IoT Communication System Using Hardware Abstraction Layer for Adaptive Data Transfer
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Solution Overview
Problem
Existing communication systems in the Internet of Things face challenges in ensuring robust and flexible data transmission between diverse data generation units and evaluation units, particularly in handling unforeseeable network influences and maintaining consistent functionality across different measurement paradigms.
Innovation Solution
The implementation of a communication system with a hardware abstraction layer that represents data evaluation units as resources with a 'data transmission type' property, allowing for adaptive data transfer modes such as 'Streaming' or 'Bulk Upload' to ensure robustness and consistency, and aligning with the measurement paradigms of the evaluation units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data transmission uses fixed protocols without abstraction layers, then implementation is simple, but adaptability to diverse data generation units is poor
Solution Approach 1:
The patent introduces a hardware abstraction layer as an intermediary component between the communication system and diverse data generation units. This abstraction layer provides standardized interfaces and protocols, enabling the system to adapt to various data generation units without modifying the core communication architecture. The abstraction layer acts as a mediator that translates between different hardware interfaces and the unified communication protocol.
Solution Approach 2:
The communication system is designed with universal interfaces and protocols that can work with multiple types of data generation units through the abstraction layer. The system provides multi-functional capability to handle different data formats, transmission protocols, and hardware interfaces while maintaining a consistent evaluation unit interface, thereby achieving versatility without proportionally increasing complexity.
2Reliability
If the system adapts to network availability dynamically, then robustness against unforeseeable influences improves, but system complexity increases
Solution Approach 1:
The communication system implements dynamic adaptation to network conditions by allowing the evaluation unit to flexibly adjust data reception and processing based on network availability. The system can switch between different operational modes (e.g., real-time processing, buffered processing, or offline evaluation) depending on network status, thereby maintaining reliability without requiring complex predetermined configurations for every possible network scenario.
Solution Approach 2:
The system changes operational parameters such as data transmission rate, buffer size, and processing timing based on network availability conditions. By dynamically adjusting these parameters rather than changing the fundamental system architecture, the patent achieves robustness against network failures while controlling the increase in system complexity.
3Measurement precision
If data transmission follows strict real-time requirements, then measurement consistency is maintained, but flexibility to network conditions decreases
Solution Approach 1:
The system performs preliminary actions by buffering data and pre-processing information when network conditions are favorable, allowing real-time measurement requirements to be met when data is available. When network conditions deteriorate, the system can operate with cached or previously processed data, maintaining measurement consistency while adapting to reduced network availability.
Solution Approach 2:
The communication system implements periodic data synchronization and evaluation cycles that maintain measurement paradigm consistency. By using periodic action, the system ensures that measurements are taken at regular intervals according to the evaluation unit's measurement paradigm, while allowing flexibility in how data is transmitted and buffered between these periodic evaluation points based on network conditions.
Data Source
AI summary
A communication system includes data generation units that generate data and a plurality of data evaluation units physically separated from the data generation units and connected to the data generation units via a non-proprietary network. The data evaluation units evaluate data transmitted by the communication system, which includes a hardware abstraction layer that represents a data evaluation unit as a resource that includes a property “data transmission type.” The property “data transmission type” is “Streaming” or “Bulk Upload” or “Streaming, Bulk Upload”. The communication system reads the property “data transmission type” and accordingly transmits the generated data to the data evaluation unit in accordance with the read property “data transmission type”.