Dynamic Workflow Management via Federated Controller Occupancy Monitoring
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Solution Overview
Problem
As device ecosystems grow in complexity, determining the optimal deployment of workflow components across diverse devices becomes challenging due to increased data and device connectivity, making it difficult to meet service level objectives (SLOs) and manage resource utilization efficiently.
Innovation Solution
A method and system where a federated controller, comprising service and platform controllers, map workflows to appropriate ecosystem portions based on capability and capacity information, monitor occupancy, and perform remediation actions when thresholds are exceeded, ensuring efficient resource use and deployment across domains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If workflows are deployed in complex device ecosystems with more data and devices, then the system can handle more diverse workloads and increase productivity, but it becomes difficult to determine optimal deployment locations and manage resource utilization efficiently
Solution Approach 1:
The patent segments the device ecosystem into multiple domains, each managed by a platform controller. Workflows are divided into workflow portions that can be independently deployed to different domains. This segmentation allows the system to handle complex workloads by distributing them across multiple manageable domains rather than treating the entire ecosystem as a single complex unit.
Solution Approach 2:
The patent introduces service controllers as intermediary components between workflow submissions and platform controllers. Service controllers receive workflow portions, determine appropriate target domains based on capability and capacity information, and coordinate the deployment. This intermediary layer simplifies the complexity of direct workflow-to-domain matching by providing an abstraction that handles the decision-making logic.
2Adaptability or versatility
If more devices and data are added to the ecosystem, then the system can support more workflows and increase versatility, but it becomes difficult to determine where to deploy workflow components
Solution Approach 1:
The patent performs preliminary actions by having platform controllers continuously discover and maintain capability and capacity information about their respective domains before workflows need to be deployed. Service controllers use this pre-collected information to quickly determine appropriate deployment locations without needing to analyze the entire ecosystem at deployment time, thus reducing the difficulty of location determination.
Solution Approach 2:
The patent implements feedback mechanisms where platform controllers monitor occupancy levels and resource capacity in their domains, and this information is fed back to service controllers. Service controllers use this feedback to make informed decisions about where to deploy workflow portions, selecting domains that have appropriate capabilities and available capacity, thereby simplifying the deployment location determination process.
3Reliability
If workflow portions are monitored for occupancy and remediation actions are performed when capacity is exceeded, then resource utilization is optimized and system reliability is improved, but additional monitoring and control mechanisms are required
Solution Approach 1:
The patent implements continuous monitoring of workflow portion occupancy in each domain, with platform controllers tracking resource usage and comparing it against available capacity. When occupancy exceeds capacity thresholds, the system triggers remediation actions such as redistributing workflow portions to other domains. This feedback loop ensures service level objectives are maintained while the automated nature of the monitoring reduces the complexity of manual management.
Solution Approach 2:
The patent enables the system to self-regulate by automatically performing remediation actions when capacity constraints are detected. Service controllers autonomously redistribute workflow portions from overloaded domains to underutilized domains without requiring external intervention. This self-service capability improves reliability by maintaining service levels while reducing the operational complexity of manual resource management.
Data Source
AI summary
Techniques described herein relate to a method for deploying workflows. The method may include receiving, by a platform controller of a domain, a workflow portion and workflow constraints from a service controller of a federated controller, provisioning, by the platform controller, a set of devices in the domain to the workflow portion, executing the workflow portion in the domain using the set of devices, monitoring the executing of the workflow portion to determine an occupancy of the workflow portion, making a determination that the occupancy of the workflow portion exceeds an available capacity of the domain, providing, based on the determination, the occupancy to the service controller, and in response to the occupancy, performing, by the service controller, a remediation action.