IoT App Metadata Deployment for Low-Latency Local Interconnectivity
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Solution Overview
Problem
Existing IoT systems rely heavily on cloud computing for interconnection, leading to high latency, network dependency, and compromised privacy, while decentralized solutions fail to provide efficient, user-centric, and flexible interaction and interconnection among IoT devices.
Innovation Solution
A decentralized approach that allows IoT applications to be deployed and run autonomously on various nodes within an IoT network, utilizing a configuration of computing hardware and programmable memory to automatically generate user interfaces and optimize interconnections based on developer-provided metadata, enabling 'write once, run anywhere' functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud computing is used for interconnection between IoT devices, then centralized control and management are achieved, but latency increases and network dependency is created
Solution Approach 1:
The patent segments the centralized cloud-based control architecture into distributed edge computing nodes deployed at network perimeters and local premises. This segmentation allows IoT devices to communicate locally without always routing through the cloud, reducing latency while maintaining centralized management capabilities for updates and security.
Solution Approach 2:
The patent introduces edge computing nodes as intermediary components between IoT devices and the cloud. These nodes provide local processing and routing capabilities, enabling devices to interact with minimal cloud dependency while still allowing centralized cloud services to perform coordination, security management, and data aggregation functions.
2Ease of operation
If cloud computing is used for interconnection between IoT devices, then centralized control is achieved, but network dependency increases
Solution Approach 1:
The architecture segments control functions between edge nodes and cloud services. Edge nodes provide autonomous local control for immediate device interactions, while cloud services handle high-level management, security policies, and coordination. This segmentation ensures operations continue locally even when cloud connectivity is unavailable.
Solution Approach 2:
Edge computing nodes are designed to autonomously manage local IoT device communications and control without requiring constant cloud intervention. They can independently route messages, enforce security policies, and maintain device operations, making the network self-sufficient while still allowing centralized cloud management when needed.
3Loss of time
If decentralized approach is used for IoT application deployment, then latency is reduced and privacy is enhanced, but device complexity increases
Solution Approach 1:
The patent employs containerization technology that packages entire application environments with all necessary dependencies, libraries, and configuration files into standardized units. This universal container format can be deployed across diverse IoT devices and edge nodes regardless of underlying hardware differences, simplifying decentralized deployment while maintaining low latency through local execution.
Solution Approach 2:
The patent uses virtualization and containerization to create lightweight copies of application environments that can be replicated across multiple devices. Instead of deploying complex native applications to each device, standardized container images are copied and executed locally, reducing deployment complexity while enabling fast local processing and enhanced privacy.
4Loss of information
If decentralized approach is used for IoT application deployment, then privacy is enhanced, but interconnection efficiency decreases
Solution Approach 1:
The patent introduces edge computing nodes as intermediary components that enable secure local communication between IoT devices without requiring data to traverse the public internet. These intermediaries establish direct peer-to-peer connections locally, enhancing privacy by keeping data within the local network while maintaining high interconnection efficiency through proximity-based communication.
Data Source
AI summary
An Internet of Things Controller and its new related tools. A Metadata Editor permits a developer of an App to specify metadata that automatically guides each deployment of the App within an end-user's particular network of IoT devices. Once an App is developed, the developer can upload the App to an online App Store, from which the App can be downloaded and deployed by end-users. A Data Editor enables end-users to create their own data, following the developer's metadata, thereby adapting the execution to their specific needs. While permitting adaptation, the Data Editor ensures the data created follows the overall pattern of the metadata, as provided by the developer. Facilities for internationalization of a deployed App's documentation, on a crowd-source basis, are also provided. Apps are “write once, run everywhere” on IoT controllers and devices to achieve optimal security, privacy, safety, power consumption, latency, and bandwidth utilization.