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 standardization 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.

This paper presents an Internet-of-Things software infrastructure that enables energy management and simulation of new control policies in a city district. The proposed platform enables the interoperability and the correlation of (near-)real-time building energy profiles with environmental data from sensors as well as building and grid models. In a smart city context, this platform fulfills 1) the integration of heterogeneous data sources at the building and district level, and 2) the simulation of novel energy policies at the district level aimed at the optimization of the energy usage accounting also for its impact on building comfort. The platform has been deployed in a real-world district and a novel control policy for the heating distribution network has been developed and tested. Results are presented and discussed in the paper

Intenet of Things (IoT) applications often involve deployment of gateways at the network edge for integrating physical devices, pre-processing sensor data, and synchronizing it with the cloud. The deployment, configuration, and maintenance of the software running on the gateways in large-scale deployments is known to be challenging. In this work, we analyze the deployment requirements of IoT gateways and evaluate containerized deployment with linux containers as a potential approach addressing them. We perform several synthetic and application benchmarks providing an insight in the performance overhead introduced by linux containers and how they affect typical applications running on IoT gateways

Modern Information and Communication Technologies are definitely a key factor to develop the green and sustainable applications that the so-called 'smart city' needs. Effective management of resources, gathering and interpreting data as well as ecological considerations are prerequisites to turn such a vision into reality. The European FP7 project DIMMER address these issues by providing a flexible Internet of Thing platform for application development and data integration, exploiting information about buildings, energy distribution grids and user behaviors. Among those applications, the possibility to real-time access and aggregate information about building environmental characteristics and energy consumption enables the optimization of energy management and control, as well as the user's awareness about, which is the scope of the DIMMER project

This chapter presents a novel distributed software infrastructure to enable energy management and simulation of novel control strategies in smart cities. In this context, the following heterogeneous information, describing the different entities in a city, needs to be taken into account to form a unified district information model: internet-of-things (IoT) devices, building information model, system information model, and georeferenced information system. IoT devices are crucial to monitor in (near-) real-time both building energy trends and environmental data. Thus, the proposed solution fulfills the integration and interoperability of such data sources providing also a correlation among them. Such correlation is the key feature to unlock management and simulation of novel energy policies aimed at optimizing the energy usage accounting also for its impact on building comfort. The platform has been deployed in a real-world district and a novel control policy for the heating distribution network has been developed and tested. Finally, experimental results are presented and discussed.