In the last few years, Internet of Things, Cloud computing, Edge computing, and Fog computing have gained a lot of attention in both industry and academia. However, a clear and neat definition of these computing paradigms and their correlation is hard to find in the literature. This makes it difficult for researchers new to this area to get a concrete picture of these paradigms. This work tackles this deficiency, representing a helpful resource for those who will start next. First, we show the evolution of modern computing paradigms and related research interest. Then, we address each paradigm, neatly delineating its key points and its relation with the others. Thereafter, we extensively address Fog computing, remarking its outstanding role as the glue between IoT, Cloud, and Edge computing. In the end, we briefly present open challenges and future research directions for IoT, Cloud, Edge, and Fog computing.INDEX TERMS Fog computing, cloud computing, edge computing, Internet of Things, mobile cloud computing, mobile edge computing.

A key application of the Internet of Things (IoT) paradigm lies within industrial contexts. Indeed, the emerging Industrial Internet of Things (IIoT), commonly referred to as Industry 4.0, promises to revolutionize production and manufacturing through the use of large numbers of networked embedded sensing devices, and the combination of emerging computing technologies, such as Fog/Cloud Computing and Artificial Intelligence. The IIoT is characterized by an increased degree of inter-connectivity, which not only creates opportunities for the industries that adopt it, but also for cyber-criminals. Indeed, IoT security currently represents one of the major obstacles that prevent the widespread adoption of IIoT technology. Unsurprisingly, such concerns led to an exponential growth of published research over the last few years. To get an overview of the field, we deem it important to systematically survey the academic literature so far, and distill from it various security requirements as well as their popularity. This paper consists of two contributions: our primary contribution is a systematic review of the literature over the period 2011-2019 on IIoT Security, focusing in particular on the security requirements of the IIoT. Our secondary contribution is a reflection on how the relatively new paradigm of Fog computing can be leveraged to address these requirements, and thus improve the security of the IIoT.

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Electric drives are used to control electric motors, which are pervasive in industrial applications. In this paper we propose enhancing the electric drives to fulfil the role of fog nodes within a Fog Computing Platform (FCP). Fog Computing is envisioned as a realization of future distributed architectures in Industry 4.0. We identify the system-level requirements of such an FCP, including requirements that are extracted from the current architecture of drives, which we consider as a baseline. These requirements are then used to design a system-level architecture, which we model using the Architecture Analysis & Design Language (AADL). We identify the "technology bricks" (components such as hardware, software, middleware, services, methods and tools) needed to implement the FCP. The proposed fog-based architecture is then used to implement a Conveyor Belt industrial use case. We evaluate the resulting use case on several aspects, demonstrating the usefulness of the proposed fog-based approach. By developing the electric drives as fog nodes, that we call fogification, new offerings like programmability, analytics and connectivity to customer Clouds are expected to increase the added value. Increased flexibility allows drives to assume a larger role in industrial and domestic control systems, instrumenting thus also legacy systems by using drives as the data source.

The Transport Layer Security (TLS) 1.3 protocol supports a fast zero round-trip time (0-RTT) session resumption mechanism, enabling clients to send data in their first flight of messages. This protocol has been designed with Web infrastructure in mind, and requires these first messages to not change any state on the server side, as it is susceptible to replay attacks. This is disastrous for common IoT scenarios, where sensors often transmit state-changing data to servers. As bandwidth is a huge concern in the IoT, the field stands to benefit significantly from an efficient session resumption protocol that does not suffer from these limitations. Building on the observation that in IoT scenarios the set of clients is often bounded and fairly static, we propose rTLS (ratchet TLS), an efficient 0-RTT session resumption protocol that dramatically decreases bandwidth overhead, while adding forward secrecy and breakin resilience, and is not susceptible against replay attacks.