A Scalable and Fault-Tolerant IoT Architecture for Smart City Environments

The Internet of Things (IoT) technology is becoming a promising computing infrastructure for the future developments of smart, connected environments. IoT has provided a digital world in which real-life objects are linked with other smart systems to facilitate rapid communication. This vision is spreading rapidly to various domains, ranging from smart homes to smart cities and industrial automation. One of the core aspects of IoT resides in the seamless connectivity and accessibility of heterogeneous devices over the network. Such an interaction is made possible by the adoption of much needed IoT protocols that offer open and standardized interfaces. A smart city is one of the examples in which devices, gateways, stakeholders, service providers, and computing platforms are fully connected to provide a ubiquitous environment. This communication involves the integration of two computing paradigms, namely edge and cloud, in order to achieve the full potential of IoT in smart cities. Their integration also demands fault tolerance, which might be possible with different software stacks on both the edge and cloud. However, it is more convenient to employ the same software stacks to ensure unified fault-tolerant management. Also, the large-scale data processing in smart cities has led to an increase in data volume, variety, and velocity. As a consequence, IoT-based systems need to process, manage, and store a large amount of real-time data on the edge, i.e., closer to the data sources, to minimize latency and save network bandwidth. This research investigates the scalability and fault tolerance of IoT applications in smart cities. The overall objective is to ensure that the smart city applications are resilient to failures and scale based on the increasing demands of users. The objective is pursued through three research questions, which identify some of the most significant challenges in smart cities: (i) How can IoT messaging standards enable real-time device-generated data processing and discovery? (ii) What is the role of edge computing in enabling scalable computation in dynamically changing environments? (iii) How can edge and cloud computing collectively provide fault tolerance capabilities? Each of the identified barriers is addressed through novel techniques presented in the research publications. Finally, the proposed solutions are validated by implementing them in various real-life case studies. The results indicate that, by adopting edge and cloud computing technologies, the proposed solutions are able to provide scalability, optimize network latency, and handle hardware- and network-based failures.