MAIA: A Microservices-based Architecture for Industrial Data Analytics

Abstract

In recent decades, it has become a significant tendency for industrial manufacturers to adopt decentralization as a new manufacturing paradigm. This enables more efficient operations and facilitates the shift from mass to customized production. At the same time, advances in data analytics give more insights into the production lines, thus improving its overall productivity. The primary objective of this paper is to apply a decentralized architecture to address new challenges in industrial analytics. The main contributions of this work are therefore two-fold: (1) an assessment of the microservices' feasibility in industrial environments, and (2) a microservicesbased architecture for industrial data analytics. Also, a prototype has been developed, analyzed, and evaluated, to provide further practical insights. Initial evaluation results of this prototype underpin the adoption of microservices in industrial analytics with less than 20ms end-to-end processing latency for predicting movement paths for 100 autonomous robots on a commodity hardware server. However, it also identifies several drawbacks of the approach, which is, among others, the complexity in structure, leading to higher resource consumption.

A Survey on the Use of Lightweight Virtualization in I4.0 Manufacturing Environments

“…With the exception of Industrial Control, Scalability is exploited across all scopes of action. In particular, researchers have addressed the compelling need of handling the increasing amount of data produced in the factory by proposing scalable communication frameworks [3,15,56,59] and scalable data management facilities [18,66]. Finally, a handful of works have called upon microservices motivated by the fact that this paradigm enables agile approaches to the development, deployment and maintenance of software components [19,35,37,52].…”

“…It is no surprise that research communities push to deploy microservices in officefloor departments (which is historically a fertile ground for information technologies) to implement typical tasks of Production Control [10, 19, 35-37, 43, 52, 58, 65] or, more generally, Data Processing [2,18,30,63,66]. In here, according to researchers, the most appreciated quality of microservices is the strong support they provide to develop, maintain, update, deploy and scale industrial software solutions.…”

“…In [18], authors propose a decentralized software architecture that addresses new challenges in industrial analytics. They focus on a production environment where mobile autonomous robots capture videos with their on-board camera and off-loads object recognition tasks to fog-located servers found on their path.…”

Development Frameworks for Microservice-based Applications: Evaluation and Comparison

“…All four microservice frameworks focus on providing infrastructure services for microservice-based applications. In fact, the separation between infrastructure ser vices and functional services has been well discussed in the literature [17]. While infrastructure services provide essential capability such as service registry or service discovery, functional services are the ones that provide actual business logic.…”

MS2M: A message-based approach for live stateful microservices migration

“…This design allows developers to focus on the actual microservices' business logic rather than on implementing mechanisms for sending and receiving data. Among others, asynchronous messaging is widely implemented for microservices, as this communication scheme can ensure that no microservice has to wait for another service's response [24]. In this design pattern, all communication among services are encapsulated in messages, and they are handled asynchronously by a message broker, hence the name "asynchronous messaging".…”