Distributed Computing

The component is responsible for executing computing tasks (eg, API calls to Docker setups to change the number of resources used) and distributes the intensive computing work tasks through a cluster, composed by a group of work nodes. So, computing performance is improved by splitting large tasks into smaller ones, reducing overall processing time. Finally, the results of intensive computing work tasks coming from different nodes are recombined and structured in the Manager node as the expected result type from the main task (API Call), returning to the requesting component.


  • Facilitates creation of logical structure for location of computational devices which can be used in efficient distribution of computational tasks at either Edge, Fog or Cloud level

  • Distribute computational task as per location constraints

  • Central orchestration for computational resources in different locations

  • Separating computing resources against each other to get more security

  • Central overview of resources and workloads

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Cluster Management

The component enables the registration of multiple Kubernetes clusters, providing a centralized view of the available cluster resources. This allows for efficient resource allocation and deployment of applications across different clusters.

Application Deployment

It facilitates the deployment of applications to the registered clusters, offering flexibility to deploy them to specific nodes or groups of nodes based on tags. This feature allows for optimized application distribution and utilization of computational resources.

Location and Resource Management

The component allows for the creation of a hierarchical structure of physical locations, such as factories or buildings, and the definition of computational resources within those locations. This enables better organization and management of resources based on their physical placement.

Distributed Task Execution

With locational constraints in mind, the component enables the execution of tasks in a distributed manner, taking into account the defined location and computational resources. It supports executing tasks in different environments like Fog or Edge, based on the specified location or resources.

Additional resources

Learn more about i4FS by visting the project website for general information, the wiki for information about the core components, the Technical Manual for API documentation, and downloading the repository’s source code.

Training Academy

Get a better understanding of the global architecture and information flow.

Source code

Our source code is opensource and available on our Gitlab repository.

Software Documentation

Read our easy to follow documentation to learn how to use the i4 Components.