Virtual Data Container (VDC)

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The DITAS Project

• What is trying to solve?• Current applications are eager to acquire and consume

more and more amounts of data

• Data is coming from distributed heterogeneous devices (IoT and mobile applications)

• Need to deal with data in an effective, fast, agile and secure manner

• What it offers?• Optimal combination of edge nodes and cloud services

• Abstraction from data management

• Tools to enable developers easily create and deploy data-intensive applications

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DITAS Toolset

• DITAS SDK• simplifies the development of data-intensive applications,

hiding the complexity of the underlying infrastructure

• provides a homogeneous view of a set of resources that could belong to both cloud and fog platforms

• Virtual Data Container (VDC)• provides an abstraction layer for developers, so that they can

focus only on data, what they want to use and why, forgettingabout implementation details

• DITAS Execution Environment• based on a powerful execution engine, capable of managing a

distributed architecture and taking care of data andcomputation movement, maintaining coordination with otherresources involved in the same application

Example of Cloud deployed Application

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Virtual Data Container (VDC)

Data Processing

Data Access Layer

Exposed API (CAF)

Data Source

Data-Intensive Application

VDC instance

Data Source

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Exposed API (CAF)

• The application knows only the Common AccessibilityFramework (CAF) which hides the complexity behind theVDC

• The programming model is REST-oriented

• The data owner provides the API that contains a set ofwell-described methods, in order to make available someof the data included in the data sources, to which the VDCis connected

• This API is specified in the abstract VDC Blueprint and isbased on the OpenAPI Specification, originally known asthe Swagger Specification

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Data Processing (1/4)

• Principles • VDC embeds a set of data processing techniques able to transform data

• (e.g., encryption, compression)

• VDC allows to compose these processing techniques in pipelines

• Node-RED programming model

• Adopted Approach• From one monolithic application architecture, to microservices

architecture

• Each microservice can be described as a module that:

• assists a specific business goal

• uses simple language with a well-defined API to communicate with other (micro)services

• An application is being converted to a collection of microservices

• Serverless or Function as a Service (FaaS) architectures

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Data Processing (2/4)

Similar Approach; Amazon Web Services (AWS) Step Functions

• Description; “web service that enables you to coordinate the components of distributed applications and microservices using

visual workflows”

• Goal; focus only on the business logic and not to waste time on coding, testing or debugging

• Benefits;

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Data Processing (3/4)

Therefore Node-RED comes into the equation to:• visualize the VDC structure as a flow that consists of

separated tasks which are distinctive and follow a certain logical sequence

• “breaks” a task into a logical flow of steps-nodes with specific functions

• offers an abstract layer for building a solution

• provides a very modular way for implementing this solution

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Data Processing (4/4)

Node-RED Implementation Details• Each task could be implemented via one or more flows

• Alternative paths

• Each flow could consist of one or more nodes such as:

• REST calls to components implemented as a service

• JavaScript snippets (function nodes) to perform data filtering, refinement, transformation etc.

• control nodes (e.g. switch) that direct the flow to different paths

• Each component should be exposed as a web service and be available through a RESTful API

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Abstract VDC Blueprint (1/2)• The VDC descriptor, written in JSON format

• Captures all the properties of the VDC

• Consists of 5 distinct sections

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Abstract VDC Blueprint (2/2)Internal Structure (section 1)

High-level textual description of the VDC to characterize it as a product, focusing on business characteristics

Data Management (section 2)

Specifies the attributes of the methods offered by the VDC and, for each method, the guaranteed levels of data quality, security and privacy

Abstract Properties (section 3)

Contains all the rules in the form of goal trees to construct the Service Level Agreement (SLA) contract between the data owner and the data consumer

Cookbook Appendix (section 4)

Describes the deployment information for a VDC

Exposed API (section 5)

Technical section to enable the application developer to fully understand how the VDC exposed methods work

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E-Health DITAS Use Case – Exposed API (CAF)

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E-Health DITAS Use Case – Data Processing (Node-RED Flow)