Hierarchical Service Mapping for Smart Item Deployment
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Solution Overview
Problem
Existing smart item technologies face challenges in efficiently mapping services to appropriate devices within networks, particularly in determining the optimal device for service deployment based on complex metadata matching and dynamic resource availability.
Innovation Solution
A system and method for service-to-device mapping that involves determining service metadata and device metadata, applying weighted formulas to select the most suitable device for service deployment, and utilizing a hierarchical architecture with global, local, and group service mappers to optimize service execution across smart item devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex metadata matching and device querying is performed to determine optimal service deployment, then service deployment accuracy and resource utilization improve, but system complexity and processing time increase
Solution Approach 1:
The system divides the service mapping functionality into multiple tiers: global service mappers at the enterprise level, local service mappers at the facility level, and group service mappers at the device level. This segmentation allows each tier to handle specific aspects of service deployment independently, reducing overall system complexity while maintaining deployment accuracy through coordinated metadata matching across all tiers.
Solution Approach 2:
Service mappers act as intermediary components between services and devices, performing metadata matching and device selection. These mappers translate service requirements into device-specific deployment decisions, simplifying the overall system architecture by centralizing the complex matching logic in dedicated intermediary components rather than distributing it across all system elements.
2Manufacturing precision
If comprehensive device metadata is collected and analyzed to match service requirements, then service deployment optimality improves, but information processing time and computational resources increase
Solution Approach 1:
The system performs preliminary device discovery and metadata collection before service deployment decisions are made. Devices proactively provide their metadata information to service mappers in advance, allowing the mappers to have pre-indexed device capabilities ready when service deployment requests arrive, thereby reducing processing time while maintaining deployment optimality.
Solution Approach 2:
The service mapping system dynamically adjusts matching parameters and weighting factors based on service requirements and device capabilities. By changing the relevance weights of different metadata parameters according to the specific service being deployed, the system optimizes the matching process to focus on the most critical parameters, reducing processing time while maintaining deployment quality.
3Adaptability or versatility
If dynamic service re-deployment is enabled to adapt to changing device resources, then system adaptability and reliability improve, but deployment frequency and operational complexity increase
Solution Approach 1:
The service mapping system implements continuous feedback mechanisms where service mappers monitor device resource availability and service performance in real-time. When changes in device metadata or resource availability are detected, the feedback loop triggers automatic re-evaluation and potential re-deployment of services, enabling dynamic adaptation without requiring manual intervention or increasing operational complexity.
Solution Approach 2:
The system transitions from static service-device mapping to dynamic mapping where service assignments can automatically change in response to evolving device capabilities and resource availability. Service mappers continuously evaluate current system state and adjust service deployments dynamically, allowing the system to adapt to changes while maintaining automated operation and avoiding manual complexity.
Data Source
AI summary
A service repository is used to store at least one service in association with service metadata describing service requirements of the service. The service repository also may store one or more platform-specific service executables. A service mapper is used to determine device metadata associated with each of a plurality of devices, where the device metadata provides device characteristics of the devices. The service mapper may thus map the service to a selected device of the plurality of devices for deployment thereon, based on a matching of corresponding elements of the service requirements and the device characteristics. The service mapper also may re-map the service between devices to maintain a quality and reliability of the service.