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 microservices-based 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.
In @cite_6 , the authors propose a microservice-based reference architecture for the . In this architecture, there are six main components, which are Visualization (dashboard tools to interact with users), Calculation and Storage (provides aggregated information for Visualization layer), Data Transport and Integration (builds a common communication infrastructure for all services), Data Provider (feeds data to the system), Data Adapter (convert received data into readable formats) and Operation (contains services that ease operating and monitoring the application). This architecture is a basic design, as it is built to exploit most prominent advantages of microservice: high level of isolation between services, robust again complete system failure, and the support for the integration of heterogeneous systems. However, this architecture again does not address the scalability of a microservice-based application.
@cite_6
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Several recently proposed infrastructures permit client applications to interact with distributed network-accessible services by simply "plugging in" into a substrate that provides essential functionality, such as naming, discovery, and multi-protocol binding. However much work remains before the interaction can be considered truly seamless in the sense of adapting to the characteristics of the heterogeneous environments in which clients and services operate. This paper describes a novel approach for addressing this shortcoming: the partitionable services framework, which enables services to be flexibly assembled from multiple components, and facilitates transparent migration and replication of these components at locations closer to the client while still appearing as a single monolithic service. The framework consists of three pieces: (1) declarative specification of services in terms of constituent components; (2) run-time support for dynamic component deployment; and (3) planning policies, which steer the deployment to accomodate underlying environment characteristics. We demonstrate the salient features of the framework and highlight its usability and performance benefits with a case study involving a security-sensitive mail service. In this work we present a middleware architecture for a mobile peer-to-peer content distribution system. Our architecture allows wireless content dissemination between mobile nodes without relying on infrastructure support. Contents are exchanged opportunistically when nodes are within communication range. Applications access the service of our platform through a publish subscribe interface and therefore do not have to deal with low-level opportunistic networking issues or matching and soliciting of contents. Our architecture consists of three key components. A content structure that facilitates dividing contents into logical topics and allows for efficient matching of content lookups and downloading under sporadic node connectivity. A solicitation protocol that allows nodes to solicit content meta-information in order to discover contents available at a neighboring node and to download content entries disjointedly from different nodes. An API that allows applications to access the system services through a publish subscribe interface. In this work we describe the design and implementation of our architecture. We also discuss potential applications and present evaluation results from profiling of our system. Industrial Internet of things (IIoTs) relies on different devices working together, gathering and sharing data using multiple communication protocols. This heterogeneity becomes a hindrance in the development of architectures that can support applications operating independently of the underlying protocols. Therefore in this paper, we proposed a modular and scalable architecture based on lightweight virtualization. The modularity provided by the proposed architecture combined with lightweight virtualization orchestration supplied by Docker simplifies management and enables distributed deployments. Availability and fault-tolerance characteristics are ensured by distributing the application logic across different devices where a single microservice or even device failure can have no effect on system performance. The proposed architecture is instantiated and tested on a simple time-dependent use case. The obtained results validates that the proposed architecture can be used to deploy services on demand at different architecture layers. In this paper, experiences and best practices from using containerized software microservices for self-driving vehicles are shared. We applied the containerized software paradigm successfully to both the software development and deployment to turn our software architecture in the vehicles following the idea of microservices. Key enabling elements include onboarding of new developers, both researchers and students, traceable development and packaging, convenient and bare-bone deployment, and traceably archiving binary distributions of our quickly evolving software environment. In this paper, we share our experience from working one year with containerized development and deployment for our self-driving vehicles highlighting our reflections and application-specific shortcomings, our approach uses several components from the widely used Docker ecosystem, but the discussion in this paper generalizes these concepts. We conclude that the growingly complex automotive software systems in combination with their computational platforms should be rather understood as data centers on wheels to design both, (a) the software development and deployment processes, and (b) the software architecture in such a way to enable continuous integration, continuous deployment, and continuous experimentation.