State-Machine Data Broker for Sensor Publish-Subscribe Control
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Solution Overview
Problem
Conventional publish/subscribe architectures struggle with managing publisher clients that have limited capabilities or intermittent connectivity, leading to undesired behavior and inefficient data handling due to the inability to dynamically adjust their operations.
Innovation Solution
A data broker system that employs a state machine to monitor and manage publisher clients, allowing for the detection of unexpected behavior and enabling actions such as data suppression, new data generation, or control message modification to mitigate issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a conventional publish/subscribe architecture is used, then data can be transmitted between publisher and subscriber clients, but the system cannot dynamically adjust publisher behavior leading to inefficient data handling and undesired behavior from publisher clients with limited capabilities
Solution Approach 1:
The data broker monitors publisher client behavior patterns and uses this feedback to dynamically adjust data handling decisions. By analyzing historical data transmission patterns and publisher capabilities, the system can adapt its response to optimize data handling efficiency while maintaining reliable communication.
Solution Approach 2:
The system transitions from a static publish/subscribe architecture to a dynamic one where the data broker can adapt its behavior based on real-time conditions. The broker can modify data transmission decisions, filtering, routing, and processing strategies based on the current state of publisher clients and network conditions.
2Device complexity
If publisher clients operate with fixed behavior patterns, then implementation is simple, but unexpected behavior cannot be detected or managed
Solution Approach 1:
The data broker continuously monitors publisher client behavior and compares it against expected patterns. When unexpected behavior is detected, the system can respond by adjusting data handling, generating control messages, or modifying subscription processing to manage the publisher's behavior while maintaining system reliability.
3Loss of information
If all sensor data is forwarded to subscriber clients, then complete data availability is achieved, but unnecessary data transmission increases system overhead
Solution Approach 1:
The data broker applies different processing quality levels to different data based on publisher behavior analysis. For publishers showing unexpected or problematic behavior, the system can filter, modify, or suppress data transmission to reduce overhead, while maintaining full data availability for well-behaved publishers.
Solution Approach 2:
The system dynamically changes data handling parameters such as filtering thresholds, transmission timing, and data formatting based on publisher behavior patterns. This allows optimization of the balance between data availability and system overhead by adjusting parameters in response to real-time publisher performance.
Data Source
AI summary
A method performed at a data broker comprises receiving from a subscriber client a request for a subscription for sensor data transmitted by a sensor client, the request in accordance with a publish/subscribe messaging protocol, receiving sensor data from the sensor client, the sensor data published by the sensor client in accordance with the messaging protocol, and determining, in dependence on the sensor data and a current state of a state machine associated with the sensor client, whether the sensor data is to be subject to subscription processing. The method further comprises determining, in dependence on the receipt of the sensor data and the current state of the state machine, an updated state for the state machine, updating the state machine to the updated state, and if the data is to be subject to subscription processing, forwarding the data to the subscriber client in accordance with the messaging protocol.