Network, Volume 2, Issue 2 (June 2022) – 9 articles

App development is a steadily growing industry. Progressive web apps (PWAs) constitute a technology inspired by native and hybrid apps; they use web technologies to create web and mobile apps. Based on a service worker, a caching mechanism, and an app shell, PWAs aim to offer web apps with features and user interfaces similar to those of native apps. Furthermore, technological development has created a greater need for accessibility. An increasing number of websites, even government ones, are overlooking the need for equal access to new technologies among people with disabilities. This article presents, in a systematic review format, both PWAs and web accessibility and aims to evaluate PWAs’ effectiveness as regards the corresponding accessibility provided. Full article

Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date very challenging. Although advanced iterative algorithms have been developed to address this challenge, they exhibit slow convergence speed and thus deliver high latency and computational complexity. To overcome this challenge, we propose a computationally efficient conjugate gradient-descent (CGD) algorithm based on the Riemannian manifold in order to optimize the DL training sequence at base station (BS), while improving the convergence rate to provide a fast CSI estimation for an FDD m-MIMO system. To this end, the sum rate and the computational complexity performances of the proposed training solution are compared with the state-of-the-art iterative algorithms. The results show that the proposed training solution maximizes the achievable sum rate performance, while delivering a lower overall computational complexity owing to a faster convergence rate in comparison to the state-of-the-art iterative algorithms. Full article

Smart logistics, combining the capabilities of logistics with methods and techniques of the Internet of Things, Information and Communication Technologies, and the highest levels of automation are key to addressing the challenges of the 21st century and minimizing emissions while maximizing logistic performance. High-performance cellular networks are a prerequisite to fully using and leveraging their possibilities. These communication networks were developed based on the need for voice communication and streaming services. While the upcoming requirements are included in the latest versions of cellular networks, the existing infrastructure requires significant improvements and will have to adapt significantly. This study evaluates the performance of the current state of implementation of cellular networks on the German highway experimentally and analytically. The known indicators RSRP, RSSI, and RSRQ are analyzed spatially, over time, and for different driving conditions. The results indicate a high level of spatial correlation and a sufficient level of confidence, which are needed to ensure consistency and repeatability of these measurements. The procedure and the results can be used to assess the suitability of cellular networks for smart logistics applications and continuously monitor their improvement. The results indicate the status of the cellular network on the German highway which is worse compared to the network operator’s self-assessment. Full article

Distributed massive multiple-input multiple-output (D-mMIMO) is one of the key candidate technologies for future wireless networks. A D-mMIMO system has multiple, geographically distributed, access points (APs) jointly serving its users. First of all, this paper reports on where to position these APs to minimize the overall transmit power in actual deployments. As a second contribution, we show that it is essential to take into account both the radiation pattern of the antenna array and the environment information when optimizing AP placement. Neglecting the radiation pattern and environment information, as generally assumed in the literature, can lead to a power penalty in the order of 15 $\mathrm{d}$$\mathrm{B}$ and 20 $\mathrm{d}$$\mathrm{B}$, respectively. These results have been obtained by formulating the AP placement optimization problem as a combinatorial optimization problem, which can be solved with different approaches where different channel models are applied. The proposed graph-based channel model drastically lowers the computational time with respect to using an ray-tracing simulator (RTS) for channel evaluation. The performance of the graph-based approach is validated via the RTS, showing that it achieves 5 $\mathrm{d}$$\mathrm{B}$ power saving on average compared with a Euclidean distance-based approach, which is the most commonly used approach in the literature. Full article

Free-space optics (FSO) communication enjoys desirable modulation rates at unexploited frequency bands, however, its application is hindered by atmospheric turbulence which causes phase shifting in laser links. Although a single deformable mirror (DM) adaptive optics (AO) system is a good solution, its performance remains unsatisfactory as the proportion of tilts aberrations becomes relatively high. This condition happens when the incident angle of the laser beam for the optical receiver dynamically shifts. To tackle this problem, we introduce a fast steering mirror (FSM), DM cascaded AO architecture, based upon which we also propose an atmospheric turbulence compensation algorithm. In this paper, we compare the compensation ability of FSM and DM towards tilts aberrations. Furthermore, we gain model matrices for FSM and DM from testbed and simulatively verify the effectiveness of our work. For a Kolmogorov theory-based atmospheric turbulence disturbed incident laser beam where the tilt components take up $80\%$ of the total proportion of wavefront aberrations, our proposed architecture compensates the input wavefront to a residual wavefront root mean square (RMS) of $\frac{1}{16}$ wavelength, compared to $\frac{1}{6}$ wavelength for single DM architecture. The study intends to overcome atmospheric turbulence and has the potential to guide the development of future FSO communications. Full article

In this paper, cooperative simultaneous wireless information and power transfer (SWIPT) terahertz (THz) multiple-input multiple-output (MIMO) nonorthogonal multiple access (NOMA) are considered. The aim is to improve wireless connectivity, resource management, scalability, and user fairness, as well as to enhance the overall performance of wireless communications and reliability. We optimized the current wireless communication systems by utilizing MIMO-NOMA technology and THz frequencies, exploring the performance and gains obtained. Hence, we developed a path-selection mechanism for the far user to enhance the system performance. The EH SWIPT approach used to improve THz communications performance was investigated. Moreover, we proposed a reliable transmission mechanism with a non-LoS (NLoS) line of THz communications for open areas or any location where the intelligent reflecting surface (IRS) cannot be deployed, in addition to using the cheap decode-forward (DF) relaying instead of IRS. The performance and scalability of the upgradeable system were examined, using adjustable parameters and the simplest modulation scheme. The system presents a noticeable improvement in energy efficiency (EE) and spectral efficiency (SE), in addition to reliability. Accordingly, the outcome showed an improvement in the overall reliability, SE, EE, and outage probability as compared to the conventional cooperative networks of the recent related work (e.g., cooperative MIMO-NOMA with THz) by multiple times with a simpler design, whereas it outperformed our previous work, i.e., cooperative SWIPT SISO-NOMA with THz, by more than 50%, with a doubled individual user gain. This system reduces the transceiver hardware and improves reliability with increasing transmission rates. Full article

There are significant data privacy implications associated with Electronic Health Records (EHRs) sharing among various untrusted healthcare entities. Recently, a blockchain-based EHRs sharing system has provided many benefits. Decentralization, anonymity, unforgeability, and verifiability are all unique properties of blockchain technology. In this paper, we propose a secure, blockchain-based EHR sharing system. After receiving the data owner’s authorization, the data requester can use the data provider’s keyword search to discover relevant EHRs on the EHR consortium blockchain and obtain the re-encryption ciphertext from the proxy server. To attain privacy, access control and data security, the proposed technique uses asymmetric searchable encryption and conditional proxy re-encryption. Likewise, proof of permission serves in consortium blockchains as the consensus method to ensure the system’s availability. The proposed protocol can achieve the specified security goals, according to the security analysis. In addition, we simulate basic cryptography and put the developed protocol into practice on the Ethereum platform. The analysis results suggest that the developed protocol is computationally efficient. Full article

Finding an available parking place has been considered a challenge for drivers in large-size smart cities. In a smart parking application, Artificial Intelligence of Things (AIoT) can help drivers to save searching time and automotive fuel by predicting short-term parking place availability. However, performance of various Machine Learning and Neural Network-based (MLNN) algorithms for predicting parking segment availability can be different. To find the most suitable MLNN algorithm for the above mentioned application, this paper evaluates performance of a set of well-known MLNN algorithms as well as different combinations of them (i.e., known as Ensemble Learning or Voting Classifier) based on a real parking datasets. The datasets contain around five millions records of the measured parking availability in San Francisco. For evaluation, in addition to the cross validation scores, we consider resource requirements, simplicity and execution time (i.e., including both training and testing times) of algorithms. Results show that while some ensemble learning algorithms provide the best performance in aspect of validation score, they consume a noticeable amount of computing and time resources. On the other hand, a simple Decision Tree (DT) algorithm provides a much faster execution time than ensemble learning algorithms, while its performance is still acceptable (e.g., DT’s accuracy is less than 1% lower than the best ensemble algorithm). We finally propose and simulate a recommendation system using the DT algorithm. We have found that around 77% of drivers can not find a free spot in their selected destinations (i.e., street or segment) and estimated that the recommendation system, by introducing alternative closest vacant locations to destinations, can save, in total, 3500 min drivers searching time for 1000 parking spot requests. It can also help to reduce the traffic and save a noticeable amount of automotive fuel. Full article

Multi-access edge computing (MEC) is one of the emerging key technologies in fifth generation (5G) mobile networks, providing reduced end-to-end latency for applications and reduced load in the transport network. This paper proposes mechanisms to enhance user privacy in MEC within 5G. We consider a basic MEC usage scenario, where the user accesses an application hosted in the MEC platform via the radio access network of the mobile network operator (MNO). First, we create a system model based on this scenario. Second, we define the adversary model and give the list of privacy requirements for this system model. We also analyze the impact on user privacy when some of the parties in our model share information that is not strictly needed for providing the service. Third, we introduce a privacy-aware access protocol for the system model and analyze this protocol against the privacy requirements. Full article