Remote Front-Drop Pipeline Stall Recovery
Solution Overview
Problem
Existing processing pipelines in IoT systems often experience stalls due to failure in processing incoming data within specified latency constraints, leading to recovery latency issues where older data is processed before newer data.
Innovation Solution
Implementing a remote front-drop strategy using a receiver-side dropping strategy driven from the sender-side, where the oldest events received by the pipeline are dropped first, even if they are waiting to be processed, to minimize recovery latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the pipeline processes data in FIFO order, then data processing order is maintained, but recovery latency increases because older data must be processed before newer data
Solution Approach 1:
The patent inverts the conventional FIFO processing approach by implementing a LIFO (Last-In-First-Out) processing strategy during pipeline stall recovery. The receiver drops oldest events first rather than processing them in order, allowing newer events to be processed immediately once the pipeline recovers, thus reducing recovery latency while maintaining event ordering integrity through timestamp-based selection
2Productivity
If the pipeline maintains all received data, then data completeness is preserved, but processing delay increases due to backlog of older data
Solution Approach 1:
The patent applies selective discarding of oldest events during pipeline stall conditions. The receiver monitors pipeline status and drops events based on their timestamps, allowing the system to recover from stalls by processing only the most recent events once the pipeline becomes available, thereby reducing processing delay while maintaining data completeness for critical events
3Reliability
If the sender queues data during pipeline stall, then data loss is prevented, but processing delay increases due to queuing time
Solution Approach 1:
The patent implements a feedback mechanism where the receiver sends signals to the sender about pipeline stall conditions and data status. Based on this feedback, the sender dynamically adjusts its queuing behavior, dropping oldest events when necessary to prevent processing delay while maintaining reliability through selective retention of critical events based on timestamps and priority
Data Source
AI summary
This disclosure describes techniques for performing a remote front-drop of data for recovery after a pipeline stall. The techniques include using a receiver-side dropping strategy that is driven from the sender-side. Components of a pipeline determine whether a pipeline is operating within specified latency constraints (e.g., experiencing a pipeline stall). Upon detecting a pipeline stall, the sending device is notified of the stall. Once the sending device is notified of the pipeline stall, the sending device can determine what action(s) to perform to address the pipeline stall. For example, the sending device may instruct one or more components of the pipeline to discard already sent data that has not been processed. This allows the older data to be dropped on the stalled pipeline while keeping the more recently sent data.