Dynamic Message Schema Control for IoT Congestion
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Solution Overview
Problem
The increasing number of IoT devices leads to communication congestion, resulting in message loss and increased network load, especially during equipment failures, which existing technologies struggle to manage effectively.
Innovation Solution
Implementing a dynamic message schema system that adjusts message packaging based on network congestion, using three schemas (SSS, SDS, and MDS) to optimize data transfer efficiency by changing the schema and size in response to operational context and network conditions, allowing for efficient data flow even during peak loads or device growth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the number of IoT devices is increased to expand network coverage and functionality, then the utility and data collection capability are improved, but communication congestion occurs leading to message loss and increased network load
Solution Approach 1:
The patent implements dynamic message schema selection that adapts to current network conditions. The system monitors network congestion levels and automatically adjusts the message schema (SSS, SDS, or MDS) to optimize data transmission. This dynamic adaptation allows the system to maintain reliable message delivery even as the number of devices increases and network conditions vary.
Solution Approach 2:
The system changes the parameter of message schema structure based on network conditions. By switching between different schema types (SSS with full device identifiers, SDS with shortened identifiers, MDS with aggregated data), the system optimizes message size and transmission efficiency, thereby improving reliability under different device quantities and network loads.
2Loss of energy
If message schema size is increased to reduce message frequency, then network load is reduced, but message processing time and latency increase
Solution Approach 1:
The system dynamically adjusts message schema size based on real-time network conditions and operational context. During periods of low network load, larger schemas (MDS, SDS) are used to reduce message frequency. When latency becomes critical, the system switches to smaller schemas (SSS) to reduce processing time, thereby balancing network load reduction with acceptable response times.
Solution Approach 2:
The system uses partial aggregation of data in messages depending on conditions. Instead of always sending complete aggregated data (excessive action), the system sends only necessary data portions based on schema type, balancing the trade-off between reducing message frequency and maintaining acceptable processing speeds.
3Ease of operation
If message schema is simplified to reduce processing complexity, then ease of operation is improved, but data completeness and measurement precision may be compromised
Solution Approach 1:
Different message schemas are used for different local conditions and data types. The SSS schema provides complete device identifiers for individual device messages, SDS provides shortened identifiers for reduced complexity, and MDS provides aggregated data for high-level monitoring. The system selects the appropriate schema based on the specific operational context, maintaining data completeness where needed while simplifying processing where appropriate.
Data Source
AI summary
A method and apparatus for controlling message schema and size for internet-of-things (IoT) devices is provided. An exemplary method includes receiving an orchestration message from a downstream device, and calculating a new message size for a current schema, based, at least in part, on the orchestration message. A data message using the new message size and the current schema.