Dynamic Manifests for Script-Consistent IoT Payload Transmission
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Solution Overview
Problem
Existing systems lack an efficient method to determine and manage payload transmission operations from IoT devices, as scripts and content vary across devices, leading to inconsistent and potentially outdated transmissions.
Innovation Solution
A dynamic manifest system that uses a machine learning model to predict content and determine operations for payload transmission based on device attributes, location, and criticality, ensuring scripts are up to date and safe to transmit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If scripts are periodically transmitted from devices to servers, then device information can be collected and managed, but the scripts may be outdated or inconsistent across different devices
Solution Approach 1:
The patent implements dynamic manifests that are continuously updated on the server and automatically retrieved by devices. This dynamic approach ensures that each device receives the latest script versions and operational instructions in real-time, eliminating the staleness issue of periodic updates while maintaining consistency across the distributed IoT network.
Solution Approach 2:
The system employs feedback mechanisms where devices report their current script versions and operational status to the server. The server then determines whether updates are needed and pushes relevant manifest changes back to devices, creating a closed-loop system that maintains script consistency without requiring continuous polling or manual updates.
2Productivity
If device attributes and locations are continuously monitored, then payload transmission can be optimized, but system complexity increases
Solution Approach 1:
The patent pre-computes and stores optimal payload transmission strategies in dynamic manifests during periods when devices are not actively transmitting. These manifests contain pre-determined operational instructions based on device attributes and location data, allowing the system to make intelligent transmission decisions without requiring complex real-time calculations, thus reducing operational complexity while maintaining high productivity.
3Productivity
If dynamic manifests are used to determine payload transmission operations, then transmission efficiency improves, but information processing requirements increase
Solution Approach 1:
The patent extracts and isolates only the critical device attributes and location data that are necessary for determining payload transmission operations. Rather than processing all available device information, the system identifies and extracts the minimal necessary subset of data to populate dynamic manifests, reducing the overall data processing volume while maintaining transmission efficiency.
Solution Approach 2:
The system applies local quality optimization by tailoring the amount and type of data processing to each specific device's characteristics and operational context. Different devices receive differently optimized manifest data based on their specific attributes, location, and transmission needs, avoiding unnecessary processing of data that would not contribute to transmission efficiency for particular devices.
Data Source
AI summary
Techniques for determining operations for transmitting information from a device on a network are disclosed. Using information identifying a device type and a version of the script executing on the device, the system computes a first dynamic manifest for the device that provides a set of operations for execution in relation to the device. This may include checking the version of the script executing on the device. The system provides an up-to-date version of the script to the device and instructs the device to update the script. The device receives and stores the updated version of the script and initiates a script restart. Upon restarting the script, the device executes the updated version of the script. The system then computes a second dynamic manifest for the device that provides another set of operations for execution in relation to the device.