Concurrent Event Detection for Distributed Rasterization
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Solution Overview
Problem
Production printers often experience downtime due to backhitches caused by the failure to deliver rasterized print data at the required rate, leading to costly delays and inefficiencies in high-volume printing operations.
Innovation Solution
An event detection system that analyzes logs from distributed computing nodes to identify concurrent events, allowing for rapid detection and graphical representation of issues, enabling operators to pinpoint the source of delays and prevent future occurrences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If rasterization is performed in real-time at the speed of the printer using massively parallel processing, then the printing speed is maintained, but the system complexity increases and the risk of backhitches increases
Solution Approach 1:
The system divides the rasterization workload into multiple segments processed by different compute nodes in a distributed computing system. Each node handles specific portions of the print data independently, allowing parallel processing while maintaining manageable complexity at each node level.
Solution Approach 2:
The system performs preliminary analysis of log files from each compute node to identify potential issues before they cause backhitches. By proactively detecting concurrent events and bottlenecks, the system can take preventive actions to maintain printing speed without requiring excessive system complexity.
2Measurement precision
If log files from all compute nodes are analyzed in detail to detect concurrent events, then the precision of event detection is improved, but the time required for analysis increases
Solution Approach 1:
The system performs preliminary indexing of log file events during or immediately after rasterization operations. Events are pre-organized with timestamps and node identifiers, so that when analysis is needed, the system can quickly retrieve and compare relevant events without re-processing entire log files, thus maintaining high detection precision while minimizing analysis time.
Solution Approach 2:
The system focuses analysis on specific time windows and node combinations where concurrent events are most likely to occur, rather than analyzing all possible event combinations across all nodes. This partial action approach maintains detection precision for critical events while significantly reducing overall analysis time.
3Reliability
If the system monitors and analyzes events from multiple compute nodes in real-time, then the reliability of print job completion is improved, but the processing overhead increases
Solution Approach 1:
The system performs event analysis periodically at key milestones in the print job process rather than continuously monitoring every event. This periodic approach maintains reliability by detecting issues at critical points while reducing processing overhead by avoiding constant analysis of all events throughout the entire rasterization process.
Solution Approach 2:
The system introduces an intermediary event detection layer that aggregates and filters events from multiple compute nodes before detailed analysis. This intermediary layer reduces the volume of data requiring intensive processing while maintaining reliability by ensuring that significant concurrent events are captured and analyzed.
Data Source
AI summary
Systems and methods are provided for event detection. One embodiment includes an interface that acquires logs, and a controller that is able to identify events recited in the logs, to include the events within a list sorted based on at least one of start times or end times indicated by the timing data, and to determine a longest duration of the events. The controller receives a requested time, calculates a prior time separated by the longest duration from the requested time, and processes the list by: identifying a first index of the list for a first event in time having a start time on or after the prior time, and identifying a last index of the list for a last event in time having a start time on or before the requested time. The controller generates a set of events bounded by the first index and the last index.