements without human intervention, optimizing resource use and avoiding bottlenecks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static deployment schemes are used, then device complexity is reduced, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent implements dynamic service deployment by replacing static deployment schemes with a context-aware orchestration system that automatically adjusts service configurations and placements based on real-time context data from multiple repositories, thereby improving resource utilization efficiency while managing complexity through automated decision-making
Solution Approach 2:
The system enables self-service deployment by using automated orchestration that parses service access requests, retrieves relevant context data from repositories, and automatically adjusts service configurations without requiring manual intervention, thus improving resource utilization while reducing operational complexity
2Adaptability or versatility
If manual intervention is required, then adaptability to service requestors' needs is improved, but productivity deteriorates
Solution Approach 1:
The system implements self-service orchestration by automatically parsing service access requests, retrieving context data from repositories, and adjusting service configurations without manual intervention, thereby maintaining adaptability to service requestors' needs while significantly improving deployment speed and productivity
Solution Approach 2:
The system uses feedback mechanisms by continuously monitoring service access requests and context data from repositories, automatically adjusting service configurations based on this feedback, thus achieving both adaptability to changing needs and high productivity through automated closed-loop control
3Productivity
If dynamic orchestration is implemented, then resource utilization is optimized, but device complexity increases
Solution Approach 1:
The patent manages orchestration complexity by segmenting the system into distinct functional components: service access request parsing, context data retrieval from multiple repositories, context data analysis, and service configuration adjustment. This modular architecture optimizes resource utilization while making the complex orchestration process manageable and maintainable
4Productivity
If automated adjustment is used, then productivity is improved, but computational overhead increases
Solution Approach 1:
The system applies partial action by selectively retrieving and processing only the specific context data relevant to each service access request from the repositories, rather than processing all available data. This approach improves deployment automation efficiency while minimizing unnecessary computational overhead through targeted data retrieval and analysis
Data Source
AI summary
Methods and systems for managing service deployment are disclosed. To deploy services, dependencies and other characteristics (such as context data, capability data, placement rules, and workflow data) of services and the infrastructure boundaries in which the services are running may be dynamically collected, analyzed and updated. By dynamically analyzing dependencies and other characteristics (such as context data, capability data, placement rules, and workflow data) of services and the infrastructure boundaries, efficiency of use of computing resources may be improved by recycling existing workflow; statically defined operations and hard-coded conditional logic of services may also be avoided each time an environment in which the services are running has changed.