Browsing by Author "Karim Djouani"

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A review of industrial wireless communications, challenges, and solutions: A cognitive radio approach
(Wiley, 2020-09-09) Oyewobi S. Stephen; Karim Djouani; Anish Matthew Kurien
Abstract Integral and crucial to performance of wireless sensor networks (WSNs), and specifically industrial wireless sensor network (IWSN) is stable, robust, reliable, and ubiquitous communications system. Though, wired communications system is suitable for industrial communications and is resilient to shadowing and multipath fading effects of industrial-WSN environments, yet its wireless counterpart is a much preferred industrial communications technology due to reduced cost and high flexibility which it offers in comparison to wired communications. However, overcrowding of the industrial, scientific, and medical band, where IWSN is deployed together with other heterogeneous technologies, as well as resultant scarcity of usable frequency spectrum has restrained exclusive application of wireless technology for industrial communications. Nonetheless, cognitive radio (CR) has ability to increase spectrum utilization efficiency and channel capacity for industrial wireless communications (IWC) through opportunistic/dynamic spectrum access (DSA) technique. In this review article, we examine how DSA can benefit IWC through exploitation of new perspectives of white space definitions in the licensed bands as well as unlicensed bands. While discussing the potential of DSA for IWC, we have considered the unique characteristics of IWC as well as technical challenges and issues imposed by industrial-WSN. Accordingly, we have suggested and proffered appropriate CR-based solutions in mitigating some of the challenges where necessary.
IoT in the Wake of COVID-19: A Survey on Contributions, Challenges and Evolution
(IEEEE Access, 2020) Musa Ndiaye; Oyewobi S. Stephen; Adnan M. Abu-Mahfouz; Gerhard Hancke; Anish M. Kurien; Karim Djouani
The novel coronavirus (COVID-19), declared by the World Health Organization (WHO) as a global pandemic, has brought with it changes to the general way of life. Major sectors of the world industry and economy have been affected and the Internet of Things (IoT) management and framework is no exception in this regard. This article provides an up to date survey on how a global pandemic such as COVID-19 has affected the world of IoT technologies. It looks at the contributions that IoT and associated sensor technologies have made towards virus tracing, tracking and spread mitigation. The associated challenges of deployment of sensor hardware in the face of a rapidly spreading pandemic have been looked into as part of this review article. The effects of a global pandemic on the evolution of IoT architectures and management have also been addressed, leading to the likely outcomes on future IoT implementations. In general, this article provides an insight into the advancement of sensor-based E-health towards the management of global pandemics. It also answers the question of how a global virus pandemic has shaped the future of IoT networks.
Performance of Path Loss Models over Mid-Band and High-Band Channels for 5G Communication Networks: A Review
(MDPI, 2023-11-07) Farooq E Shuaibu; Elizabeth N. Onwuka; Nathaniel Salawu; Oyewobi S. Stephen; Karim Djouani; Adnan M. Abu-Mahfouz
The rapid development of 5G communication networks has ushered in a new era of highspeed, low-latency wireless connectivity, as well as the enabling of transformative technologies. However, a crucial aspect of ensuring reliable communication is the accurate modeling of path loss, as it directly impacts signal coverage, interference, and overall network efficiency. This review paper critically assesses the performance of path loss models in mid-band and high-band frequencies and examines their effectiveness in addressing the challenges of 5G deployment. In this paper, we first present the summary of the background, highlighting the increasing demand for high-quality wireless connectivity and the unique characteristics of mid-band (1–6 GHz) and high-band (>6 GHz) frequencies in the 5G spectrum. The methodology comprehensively reviews some of the existing path loss models, considering both empirical and machine learning approaches. We analyze the strengths and weaknesses of these models, considering factors such as urban and suburban environments and indoor scenarios. The results highlight the significant advancements in path loss modeling for mid-band and high-band 5G channels. In terms of prediction accuracy and computing effectiveness, machine learning models performed better than empirical models in both mid-band and high-band frequency spectra. As a result, they might be suggested as an alternative yet promising approach to predicting path loss in these bands. We consider the results of this review to be promising, as they provide network operators and researchers with valuable insights into the state-of-the-art path loss models for mid-band and high-band 5G channels. Future work suggests tuning an ensemble machine learning model to enhance a stable empirical model with multiple parameters to develop a hybrid path loss model for the mid-band frequency spectrum.
Using priority queuing for congestion control in IoT-based technologies for IoT applications
(Wiley, 2020-11-24) Oyewobi S. Stephen; Karim Djouani; Anish Matthew Kurien
The Internet of Things (IoT) connect millions of devices in diverse areas such as smart cities, e-health, transportation and defense to meet a wide range of human needs. To provide these services, a large amount of data needs to be transmitted to the IoT network servers. However, the IoT networks suffer from limited resources such as buffer size, node processing capabilities, and server capacities adversely affecting throughputs, latency, and energy consumption. Additionally, the ensuing heavy network traffic due to large amount of data transmitted results in congestion which degrades IoT network performance. Therefore, innovative congestion control techniques, e.g., queue management approach needs to be developed to overcome congestion problems in IoT networks. In this paper, a novel priority queuing technique (Npqt++) is developed to control congestion in IoT networks. The Npqt++ implements a preemptive/nonpreemptive discipline with a discretion rule to classify network traffic based on their real-time requirement into priority groups. If the discretion rule for low priority packets is satisfied, high priority packets are pushed to the front of the queue; otherwise, they wait in the queue. Our approach significantly outperforms existing techniques in terms of throughput, delay, and energy consumption.
Visible Light Communications for Internet of Things: Prospects and Approaches, Challenges, Solutions and Future Directions
(MDPI, 2022-02-05) Oyewobi S. Stephen; Karim Djouani; Anish Matthew Kurien
Visible light communications (VLC) is an emerging and promising concept that is capable of solving the major challenges of 5G and Internet of Things (IoT) communication systems. Moreover, due to the usage of light-emitting diodes (LEDs) in almost every aspect of our daily life VLC is providing massive connectivity for various types of massive IoT communications ranging from machine-to-machine, vehicle-to-infrastructure, infrastructure-to-vehicle, chip-to-chip as well as device-to-device. In this paper, we undertake a comprehensive review of the prospects of implementing VLC for IoT. Moreover, we investigate existing and proposed approaches implemented in the application of VLC for IoT. Additionally, we look at the challenges faced in applying VLC for IoT and offer solutions where applicable. Then, we identify future research directions in the implementation of VLC for IoT.