Workflow Simulation Using Provenance Data Similarity

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Solution Overview

Problem

Modern industrial systems face challenges in determining the impact of resource allocation changes on workflow execution states and dynamics, particularly in allocating CPUs and memory for tasks like data mining and image processing, where historical data is leveraged for simulation-driven optimization but requires improved techniques for mapping new system states.

Innovation Solution

The method employs provenance data similarity and sequence alignment to simulate workflow executions by identifying anchor states and generating new simulation traces for resource allocation configurations not represented in the data, using linear or non-linear mapping functions based on task completion criteria and resource consumption metrics.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If historical provenance data is used for simulation-driven workflow optimization, then resource allocation can be improved, but the ability to accurately determine the impact of resource allocation changes on new system states deteriorates

Engineering Contradiction:

Improveresource allocation efficiencyVSAvoidsystem state prediction accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent performs preliminary actions by identifying anchor states in historical execution traces before generating new simulation traces. These anchor states serve as reference points that capture key system states, allowing the mapping function to predict new system states by comparing them against pre-identified anchor states rather than relying solely on historical provenance data.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary mapping function that bridges historical provenance data and new system state predictions. This mapping function uses anchor states as intermediaries to transform and adapt historical execution patterns to new resource allocation scenarios, enabling accurate prediction without directly copying historical data.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If mapping functions are used to determine new system states after resource allocation changes, then workflow optimization can be achieved, but handling complex workflows with varying task orders and resource usage becomes difficult

Engineering Contradiction:

Improveworkflow optimization capabilityVSAvoidmapping function complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments complex workflows into discrete execution traces with identifiable anchor states. By dividing the workflow execution into segments bounded by anchor states (which represent significant milestones or completion points), the mapping function can handle each segment independently, reducing the overall complexity of processing entire complex workflows.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent changes parameters by using anchor states that capture essential workflow characteristics while abstracting away detailed variations. This parameter transformation allows the mapping function to work with simplified representations of complex workflows, maintaining adaptability while reducing computational complexity.

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If anchor states are identified and execution traces are mapped between different resource allocation configurations, then simulation accuracy improves, but the computational effort and data processing requirements increase

Engineering Contradiction:

Improveexecution trace mapping accuracyVSAvoidsimulation processing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent performs preliminary action by pre-identifying anchor states in historical execution traces before the actual simulation process. These pre-identified anchor states serve as fixed reference points that reduce the computational burden during new simulations, as the system only needs to map against these predetermined states rather than analyzing entire execution traces in real-time.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent extracts only the essential anchor states from complete execution traces, separating the critical information needed for accurate mapping from the redundant detailed data. This extraction process reduces data processing requirements while maintaining the accuracy needed for effective simulation and resource allocation optimization.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS11263369B2Workflow simulation using provenance data similarity and sequence alignment

Publication Date: 2022.03.01 EMC IP HLDG CO LLC

AI summary

Techniques are provided for workflow simulation using provenance data similarity and sequence alignment. An exemplary method comprises: obtaining a state of workflow executions of concurrent workflows with multiple resource allocation configurations, wherein the state comprises provenance data of the concurrent workflows; obtaining execution traces of the concurrent workflows representing different resource allocation configurations; identifying a set of states in a first execution trace and a set of states in a second execution trace as corresponding anchor states; mapping a first intermediate state to a second intermediate state between a pair of anchor states using the provenance data; generating a simulation model of the workflow executions representing the different configurations of the resource allocation; and generating new simulation traces of the workflow executions with resource allocation configurations that are not represented in the provenance data.