Internet of things IoT is playing a remarkable role in the advancement of many fields such as healthcare, smart grids, supply chain management, etc. It also eases people’s daily lives and enhances their interaction with each other as well as with their surroundings and the environment in a broader scope. IoT performs this role utilizing devices and sensors of different shapes and sizes ranging from small embedded sensors and wearable devices all the way to automated systems. However, IoT networks are growing in size, complexity, and number of connected devices. As a result, many challenges and problems arise such as security, authenticity, reliability, and scalability. Based on that and taking into account the anticipated evolution of the IoT, it is extremely vital not only to maintain but to increase confidence in and reliance on IoT systems by tackling the aforementioned issues. The emergence of blockchain opened the door to solve some challenges related to IoT networks. Blockchain characteristics such as security, transparency, reliability, and traceability make it the perfect candidate to improve IoT systems, solve their problems, and support their future expansion. This paper demonstrates the major challenges facing IoT systems and blockchain’s proposed role in solving them. It also evaluates the position of current researches in the field of merging blockchain with IoT networks and the latest implementation stages. Additionally, it discusses the issues related to the IoT-blockchain integration itself. Finally, this research proposes an architectural design to integrate IoT with blockchain in two layers using dew and cloudlet computing. Our aim is to benefit from blockchain features and services to guarantee a decentralized data storage and processing and address security and anonymity challenges and achieve transparency and efficient authentication service.

Recently, electric vehicles (EVs) have been introduced as an alternative method of transportation to help mitigate environmental issues, such as carbon emissions and fuel consumption, caused by conventional transportation systems. The implementation of effective EV charging systems is essential to motivate mass adoption of EVs. Accordingly, fast and reliable communications between the charging systems and the EVs are vital for efficient management of the charging process. Different radio access technologies (RATs) are discussed in the literature to enable communication between the highly mobile EVs and the charging subsystems, to collect and exchange information such as state of charge (SoC), users’ locations, and charging decisions between the different network entities. This information can be used to coordinate charging plans and select the optimal routes for moving vehicles. This paper presents a survey of existing literature on vehicular communications for EV charging coordination and management. The communication requirements and feasible communication technologies for vehicular communication are first discussed in details. A review of the physical layer security strategies is then presented and the role of the different RATs in EV charging coordination and management is described and studied.

In this paper, we present novel exact closed-form expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the sum of an arbitrary number of independent and non-identically distributed (i.n.i.d.) Fox's H-function random variables (RVs), which has been recently used to model fading in wireless channels. The obtained expressions are given in terms of the multivariate Fox's H-function, which has multiple implementations already available in the literature. We verify the validity of the obtained expressions using Monte Carlo simulations. Moreover, the distribution of the sum of other RVs for which no exact expressions are available are derived as special cases. This includes the alpha-mu, the extended generalized-K (EGK) and the recently investigated Fisher-Snedecor F RVs. The obtained PDF and CDF expressions can be directly used for evaluating the performance in several wireless communications scenarios, for instance, when calculating the outage probability (OP), the symbol error rate (SER) or the ergodic capacity of the H-function fading channel (or its special cases) with diversity reception as shown in this work. We also present simple asymptotic expansions for such quantities that enjoy low computational burden.

The utilization of dynamic wireless charging (DWC) systems to charge on-the-move EVs is currently gaining an increasing popularity, as it addresses range and charging downtime issues of EV users. To ensure optimal utilization of this charging infrastructure, coordination of EV charging demand is essential to achieve grid load balancing and prevent grid overload. In contrast to offline, day-ahead charging scheduling, this work proposes an online, mobility-aware, spatial EV allocation algorithm within a DWC coordination strategy. This strategy allocates EVs requesting charge to the most optimal DWC lanes within an EV charging network (ECN) in an Internet of EVs (IoEVs). A detailed charging request scenario is presented to highlight the required communication for authentication between the EVs and the charging infrastructure, to achieve the desired coordination. Description of the proposed EV allocation algorithm is then presented and the performance of the algorithm is evaluated using a hypothetical case study of predicted EV traffic trips in the cities of Dubai and Sharjah, UAE. Upon parameter optimization, results of the conducted analysis reveal that the proposed EV allocation algorithm achieves an almost flattened load profile across the DWC lanes that reduces the PAER by more than 44% in comparison with a shortest distance allocation algorithm, for a maximum $2\times $ increase in trip length, and sufficient received energy to compensate for the energy consumed during the trip. This acknowledges grid supply limitations, EV traveling velocities and the maximum service capacity per DWC lane.

The growing penetration of electric vehicles (EVs) and the increasing EV energy demand pose several challenges to the power grid, the power distribution networks and the transportation networks. This growing demand drives the need for effective demand management and energy coordination strategies to maximize the demand covered by the EV charging stations, ensure EV users' satisfaction and prevent grid-side overload. As a result, several optimization problems are formulated and solved in the literature to provide optimal EV charging schedules (i.e. temporal coordination) as well as optimal EV-to-charging-station assignments and routing plans (i.e. spatial coordination). This paper presents a review of the state-of-the-art literature on the utilization of different deterministic optimization techniques to develop optimal EV charging coordination strategies. In particular, these works are reviewed according to their domains of operation (i.e. time-based scheduling, spatial coordination, and spatio-temporal charging coordination), their respective objectives (user-, grid- and operator-related objectives), and the solution algorithms adopted to provide the corresponding optimal coordination plans. This helps in identifying key research gaps and provide recommendations for future research directions to develop comprehensive and computationally efficient charging coordination models.

Dynamic wireless power transfer (DWPT) systems are becoming increasingly important for on-the-move electric vehicle (EV) charging solutions, to overcome range anxiety and compensate for the consumed energy while the EV is in motion. In this work, a DWPT EV charging system is proposed to be implemented on a straight road stretch such that it provides the moving EV with energy at a rate of 308 Wh/km. This rate is expected to compensate for the vehicle’s average energy consumption and allow for additional energy storage in the EV battery. The proposed charging system operates at an average power transfer efficiency that is higher than $90\%$ and provides good lateral misalignment tolerance up to $\pm 200$ mm. Details of the proposed system’s design are presented in this paper, including EV specifications, inductive link and compensation network design and power electronic circuitry.