Hossam S. Hassanein

Queen's University | QueensU · School of Computing

Welcome to a Special Issue of the IEEE Canadian Journal of Electrical and Computer Engineering (IEEE-CJECE), which presents articles in the research areas of the Journal’s Former Area Editor, Dr. Sameh Sourour, in his memorial. Sameh Sorour was with the School of Computing at Queen’s University, Kingston, ON, Canada, where he was leading research i...

Reinforcement Learning (RL) algorithms have recently been proposed to solve dynamic radio resource management (RRM) problems in beyond 5G networks. However, RL-based solutions are still not widely adopted in commercial cellular networks. One of the primary reasons for this is the slow convergence of RL agents when they are deployed in a live networ...

The number of individuals and groups of users offloading independent and inter-related computational tasks to mobile edge computing (MEC) servers is rapidly increasing, thus overloading them and raising the risk of service interruptions. Hence, reactive service replication has been suggested to enable individuals and groups of users to access servi...

Deep reinforcement learning (DRL) algorithms have recently gained wide attention in the wireless networks domain. They are considered promising approaches for solving dynamic radio resource management (RRM) problems in next-generation networks. Given their capabilities to build an approximate and continuously updated model of the wireless network e...

Extreme edge computing (EEC) refers to the endmost part of edge computing wherein computational tasks and edge services are deployed only on extreme edge devices (EEDs). EEDs are consumer or user-owned devices that offer computational resources, which may consist of wearable devices, personal mobile devices, drones, etc. Such devices are opportunis...

Social media traffic constitutes the highest percentage of Internet traffic. Such traffic is largely facilitated by mobile devices, which imposes a huge traffic load on backhaul links in 5G networks, and can in turn affect the quality of service. This traffic load can be alleviated by using vehicular networks as a traffic offloading platform. In pa...

p>The Internet of Vehicles over Vehicular Ad-hoc Networks is an emerging technology enabling the development of smart city applications focused on improving traffic safety, traffic efficiency, and the overall driving experience. These applications have stringent requirements detailed in Service Level Agreement. Since vehicles have limited computati...

Internet of Vehicles (IoV) over Vehicular Ad-hoc Networks (VANETS) is an emerging technology enabling the development of smart cities applications for safer, efficient, and pleasant travel. These applications have stringent requirements expressed in Service Level Agreements (SLAs). Considering vehicles limited computational and storage capabilities...

Deep reinforcement learning (DRL) algorithms have recently gained wide attention in the wireless networks domain. They are considered promising approaches for solving dynamic radio resource management (RRM) problems in next-generation networks. Given their capabilities to build an approximate and continuously updated model of the wireless network e...

The Internet of Vehicles over Vehicular Ad-hoc Networks is an emerging technology enabling the development of smart city applications focused on improving traffic safety, traffic efficiency, and the overall driving experience. These applications have stringent requirements detailed in Service Level Agreement. Since vehicles have limited computation...

Automatic Facial Emotion Recognition (FER) is currently in high demand, with many industries trying to incorporate emotion-aware technologies into their products. This process involves analyzing images of human faces and detecting features in order to determine which emotion they are displaying. This study investigates data augmentation techniques,...

Driver profiling is the real-time process of detecting driving behaviors and computing a driver’s expected risk based on detected behaviors. Predicting risk based solely on the inclusion of detected behaviors may not be accurate because this method of predicting ignores the environmental (e.g., weather conditions, traffic density level) context of...

It has been expected that space information networks (SINs), as an extension of terrestrial networks, would provide highspeed, high-capacity, global continuous communication, and data transmission services anywhere for anyone at any time. With the rapid advances in relevant technologies (e.g., satellite miniaturization technology, reusable rocket l...

Road accidents have a significant impact on increasing death rates. In addition to weather, roads, and vehicles, human error constitutes these accidents’ main reason. So, driver-safety technology is one of the common research areas, whether in academia or industry. The driver’s behavior is influenced by his feelings such as anger or sadness, as wel...

This paper exploits crowdsensing to propose a novel IoT-Based Vehicle Crowd Management (IoT-VCM) framework. By efficiently managing vehicle departures and navigation, the IoT-VCM clears the network in a shorter time, while maintaining the network at low congestion levels to reduce the average travel time. To compromise between these conflicting obj...

Recent studies into streaming media delivery suggest that performance gains from ubiquitous caching in Information-Centric Networks (ICN) may be negated by Dynamic Adaptive Streaming (DAS), the de facto method for retrieving multimedia content. Bitrate adaptation mechanisms, that drive video streaming, clash with caching mechanisms in ways that aff...

Mobile network traffic is increasing in an unprecedented manner, resulting in growing demand from network operators to deploy more base stations able to serve more devices while maintaining a satisfactory level of service quality. Base stations are considered the leading energy consumer in network infrastructure; consequently, increasing the number...

Driver behavior profiling has been gaining increased attention due to its relevance in many applications. For instance, car insurance telematics and fleet management entities have been recently using smartphones' embedded sensors, On-Board Diagnostics II (OBDII) units and other on-board IoT devices to collect data on vehicles' behavior and evaluate...

The importance of securing communications on the Internet of Things (IoT) cannot be overstated. This is especially the case in light of the increasing proliferation of IoT devices and instances, as well as the growing dependence on their usage. Meanwhile, there have recently been mounting concerns over a wide array of vulnerabilities in IoT communi...

This paper presents a Dynamic Access Control Framework for the Internet of Things (DACIoT). The main objective of DACIoT is to prevent unauthorized access to IoT devices and tightens the authorized access while an IoT device is in use. The rigidness of existing access control techniques in terms of manual policy specification, discontinuity of acce...

Machine learning (ML) and artificial intelligence (AI) have recently made a significant impact on improving the operations of wireless networks and establishing intelligence at the edge. In return, rare efforts were made to explore how adapting, optimizing, and arranging wireless networks can contribute to implementing ML/AI at the edge. This artic...

Abstract—In the era of the Internet of Things (IoT), it has become possible for a set of smart devices to collaborate autonomously and communicate seamlessly to achieve complex tasks that require a high degree of intelligence. Unlike traditional internet devices, a compromised IoT device can cause real-world damages. The severity of these damages i...

Mobile Crowd Sensing (MCS) is a paradigm that exploits the presence of a crowd of moving human participants to acquire, or generate, data from their environment. As part of the Internet of Things (IoT) paradigm, MCS serves the quest for more efficient operation of a smart city. Big data techniques employed on this data produce inferences about the...

The upsurge of smart devices has enabled the realization of safe, efficient smart cities that improve the quality of life of their citizens. A prevalent class of smart city services that are attracting increasing attention are Smart Emergency Response and Management (SERM) systems, where sensing paradigms such as crowd sensing and IoT-centric sensi...

Current route planning systems report to the driver routes based on expected travel time and distance. However, these systems do not provide individualized routing options. With the current routing systems lacking the provision of individualized routing choices, a routing framework which provides a personalized route option not solely based on time...

Next-generation Intelligent Transportation Systems (ITS) of future road traffic monitoring will be required to provide reports on traffic status, road conditions, and driver behaviour. Road surface anomalies contribute to increasing the risk of traffic accidents, reduced driver comfort and increased vehicles' damage. The conventional integrated Glo...

Personal Area Networks (PAN) are key topologies in pervasive Internet of Things (IoT) localization applications. In the numerous object localization techniques, centralization and synchronization between the elements are assumed. In this paper, we leverage crowdsourcing from multiple fixed and mobile elements to enhance object localization. A coope...

Information Centric Networking (ICN) is a developing paradigm, poised to transform the Internet's architecture. At its core, ICN focuses on efficient content dissemination and retrieval, regardless of storage location and physical representation of content. Thus, content caching schemes play a pivotal role in providing fast, reliable, and scalable...

Future smart cities are profoundly looking forward to providing services that assure daily competent functionality. Efficient traffic management and related vehicular services are crucial aspects when considering the city's decent operation. The significant presence of the vehicular and smartphone sensing and computing capabilities within and among...

Advancements and convergence in IoT enabling technologies along with ubiquitous connectivity have led to the generation of new wave of smart services and applications based on real-time data access. The popularity of ubiquitous data access and accelerated adoption of these services pose significant challenges on user and data privacy. Thus, control...

The Industrial Internet-of-Things (IIoT) has gained significant interest from both the research and industry com- munities. Such interest came with a vision towards enabling automation and intelligence for futuristic versions of our day to day devices. However, such a vision demands the need for accelerated research and development of IIoT systems,...

The IoT industry involves a wide diversity of sensing and control transducers, each using a different type of interfacing and operation technology. Such diversity creates a wide-range of challenges to large-scale IoT development and deployment. Despite the literature efforts to provide solutions for IoT trans- ducer interfacing, they still lack key...

The articles in this special section focus on crowd management in areas that are increasingly experiencing growths in populations. In its 2018 Revision of the World Urbanization Prospects, the United Nations projects that 68 percent of the world’s population is expected to be living in urban spaces by 2050, compared to the current 54 percent and 30...