Application of Wireless Sensor and Actuator Networks to Achieve Intelligent Microgrids: A Promising Approach towards a Global Smart Grid Deployment

Smart Grids (SGs) constitute the evolution of the traditional electrical grid towards a new paradigm, which should increase the reliability, the security and, at the same time, reduce the costs of energy generation, distribution and consumption. Electrical microgrids (MGs) can be considered the first stage of this evolution of the grid, because of the intelligent management techniques that must be applied to assure their correct operation. To accomplish this task, sensors and actuators will be necessary, along with wireless communication technologies to transmit the measured data and the command messages. Wireless Sensor and Actuator Networks (WSANs) are therefore a promising solution to achieve an intelligent management of MGs and, by extension, the SG. In this frame, this paper surveys several aspects concerning the application of WSANs to manage MGs and the electrical grid, as well as the communication protocols that could be applied. The main concerns regarding the SG deployment are also presented, including future scenarios where the interoperability of different generation technologies must be assured

A Case Study of Edge Computing Implementations: Multi-access Edge Computing, Fog Computing and Cloudlet

With the explosive growth of intelligent and mobile devices, the current centralized cloud computing paradigm is encountering difficult challenges. Since the primary requirements have shifted towards implementing real-time response and supporting context awareness and mobility, there is an urgent need to bring resources and functions of centralized clouds to the edge of networks, which has led to the emergence of the edge computing paradigm. Edge computing increases the responsibilities of network edges by hosting computation and services, therefore enhancing performances and improving quality of experience (QoE). Fog computing, multi-access edge computing (MEC), and cloudlet are three typical and promising implementations of edge computing. Fog computing aims to build a system that enables cloud-to-thing service connectivity and works in concert with clouds, MEC is seen as a key technology of the fifth generation (5G) system, and Cloudlet is a micro-data center deployed in close proximity. In terms of deployment scenarios, Fog computing focuses on the Internet of Things (IoT), MEC mainly provides mobile RAN application solutions for 5G systems, and cloudlet offloads computing power at the network edge. In this paper, we present a comprehensive case study on these three edge computing implementations, including their architectures, differences, and their respective application scenario in IoT, 5G wireless systems, and smart edge. We discuss the requirements, benefits, and mechanisms of typical co-deployment cases for each paradigm and identify challenges and future directions in edge computing

ChainSplitter: Towards Blockchain-based Industrial IoT Architecture for Supporting Hierarchical Storage

The fast developing Industrial Internet of Things (IIoT) technologies provide a promising opportunity to build large-scale systems to connect numerous heterogeneous devices into the Internet. Most existing IIoT infrastructures are based on a centralized architecture, which is easier for management but cannot effectively support immutable and verifiable services among multiple parties. Blockchain technology provides many desired features for large-scale IIoT infrastructures, such as decentralization, trustworthiness, trackability, and immutability. This paper presents a blockchain-based IIoT architecture to support immutable and verifiable services. However, when applying blockchain technology to the IIoT infrastructure, the required storage space posts a grant challenge to resource-constrained IIoT infrastructures. To address the storage issue, this paper proposes a hierarchical blockchain storage structure, \textit{ChainSplitter}. Specially, the proposed architecture features a hierarchical storage structure where the majority of the blockchain is stored in the clouds, while the most recent blocks are stored in the overlay network of the individual IIoT networks. The proposed architecture seamlessly binds local IIoT networks, the blockchain overlay network, and the cloud infrastructure together through two connectors, the \textit{blockchain connector} and the \textit{cloud connector}, to construct the hierarchical blockchain storage. The blockchain connector in the overlay network builds blocks in blockchain from data generated in IIoT networks, and the cloud connector resolves the blockchain synchronization issues between the overlay network and the clouds. We also provide a case study to show the efficiency of the proposed hierarchical blockchain storage in a practical Industrial IoT case

Error Minimization in Indoor Wireless Sensor Network Localization Using Genetic Technique

Using the genetic technique, error minimisation in indoor wireless sensor network localisation improves indoor wireless sensor network localisation during this field research. Sensor localisation-based techniques; several wireless device network applications require awareness of each node's physical location. The discovery of the position complete utilising range measurements also as sensor localisation received signal strength in time of arrival and sensor localisation received signal strength in a time difference of arrival and angle of arrival. WSN in positioning algorithms like the angle of arrival between two neighbour nodes. A wireless sensor network using positioning techniques in the area is assumed as localisation. WSNs always operate in an unattended manner, various situations like dynamic situations in the wireless network. It's impossible to exchange sensor manner after deployment. Therefore, a fundamental objective is to optimise the sensor manner lifetime. There has been much specialising in mobile sensor networks, and we have even seen the event of small-profile sensing devices that are ready to control their movement. Although it's been shown that mobility alleviates several issues regarding sensor network coverage and connectivity, many challenges remain node localisation in wireless device network is extremely important for several applications and received signal strength indicator has the capability of sensing, actuating the environmental data the actual-time and favourable information are often collected using the sensor in WSN systems. WSN is often combined with the internet of things to permit the association and extensive access to sensor data, and genetic techniques search the position of the nodes in WSN using all anchor nodes. A proposed algorithm as a genetic technique supported received signal strength, angle of arrival, receptive wireless device and also localisation wireless network. In the study, this paper problem that accuracy is low and error more, but the proposed algorithm overcomes this problem and minimises the error rate. Finally, the simplest possible location satisfies each factor with a minimal error rate and absolute best solution using GA

Pairing-based authentication protocol for V2G networks in smart grid

[EN] Vehicle to Grid (V2G) network is a very important component for Smart Grid (SG), as it offers new services that help the optimization of both supply and demand of energy in the SG network and provide mobile distributed capacity of battery storage for minimizing the dependency of non-renewable energy sources. However, the privacy and anonymity of users¿ identity, confidentiality of the transmitted data and location of the Electric Vehicle (EV) must be guaranteed. This article proposes a pairing-based authentication protocol that guarantees confidentiality of communications, protects the identities of EV users and prevents attackers from tracking the vehicle. Results from computing and communications performance analyses were better in comparison to other protocols, thus overcoming signaling congestion and reducing bandwidth consumption. The protocol protects EVs from various known attacks and its formal security analysis revealed it achieves the security goals.Roman, LFA.; Gondim, PRL.; Lloret, J. (2019). Pairing-based authentication protocol for V2G networks in smart grid. Ad Hoc Networks. 90:1-16. https://doi.org/10.1016/j.adhoc.2018.08.0151169

Secure data exchange in IIoT

Dupla diplomação com a National Polytechnic University of ArmeniaIndustrial Internet of Things (IIoT) plays a central role for the Fourth Industrial Revolution. In the scope of Industry 4.0 many specialists of the field are working together towards implementing large scalable, reliable and secure Industrial environments. However, existing environments are lacking security standards and have limited resources per component which results in various security britches such as trust in between the components, partner factories or remote control units with the system. Due to the resilience and it’s security properties, combining blochchain-based solutions with IIoT environments is gaining popularity. Despite that, chain-structured classic blockchain solutions are extremely resource-intensive and are not suitable for power-constrained IoT devices. To mitigate the security challenges presented above a secure architecture is proposed by using a DAG-structured asynchronous blockchain which can provide system security and transactions efficiency at the same time. Use-cases and sequence diagrams were created to model the solution and a security threat analysis of the architecture is made. Threat analysis is performed based on STRIDE methodology and provides us in depth understanding how our security architecture mitigates the threats and reveals also open challenges. The results are robust, supported by extensive security evaluation, which foster future development over the proposed architecture. Therefore, the contributions made are valid, and as the architecture is generic, will be possible to deploy it in diverse custom industrial environments. The flexibility of the architecture will allow incorporation of future hardware and software development in the field.A Internet das Coisas Industriais (IIoT) tem um papel central na quarta revolução industrial. Na área da Indústria 4.0 muitos especialistas colaboram com o objetivo de criar ambientes industriais escaláveis, confiáveis e seguros. No entanto, os cenários existentes carecem de normas de segurança, os recursos dos componentes são limitados, que levam a várias falhas de segurança que impedem a confiança entre dos diversos componentes, entre fábricas parceiras e entre unidades de controlo remoto de sistemas. Soluções suportadas por blockchain em ambientes IIoT estão a ganhar popularidade, principalmente devido à resiliência e propriedades de segurança da blockchain. No entanto, as soluções baseadas em blockchain clássicas estruturadas em cadeia fazem uso intensivo dos recursos, o que as torna não adequadas pra dispositivos IoT com restrição de energia. Para mitigar os desafios apresentados, propõe-se uma arquitetura segura que recorre a uma blockchain assíncrona com uma estrutura DAG, que procura fornecer segurança e eficiência nas transações. Casos de uso e diagramas sequência foram criados para modelar a solução e é realizada uma análise de ameaças de segurança à arquitetura. A análise recorre à metodologia STRIDE e fornece informação de como a nossa proposta mitiga as ameaças e revela também os desafios em aberto. Os resultados da avaliação demonstram que esta abordagem é robusta permitindo o desenvolvimento futuro da arquitetura proposta. As contribuições deste trabalho são validas, e como a arquitetura é genérica, será possível a implantar em diversas ambientes indústrias específicos. A flexibilidade da arquitetura permitirá a incorporar os futuros desenvolvimentos na área sejam hardware e/ou software

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected