Stream Processing Network Load Management for Time-Critical Data

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Solution Overview

Problem

Current stream processing technologies fail to dynamically manage load and meet specific time constraints, leading to delays and reduced throughput in time-critical applications, such as real-time monitoring and analysis in industrial domains.

Innovation Solution

A method and system that incorporate load management modules on processing elements to collect and manage load information, with a load control unit that dynamically adjusts processing and data routing to ensure data items meet time constraints, including dropping items that cannot be processed in time, thereby optimizing resource allocation and reducing bottlenecks.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Speed

If stream processing engines output results as fast as possible with best-effort delivery, then processing speed is improved, but end-to-end latency constraints are not met

Engineering Contradiction:

Improveprocessing speedVSAvoidend-to-end latency

Core Design Contradiction:

SpeedVSLoss of time

Solution Approach 1:

The system dynamically adjusts processing behavior based on current load conditions and time constraints. Processing elements monitor their own load and the load of other PEs, and adaptively route data items to appropriate PEs that can meet time constraints, rather than using static processing assignments.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system implements feedback mechanisms where processing elements report their load status to a coordinator, which then makes routing decisions. This closed-loop control ensures that data items are directed to processing elements that can meet their time constraints while balancing the overall system load.

Inventive Principle:

Principle #23Feedback

2Productivity

If a high system load is present, then more data items can be processed, but substantial delays occur and time constraints are violated

Engineering Contradiction:

Improvedata processing throughputVSAvoidprocessing delay

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

A coordinator PE acts as an intermediary that receives load status reports from all processing elements and makes centralized routing decisions. This mediator balances the load across the system by directing new data items to PEs with available capacity, preventing any single PE from becoming overloaded and causing delays.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system divides the processing workload across multiple processing elements, each handling specific data items based on their current capacity. This segmentation allows parallel processing while maintaining the ability to dynamically reallocate work based on load conditions, preventing bottlenecks.

Inventive Principle:

Principle #1Segmentation

3Reliability

If data items are discarded when time constraints cannot be met, then output data quality is improved, but data loss increases

Engineering Contradiction:

Improvetime constraint satisfactionVSAvoiddata loss

Core Design Contradiction:

ReliabilityVSLoss of substance

Solution Approach 1:

The system performs preliminary routing decisions before processing, using load information and time constraint analysis to direct data items to PEs that can meet their deadlines. This proactive approach prevents data items from being discarded by ensuring they are assigned to appropriate processing elements from the start.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system changes routing parameters based on current system state, including load levels and time constraints. By dynamically adjusting which PE processes which data item based on these parameters, the system maximizes the amount of data that can be processed in time while minimizing unnecessary discards.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentEP2963875B1Method for processing data streams including time-critical messages of a power network

Publication Date: 2018.02.28 ABB (SCHWEIZ) AG

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AI summary

The present invention relates to a method for processing data stream within a time constraint by a stream processing network comprising a plurality of processing elements, wherein the method comprises the steps of: determining a processing unit, by selecting at least one of the plurality of processing elements, for transmitting next data items of the data stream; collecting system information of the processing unit, wherein the system information includes load information of the selected processing element; adapting, based on the system information, sending rate of the stream data; discarding, by the processing unit, data items of the data stream that would not be processed within the time constraint; and sending, by the processing unit, data items of the data stream that would be processed within the time constraint.