Heartbeat Listener for Event-Driven Data Reprocessing After Reconnection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Data processing pipelines face issues with bandwidth management and inaccurate calculations due to devices going offline, causing large volumes of past data to be transmitted and persisted without proper context, leading to resource scaling challenges and delayed system updates.
Innovation Solution
Implement a heartbeat listener module that tracks device health status, provides metadata to the data loader for efficient persisting of past data, and triggers unscheduled execution of the fact modeler to ensure timely and accurate system updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If devices transmit all past data upon reconnection, then data completeness is improved, but bandwidth consumption increases
Solution Approach 1:
The patent extracts only the essential metadata (device identifier, timestamp, status) from the full data packets transmitted during downtime. This selective extraction reduces bandwidth consumption while maintaining data completeness, as the metadata enables the server to reconstruct and process the full data set efficiently without receiving redundant information.
Solution Approach 2:
The system performs preliminary actions by having devices store data locally during downtime and prepare metadata in advance. When reconnection occurs, the pre-prepared metadata is transmitted first, allowing the server to anticipate and efficiently process the incoming data stream, reducing overall bandwidth requirements compared to transmitting complete data sets.
2Measurement precision
If the system waits for past data to be persisted before processing, then data accuracy is improved, but system responsiveness deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the server continuously monitors for reconnection events and triggers processing operations based on real-time status changes. When metadata indicates device reconnection, the system immediately initiates data retrieval and processing, ensuring both accuracy (by waiting for complete data) and responsiveness (by triggering processing as soon as data arrives).
Solution Approach 2:
The system performs preliminary actions by pre-configuring processing pipelines and maintaining ready-state computational resources. When past data arrives, the pre-prepared processing infrastructure can immediately act on the data without delay, achieving both accuracy through complete data processing and responsiveness through pre-positioned processing capabilities.
3Stability of the object's composition
If the fact modeler processes data on a fixed schedule, then system stability is improved, but data freshness deteriorates
Solution Approach 1:
The patent transforms the static, fixed-schedule processing model into a dynamic, event-driven model. The fact modeler now adapts its execution timing based on real-time events such as device reconnections and data arrivals. This dynamic approach maintains system stability through structured processing while improving data freshness by triggering processing immediately when data becomes available, eliminating unnecessary delays.
4Productivity
If resources are scaled to handle peak data transmission, then data processing capacity is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent implements periodic, event-triggered processing actions instead of continuous resource allocation. The system activates data processing resources periodically based on specific events (device reconnections, data arrivals) rather than maintaining constant high-capacity resources. This approach provides sufficient processing capacity during data transmission events while avoiding the energy waste of maintaining peak resources during idle periods.
Data Source
AI summary
A system for handling temporal delays in data processing, which has one or more devices configured to transmit data, the data comprising at least one of device status, downtime data, uptime data, metadata of the downtime data, a heartbeat listener operatively connected to the one or more devices and configured to receive the device status, a data loader operatively connected to the one or more devices and configured to persist the uptime data, a fact modeler configured to process the uptime data persisted by the data loader. The heartbeat listener determines from the device status, the downtime duration of one or more devices, transmits the metadata of the downtime data associated with the downtime duration of the one or more devices to the data loader, such that the data loader is further configured to receive and persist the downtime data from one or more devices and triggers the fact modeler to re-process the uptime and downtime data persisted by the data loader.