Designing a Smart City Internet of Things Platform with Microservice Architecture

The Internet of Things (IoT) is being adopted in different application domains and is recognized as one of the key enablers of the Smart City vision. Despite the standard-ization efforts and wide adoption of Web standards and cloud computing technologies, however, building large-scale Smart City IoT platforms in practice remains challenging. The dynamically changing IoT environment requires these systems to be able to scale and evolve over time adopting new technologies and requirements. In response to the similar challenges in building large-scale distributed applications and platforms on the Web, microservice architecture style has emerged and gained a lot of popularity in the industry in recent years. In this work, we share our early experience of applying the microservice architecture style to design a Smart City IoT platform. Our experience suggests significant benefits provided by this architectural style compared to the more generic Service-Oriented Architecture (SOA) approaches, as well as highlights some of the challenges it introduces

Exploring the effectiveness of service decomposition in fog computing architecture for the Internet of Things

The Internet of Things (IoT) aims to connect everyday physical objects to the internet. These objects will produce a significant amount of data. The traditional cloud computing architecture aims to process data in the cloud. As a result, a significant amount of data needs to be communicated to the cloud. This creates a number of challenges, such as high communication latency between the devices and the cloud, increased energy consumption of devices during frequent data upload to the cloud, high bandwidth consumption, while making the network busy by sending the data continuously, and less privacy because of less control on the transmitted data to the server. Fog computing has been proposed to counter these weaknesses. Fog computing aims to process data at the edge and substantially eliminate the necessity of sending data to the cloud. However, combining the Service Oriented Architecture (SOA) with the fog computing architecture is still an open challenge. In this paper, we propose to decompose services to create linked-microservices (LMS). Linked-microservices are services that run on multiple nodes but closely linked to their linked-partners. Linked-microservices allow distributing the computation across different computing nodes in the IoT architecture. Using four different types of architectures namely cloud, fog, hybrid and fog+cloud, we explore and demonstrate the effectiveness of service decomposition by applying four experiments to three different type of datasets. Evaluation of the four architectures shows that decomposing services into nodes reduce the data consumption over the network by 10% - 70%. Overall, these results indicate that the importance of decomposing services in the context of fog computing for enhancing the quality of service

Digital Twins: A Meta-Review on Their Conceptualization, Application, and Reference Architecture

The concept of digital twins (DTs) is receiving increasing attention in research and management practice. However, various facets around the concept are blurry, including conceptualization, application areas, and reference architectures for DTs. A review of preliminary results regarding the emerging research output on DTs is required to promote further research and implementation in organizations. To do so, this paper asks four research questions: (1) How is the concept of DTs defined? (2) Which application areas are relevant for the implementation of DTs? (3) How is a reference architecture for DTs conceptualized? and (4) Which directions are relevant for further research on DTs? With regard to research methods, we conduct a meta-review of 14 systematic literature reviews on DTs. The results yield important insights for the current state of conceptualization, application areas, reference architecture, and future research directions on DTs

DBL SmartCity: An Open-Source IoT Platform for Managing Large BIM and 3D Geo-Referenced Datasets

The `smart city\u27 approach has been promoted as an effective way to manage urban environments. Information and communication technology in general, as well as `Internet of Things\u27 systems in particular, constitute an essential component of all smart city initiatives. However, many past and current smart city implementations place only an insufficient emphasis on the geo-spatial and 3D nature of data. In order to fill this gap, we present DBL SmartCity, an open-source smart city IoT platform that is based on open standards and designed from the ground-up to effectively store, manage, and present large sets of BIM and 3D geo-referenced data

Integrated scalable system for smart energy management

The planet's reserves are encountering vital challenges and suffer inequitable consumption. The outcomes of the prostration of natural reserves have started affecting every single organism on the globe. Energy is a critical key factor in this aspect because a considerable part of the destruction is triggered by utilising the planet reserves to produce power in diverse forms. The increasing environmental awareness in humans' minds, and the rapid development of smart concepts, home automation technologies in both hardware and software fields, played an essential role in speeding up the progress to apply smart energy management which is needed to revert the situation to its appropriate track by focusing on two main divisions: firstly, producing clean and renewable energy and secondly, reducing the loss of the total generated energy. This research will concentrate on the second approach by proposing, implementing and evaluating a contemporary integrated, scalable, smart energy management framework that assists in reducing the energy consumption in the household sector, covering a range of single households till huge communities and big organisations with thousands of appliances. A number of correspondent strategies and policies which utilise a set of observed and predicted system entities are applied to keep meetings the most relevant quality attributes such as integrability, scalability, interoperability and availability. IoT concepts are applied in this context to connect conventional household appliances to a farm of microservices that implement predictive analytics techniques to reduce energy consumption by applying two main strategies; appliance substitution based on the energy consumption and creating automatic schedules to run appliances based on predictions. A case study is presented on two sample appliances within the household to illustrate the framework validity and deliver percentage figures of the saved energy. Additionally, the framework offers a number of possibilities to provide relevant third parties such as local energy providers, apparatuses' manufacturers, or pertinent government offices with various appliances’ operational behaviours under real-life conditions