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Split Learning-Based Robust Resource Allocation for Consumer Electronics in Smart Cities
IEEE Transactions on Consumer Electronics
Year: 2025 | Early Access Article |
In the smart city, high-density deployment of consumer electronics (CE) may lead to mutual interference, resulting in imperfect estimation of the channel state information (CSI). To tackle the problem, this paper proposes a split learning-based robust resource allocation for CEs in smart cities. We constructed an interference hypergraph model and divided resource allocation conflicts in overlappin...Show More
Impact of Modulation Schemes on Joint Estimation of Range and Velocity for UAV-to-Ground Scenarios
Xiaobo Yang;Daosen Zhai;Ruonan Zhang;Shengchen Wu;Yiyang Ni;Mubarak Alrashoud
ICC 2024 - IEEE International Conference on Communications
Year: 2024 | Conference Paper |
The emergence of new application scenarios has enabled integrated sensing and communication (ISAC) as one of the potential technologies of 6-th generation mobile communication (6G). To meet both communication efficiency and sensing efficiency, a satisfactory ISAC waveform is essential. In this paper, we primarily investigate the impact of different modulation schemes on sensing performance for UAV...Show More
Message Passing Assisted Scalable Distributed Link Management for Ubiquitous Network
Mengke Yang;Daosen Zhai;Haotong Cao;Bin Li;Mubarak Alrashoud
ICC 2024 - IEEE International Conference on Communications
Year: 2024 | Conference Paper |
The development of the next generation ubiquitous network puts forward higher requirements for the connection density in the communication network, e.g., massive IoT and UAV swarm, which has led to a lot of research on link management. With the expansion of network scale, the weaknesses of existing algorithms in computing efficiency, performance, and realizability have become prominent. The emergi...Show More
GCN-Based Multi-Agent Deep Reinforcement Learning for Dynamic Service Function Chain Deployment in IoT
Shuyi Wang;Haotong Cao;Longxiang Yang;Sahil Garg;Georges Kaddoum;Mubarak Alrashoud
The rapid development of technologies such as the Internet of Things, SDN/NFV, and 6G is driving up the demand for dynamic deployment of service function chains (SFC). These technologies are making network architectures more complex and service deployments more dynamic and adaptable. More than ever, there are situations that call for multi-objective SFC dynamic deployment, which necessitates resou...Show More
Lightweight Infrared and Visible Image Fusion Technique: Guided Gradient Optimization Driven
Yuhang Song;Ruijin Wang;Zengpeng Li;Sahil Garg;Georges Kaddoum;Mubarak Alrashoud
Infrared and visible image fusion technology aims to combine data from several spectral bands in order to increase target identification, processing capabilities, and image quality. With the rapid development of consumer electronic products for imaging, there is an urgent need for a lightweight and efficient fusion technology that ensures efficient information extraction and fusion while maintaini...Show More
Smart Contract-Based Access Control Scheme for Blockchain Assisted 6G-Enabled IoT-Based Big Data Driven Healthcare Cyber Physical Systems
Sourav Saha;Ashok Kumar Das;Mohammad Wazid;Youngho Park;Sahil Garg;Mubarak Alrashoud
6G (sixth-generation wireless), the successor to 5G cellular technology, operates at higher frequencies than its predecessor and supports significantly greater capacity and markedly reduced latency. Healthcare is treated as a complex system with various stakeholders, like doctors, patients, hospitals, pharmaceutical companies as well as healthcare decision-makers. The innovations in the Internet o...Show More
Softwarized Resource Allocation of Tailored Services with Zero Security Trust in 6G Networks
Haotong Cao;Longxiang Yang;Sahil Garg;Mubarak Alrashoud;Mohsen Guizani
IEEE Wireless Communications
Cited by: Papers (4)
Comparing with previous five generation networks consisting of dedicated appliance, 6G network appliances are designed to be softwarized and isolated into software (resource and function) blocks and general-purpose hardware. Tailored services, having customized resources and function demands, can be executed by chained software blocks and co-exist in the underlying 6G general-purpose hardware. How...Show More
Softwarized Resource Allocation in Digital Twins-Empowered Networks for Future Quantum-Enabled Consumer Applications
Haotong Cao;Sahil Garg;Shahid Mumtaz;Mubarak Alrashoud;Longxiang Yang;Georges Kaddoum
Network softwarization (NetSoft), recognized as crucial attribute of 6G networks, promises to provide enhanced and advanced services, including future quantum-enabled consumer applications. Softwarized resource allocation is the core issue in NetSoft concept. Digital twins (DT) guarantees to generate the corresponding digital world that reflects and interacts with the original physical world seaml...Show More
AI-Enabled Trajectory Optimization of Logistics UAVs With Wind Impacts in Smart Cities
Pengfei Du;Yueqiang Shi;Haotong Cao;Sahil Garg;Mubarak Alrashoud;Piyush Kumar Shukla
AI-enabled logistics unmanned aerial vehicles (UAVs) are progressively revealing their unique advantages for future smart cities. Nevertheless, the existing research on logistics UAV path planning lacks to simultaneously consider the UAV energy consumption constraints, the customer time windows, the impacts of wind speed and direction. This omission renders the existing models inappropriate for re...Show More
An Adaptive Rank-Based Tensor Ring Completion Model for Intelligent Transportation Systems
Low rank tensor ring based data recovery algorithms have been widely used in vehicle road cooperation intelligent transportation system to recover missing data entries in the sensing data pre-processing stage. However, the existing tensor ring decomposition based methods often resolve the low rank optimization with predefined ranks, which often leads over-fitting when the selected rank is large. T...Show More
Long-Term Energy Management Empowered Hierarchical Federated Learning for Smart Consumer Electronics
Managing for local data among the increasingly popular consumer smart electronics in a secure manner while increasing the user experience is still a hard work. Federated learning (FL), can develop intelligent electronics-related applications while protecting the privacy of local data. However, considering the traditional cloud-based FL training process, consumer electronics with a limited energy b...Show More
Federated Multimodal Learning for Privacy-Preserving Driver Break Recommendations in Consumer Electronics
Peng Liu;Longfei Jiang;Huaming Lin;Jia Hu;Sahil Garg;Mubarak Alrashoud
In recent years, driver distraction behaviors, such as eating, drinking, and making phone calls, have become more and more frequent, especially during continuous driving. This results in a significant increase in traffic accidents caused by those behaviors. Therefore, it is crucial to recommend driver breaks when frequent instances of driver distraction are detected. Despite numerous single modal-...Show More
Community Detection-Empowered Self-Adaptive Network Slicing in Multi-Tier Edge-Cloud System
Chenjing Tian;Haotong Cao;Jun Xie;Sahil Garg;Mubarak Alrashoud;Prayag Tiwari
Network slicing (NS) is a highly promising paradigm in 5G and forthcoming 6G communication networks. NS allows for the customization of multiple logically independent network slices to provide tailored service for vertical applications with diverse quality of service (QoS) requirements. However, current research on NS primarily relies on the traditional modeling methods such as service function ch...Show More
Efficient Resource Allocation of Slicing Services in Softwarized Space-Aerial-Ground Integrated Networks for Seamless and Open Access Services
Haotong Cao;Sahil Garg;Georges Kaddoum;Mubarak Alrashoud;Longxiang Yang
In current 6G study, space-aerial-ground integrated networks (SAGIN) are attracting the eye-catching attention. Traditional ground networks and facilities (e.g., open random access networks, Open-RAN) simply provide two-dimensional (2D) and limited-coverage services at low altitudes. SAGIN are designed to overcome these limitations and promise to provide 3D and seamless services and connectivity o...Show More
3-D Trajectory Optimization and Communication Resources Allocation in UAV-Assisted IoT Networks for Sustainable Industry 5.0
Pengfei Du;Yueqiang Shi;Haotong Cao;Sahil Garg;Georges Kaddoum;Mubarak Alrashoud
Unmanned aerial vehicle (UAV) has been utilized as an efficient data collector for Internet of Things (IoT) networks in sustainable industry 5.0. Whereas, how to sustain a stable power for the energy-constrained IoT devices (IoTDs) and to enhance the data gathering throughput of UAV-aided IoT networks via the wireless power transfer (WPT) or non-orthogonal multiple access (NOMA) is a twofold chall...Show More
Intelligent Beamforming for UAV-Assisted IIoT Based on Hypergraph Inspired Explainable Deep Learning
The development of industry is inseparable from the development of Industrial Internet of Things (IIoT), with the continuous development of artificial intelligence (AI), deep learning enabled intelligent communication has been widely studied. While, most existing neural networks for the current research often have poor performances on scalability and universality issues. In our previous work [1], ...Show More
AGRIC: Artificial-Intelligence-Based Green Routing for Industrial Cyber–Physical System Pertaining to Extreme Environment
Sandeep Verma;Satnam Kaur;Sahil Garg;Ajay K. Sharma;Mubarak Alrashoud
IEEE Internet of Things Journal
Cited by: Papers (7)
Industrial cyber–physical systems (ICPSs) can play a crucial role in damage assessment during extreme conditions by leveraging their integration of physical infrastructure, sensing capabilities, and advanced analytics. However, due to the wireless sensing devices that are made to operate in ICPS, there is a dire need to address the green routing (energy-efficient) challenges through an optimized s...Show More
Hypergraph-Based Resource-Efficient Collaborative Reinforcement Learning for B5G Massive IoT
Fan Yang;Cheng Yang;Jie Huang;Keping Yu;Sahil Garg;Mubarak Alrashoud
Beyond 5G (B5G) networks rapidly growing to connect billions of Internet of Things (IoT) devices and the dense deployment of IoT devices leads the large-scale network conflict and obstacles the resource-efficient, which brings a great challenge for network resource management (NRM). To tackle this problem, hypergraph based resource-efficient collaborative reinforcement learning (CRL) was proposed ...Show More
Uncertainty and Dependency-wise Requirements Prioritization
Norah Ibrahim Alfassam;M. Abdullah-Al-Wadud;Mubarak Rashed Alrashoud
2022 International Conference on Computational Science and Computational Intelligence (CSCI)
Year: 2022 | Conference Paper |
With the increase of complexity in software systems, optimizing the requirements management has become an important task in Software Engineering. The selection and prioritization of software requirements among plenty of requirements for each release of a software is a common problem. Several methods have been introduced to solve this common problem. Literature shows that the majority of existing r...Show More
Adaptive Fuzzy Neural Network vs. Convolution Neural Network in Classifying COVID-19 from Chest X-rays
2022 IEEE Globecom Workshops (GC Wkshps)
Year: 2022 | Conference Paper |
Detecting COVID-19 in the early time can save lives and reduce the cost of huge pressure on healthcare centers. Many machine and deep learning models have been proposed by researchers to detect and diagnose COVID-19 based on chest X-rays. However, we need to know which of those models is more effective and efficient. This paper presents a comparative study between adaptive fuzzy neural network (AF...Show More
Multimodal Educational Data Fusion for Students’ Mental Health Detection
Teng Guo;Wenhong Zhao;Mubarak Alrashoud;Amr Tolba;Selena Firmin;Feng Xia
Mental health issues can lead to serious consequences like depression, self-mutilation, and worse, especially for university students who are not physically and mentally mature. Not all students with poor mental health are aware of their situation and actively seek help. Proactive detection of mental problems is a critical step in addressing this issue. However, accurate detections are hard to ach...Show More
Deep Learning-Based Smart IoT Health System for Blindness Detection Using Retina Images
Amit Kumar Jaiswal;Prayag Tiwari;Sachin Kumar;Mabrook S. Al-Rakhami;Mubarak Alrashoud;Ahmed Ghoneim
Deep Learning-based Smart Healthcare is getting so much attention due to real-time applicability in everyone life's, and It has obtained more attention with the convergence of IoT. Diabetic eye disease is the primary cause of blindness between working aged peoples. The major populated Asian countries such as India and China presently account for millions of people and at the verge of an eruption o...Show More
Exploring the Use of Artificial Intelligence Techniques to Detect the Presence of Coronavirus Covid-19 Through Speech and Voice Analysis
Laura Verde;Giuseppe De Pietro;Ahmed Ghoneim;Mubarak Alrashoud;Khaled N. Al-Mutib;Giovanna Sannino
The Covid-19 pandemic represents one of the greatest global health emergencies of the last few decades with indelible consequences for all societies throughout the world. The cost in terms of human lives lost is devastating on account of the high contagiousness and mortality rate of the virus. Millions of people have been infected, frequently requiring continuous assistance and monitoring. Smart h...Show More
Blockchain-Empowered Trusted Networking for Unmanned Aerial Vehicles in the B5G Era
Xin Jian;Pengcheng Leng;Yanfeng Wang;Mubarak Alrashoud;M. Shamim Hossain
An unmanned aerial vehicle ad hoc network (UAANET) is an information sensing, analyzing, and transmitting network formed by multiple coordinated and collaborating UAVs. It is an emerging networking technology with a broad market prospect, but faces the problems of high dynamic topology and lack of trust. To address these issues, this article proposes a blockchain-em-powered trusted networking fram...Show More
ICN-Based Enhanced Cooperative Caching for Multimedia Streaming in Resource Constrained Vehicular Environment
Divya Gupta;Shalli Rani;Syed Hassan Ahmed;Sahil Garg;Md. Jalil Piran;Mubarak Alrashoud
Today, with the worldwide offer and rapid increment in multimedia applications on the web, the demands of users to get them accessed are also increasing prominently. The users in vehicular environment too expect efficient multimedia streaming while travelling on the road. However, the high mobility of vehicles as well as the limited transmission range of infrastructure components in IP based netwo...Show More
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