Service-to-Device Mapping for Smart Items
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Solution Overview
Problem
Existing smart item technologies face challenges in reliably deploying services onto sensor networks due to non-meetable deployment conditions, leading to partial or failed deployments, which hinders efficient business process execution and data collection.
Innovation Solution
A system that includes a service mapper and system monitor to initiate service deployments on sensor network devices, altering deployment conditions through requirement reduction, network reconfiguration, and component removal logic to ensure allowable deployment conditions are met, thereby ensuring successful service execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If services are deployed onto sensor network devices using existing smart item technologies, then service deployment is initiated, but deployment conditions are not met leading to partial or failed deployments
Solution Approach 1:
The system performs preliminary evaluation of deployment conditions before actual service deployment. The service mapper assesses whether deployment conditions are met, and if not, proactively alters conditions by removing non-critical components or requirements before deployment attempts, preventing failed deployments rather than recovering from them
Solution Approach 2:
The system dynamically changes deployment parameters and conditions based on current sensor network state. When deployment conditions are not met, the service mapper modifies deployment parameters such as resource requirements, service components, or target device selection to create acceptable deployment conditions that satisfy both service requirements and network capabilities
2Manufacturing precision
If deployment conditions are strictly enforced, then deployment quality is maintained, but deployment success rate decreases due to partial or failed deployments
Solution Approach 1:
The service mapper applies partial enforcement of deployment conditions by identifying and removing non-critical components or relaxed requirements when full condition satisfaction is not possible. This allows deployment to proceed with reduced but acceptable quality, maintaining productivity while preserving essential deployment standards through selective condition enforcement
Solution Approach 2:
The system dynamically adjusts deployment conditions based on real-time sensor network state and service requirements. Deployment criteria are not fixed but adaptively modified during the deployment process, allowing the system to transition between strict enforcement when conditions are met and flexible enforcement when conditions must be altered, optimizing both quality and success rate
3Device complexity
If manual data collection methods are used in centralized back-end systems, then data storage is simplified, but data collection accuracy and timeliness decrease
Solution Approach 1:
The system segments data collection and processing functions across distributed sensor network devices rather than centralizing them. Each device independently collects and processes local data with high accuracy and timeliness, then shares results through ad-hoc networks, maintaining simplicity at the backend while achieving high data quality through distributed intelligence
Data Source
AI summary
Systems and methods allow service-to-device mapping by which services are mapped onto best-suited smart items selected from a plurality of smart items of a sensor network. As part of the mapping, and/or subsequent thereto, a deployment of the service(s) onto the smart items is initiated. However, in some cases, the deployment may fail, or may only partially succeed. In such cases, one or more conditions of the deployment may be altered to obtain a modified, allowable deployment condition, so that the deployment may then proceed. As a result, users may achieve a desired result in a fast, convenient, and reliable manner, even when executing the deployment remotely or automatically.