Industry 4.0 aims to dramatically enhance the productivity of manufacturing technologies through the collection and analysis of real-time data. This combines the ubiquity of the IoT with the processing capabilities of cloud computing to generate insights that help to optimize the decision making process. The increasing demand of data and the explosion in the number of sensing devices, which might be highly constrained in terms of communication, battery and computational power, introduce new challenges that need efficient IoT-Cloud architectures. With this in mind, we extend MQTT, the de facto IoT communication protocol, using a fog computing approach that introduces a low complexity computational layer between the Cloud and IoT nodes. In this approach, the MQTT broker, which is in charge of relaying data from publishers to subscribers, is placed at the fog layer. The purpose of introducing an intermediate layer to this particular scenario is to: i) predict future data measurements through prediction techniques; ii) operate as a gateway to upper layers; and iii) provide the capability to offload computationally expensive data processing jobs from the Cloud to the Fog, minimizing additional latency and operational expenses. With this architecture, the transmissions required from IoT devices may be reduced, since the publishers would only need to update the predicted data in case of mismatching. We validate our approach with an energy consumption analysis and simulations of different Machine Learning algorithms on a real dataset, and compare it with the traditional MQTT scheme.

The introduction of the Internet of Things (IoT) is creating manifold new services and opportunities. This new technological trend enables the connection of a massive number of devices among them and with the Internet. The integration of IoT with cloud platforms also provides large storage and computing capabilities, enabling Big Data analytics and bidirectional communication between devices and users. Novel research directions are showing that Network Coding (NC) can increase the robustness and throughput of wireless networks, as well as that Homomorphic Encryption (HE) can be used to perform computations in the cloud while maintaining data privacy. In this paper, we overview the benefits of NC and HE along the entire vertical of cloud-based IoT architectures. By merging both technologies, the architecture may offer manifold advantages: First, it provides end-to-end data privacy, from end-devices to end-users. Second, sensitive data can be stored in public cloud platforms without concern about their privacy. In addition, clouds can perform advanced operations in a confidential manner, without the need to access actual data. Finally, latency can be reduced and the reliability of the system is increased. We show state-of-the-art works that demonstrate the role of both technologies in this type of architectures on a review basis. Furthermore, we describe the main characteristics of NC and HE and also discuss their benefits and limitations, as well as the emerging open challenges.

The next industrial revolution, generally referred to as Industry 4.0, is already here. This envisions a rapid transformation in the design, operation and service of manufacturing systems, where machines, sensors and actuators are interconnected in the factories in order to enable spontaneous collaboration, monitoring and control. Currently, Cyber-Physical-Systems (CPS) use regular Internet protocols (e.g. SOAP or HTTP) to communicate with each other. However, these protocols inherently present certain drawbacks or disadvantages: large footprint, CPU usage, high memory and energy consumption, etc. In recent years, new Industrial Internet of Things (IIoT) protocols have emerged to solve this issue, such as the Constrained Application Protocol (CoAP) and MQ Telemetry Transport (MQTT). These are lightweight protocols designed to face the challenges of industrial environments with a small footprint and overhead. These protocols have different features in terms of communication model and Quality of Service (QoS), that make them more suitable to an specific domain. Thus, it is important to identify the right metrics to adopt the most appropriate. This paper presents a theoretical and empirical comparison of MQTT and CoAP in terms of network overhead and latency, to assist system designers with this decision. Furthermore we describe the quantitative comparison conducted with their implementation in hardware platforms with high constraints. The achieved results provide useful metrics and guidelines to help designers to choose the appropriate schemes for their implementations.

Low-Power Wide-Area Networks (LPWANs) are becoming one of the main building blocks for the Industrial IoT (IIoT) ecosystem, being an alternative to 2G/3G/4G cellular networks where long-range communication at very low speed is needed by battery powered sensors spread around the factory. Among the most promising approaches, SIGFOX stands out as an ultra-narrow band technology that allows similar signal coverage to that of cellular networks at one thousandth of its power requirements. In this paper, we analyze a SIGFOX-based heterogeneous network architecture, based on combining an ultra-low-power star network topology for short distance communications and SIGFOX as Internet Gateway for the low-power devices. By following this approach, clusters of IIoT devices are able to communicate with a nearby SIGFOX Gateway that reports the sensed data to the Internet. Extensive experimentation and energy modeling has been performed. In particular, it is found that an IoT sensor is able to autonomously operate during remarkably long periods of time, reaching up to 4 years when operating at a duty cycle of 60 minutes and powered by a 1 Ah battery.

Electrical substations are crucial elements of Smart Grids where they are mainly responsible for voltage transformations. However, due to the integration of distributed energy resources in the grid, substations now have to provide additional grid management capabilities which in turn require supervision and automation solutions for large low-voltage grids. A recurring challenge in such deployments are siloed systems that are due to non-interoperable communication protocols across substations: although most substations’ communication is based on the International Electrotechnical Commission (IEC) 61850 standard, deployed legacy protocols lag behind modern communication technologies in terms of performance, hindering the full transition to lightweight protocols. This paper demonstrates that IEC 61850 can be fully mapped to the Constrained Application Protocol (CoAP) in combination with the Concise Binary Object Representation (CBOR) format while improving system performance compared to existing alternatives (e.g. WS-SOAP and HTTP). On average, CoAP+CBOR needs 44% and 18% of the message size and 71% and 85% of the time compared to systems based on HTTP and WS-* Web Services, respectively – this is especially relevant for resource-constrained devices and networks in electrical grids. In addition, CoAP is based on the Representational State Transfer (REST) architectural style, which supports system integration and interoperability through uniform identification and interaction. This approach fosters the standard-compliant integration of legacy platforms with modern substations as well as current IoT systems in neighboring domains such as building management and infrastructure automation systems.

In this paper we analyze the performance of QUIC as a transport alternative for Internet of Things (IoT) services based on the Message Queuing Telemetry Protocol (MQTT). QUIC is a novel protocol promoted by Google, and was originally conceived to tackle the limitations of the traditional Transmission Control Protocol (TCP), specifically aiming at the reduction of the latency caused by connection establishment. QUIC use in IoT environments is not widespread, and it is therefore interesting to characterize its performance when in over such scenarios. We used an emulation-based platform, where we integrated QUIC and MQTT (using GO-based implementations) and compared their combined performance with the that exhibited by the traditional TCP/TLS approach. We used Linux containers as end devices, and the ns-3 simulator to emulate different network technologies, such as WiFi, cellular, and satellite, and varying conditions. The results evince that QUIC is indeed an appropriate protocol to guarantee robust, secure, and low latency communications over IoT scenarios.