China
Africa
Explore chapters and articles related to this topic
Securing IoT-Based Microservices Using Artificial Intelligence
Published in Sandeep Saini, Kusum Lata, G.R. Sinha, VLSI and Hardware Implementations Using Modern Machine Learning Methods, 2021
Sushant Kumar, Saurabh Mukherjee
The implementation decision was mainly that each of the components can be executed on a variety of computers and with the least interdependence, for which we proceeded to work on a microservices architecture that allows their deployment either as independent processes, or within a containerization structure, such as Docker [30]. For desktop services and clients, Java was used with Spring Boot in general. For the central messaging service, it was decided to work using the MQTT protocol, and for the development of the broker, the Moquette library [31] was taken as a base, to which it was modified to add support for OAuth2 mainly. An HDFS cluster was used as a basis for persistence services [32]; time series services were built on the local network, which, according to the current interests of the project, were the most suitable for processing the data coming from the sensors.
Challenges in Designing Software Architectures for Web-Based Biomedical Signal Analysis
Published in Aboul Ella Hassanien, Nilanjan Dey, Surekha Borra, Medical Big Data and Internet of Medical Things, 2018
Alan Jovic, Kresimir Jozic, Davor Kukolja, Kresimir Friganovic, Mario Cifrek
However, supporting many users at the same time and performing complex analysis scenarios (as depicted in Figure 4.1) may require more resources for a general and expandable solution. A typical minimum solution would include a single computer, acting as a server for data analysis with fast multi-core processor capabilities (4 or more logical cores), as well as large hard drive and RAM capacities. The computer would need to have a web server installed to support the web application (e.g. Apache Tomcat), H2 or similar in-memory relational DBMS, and would need to provide software support for the whole web development technological stack in order to accommodate for potential software improvements. It would hence include (1) frontend technologies, such as HTML, CSS, Bootstrap, JavaScript/TypeScript, Angular or similar frontend development frameworks; and (2) backend technologies, such as Java 9, Spring Boot and JPA (or related backend Microsoft, PHP, or Python technologies). Additionally, permissive license libraries used to cover the various steps in biomedical signal analysis would be a welcome – but not a necessary – requirement for the construction of the web platform, as some of the required methods may be efficiently implemented from scratch.
Towards logistics 4.0: an edge-cloud software framework for big data analytics in logistics processes
Published in International Journal of Production Research, 2021
Moritz von Stietencron, Karl Hribernik, Katerina Lepenioti, Alexandros Bousdekis, Marco Lewandowski, Dimitris Apostolou, Gregoris Mentzas
The DECIDE component provides proactive recommendations about optimal actions and plans by receiving streams of predictions about future states, while it takes into account human feedback. It is capable of modelling the decision making process and handling multiple actions upon user configuration. Therefore, the required parameters are either derived from the data or they are configured by the user through the GUI. Such parameters include: list of actions, objectives to be optimised (e.g. costs of actions), etc. It is a Java-based web application that has been developed as a Maven project and uses the Spring Boot framework. The overall integration of Kafka with Spring is enabled by the Spring for Apache Kafka (spring-kafka) project.