Year-end Sale % OFF 
Abstract
The impressive evolution of the Internet of Things and the great amount of data flowing through the systems provide us with an inspiring scenario for Big Data analytics and advantageous real-time context-aware predictions and smart decision-making. However, this requires a scalable system for constant streaming processing, also provided with the ability of decision-making and action taking based on the performed predictions. This paper aims at proposing a scalable architecture to provide real-time context-aware actions based on predictive streaming processing of data as an evolution of a previously provided event-driven service-oriented architecture which already permitted the context-aware detection and notification of relevant data. For this purpose, we have defined and implemented a microservice-based architecture which provides real-time context-aware actions based on predictive streaming processing of data. As a result, our architecture has been enhanced twofold: on the one hand, the architecture has been supplied with reliable predictions through the use of predictive analytics and complex event processing techniques, which permit the notification of relevant context-aware information ahead of time. On the other, it has been refactored towards a microservice architecture pattern, highly improving its maintenance and evolution. The architecture performance has been evaluated with an air quality case study.
Highlights
The impressive evolution of the Internet of Things (IoT) over the last years has strongly favored the provision of information by multiple sensors and other devices connected to the Internet; that, all the information flowing through the Internet is considered useful and relevant for multiple domains
Ortiz et al.: Real-Time Context-Aware Microservice Architecture for Predictive Analytics and Smart Decision-Making. Based on such a scenario, in the past we proposed CARED-SOA (Context-Aware Event-Driven ServiceOriented Architecture), a holistic architecture which permits dealing with context awareness in Service-Oriented Architecture (SOA), providing the means for context dealing from reception to delivery of personalized context-aware services [5], [6]
To illustrate how prediction is integrated into the architecture and evaluate the performance of the new micro-service architecture, we extended our air quality detection and warning case study to illustrate the novel CARED-SOA architecture, to predict the different levels of air quality for each pollutant and location and notify users of potential health risks based on their specific context
Summary
The impressive evolution of the Internet of Things (IoT) over the last years has strongly favored the provision of information by multiple sensors and other devices connected to the Internet; that, all the information flowing through the Internet is considered useful and relevant for multiple domains This way, the amount of generated data is huge. The associate editor coordinating the review of this manuscript and approving it for publication was Xiping Hu. scope is so huge, and it is generated so fast, that a constant streaming processing is required so as to obtain real-time relevant information to improve our business decision-making. Scope is so huge, and it is generated so fast, that a constant streaming processing is required so as to obtain real-time relevant information to improve our business decision-making Such an amount of useful information has fostered an interest in context-aware applications [3]. In the following paragraphs we summarize the key patterns for the architecture proposed in this paper
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
