R
Rehmat Ullah
Researcher at Queen's University Belfast
Publications - 55
Citations - 654
Rehmat Ullah is an academic researcher from Queen's University Belfast. The author has contributed to research in topics: Computer science & Biology. The author has an hindex of 9, co-authored 30 publications receiving 311 citations. Previous affiliations of Rehmat Ullah include COMSATS Institute of Information Technology & Hongik University.
Papers
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Energy and Congestion-Aware Routing Metric for Smart Grid AMI Networks in Smart City
TL;DR: An energy- and congestion-aware routing metric for smart meter networks to be deployed in smart cities is proposed that considers the residual energy and queue utilization of neighboring nodes and will enhance network lifetime.
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An Experimental Analysis of Attack Classification Using Machine Learning in IoT Networks.
Andrew Churcher,Rehmat Ullah,Jawad Ahmad,Sadaqat Ur Rehman,Fawad Masood,Mandar Gogate,Fehaid Alqahtani,Boubakr Nour,William J Buchanan +8 more
TL;DR: In this paper, the authors compared several machine learning (ML) methods such as k-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), naive Bayes (NB), random forest (RF), artificial neural network (ANN), and logistic regression (LR) for both binary and multi-class classification on Bot-IoT dataset.
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Information-Centric Networking With Edge Computing for IoT: Research Challenges and Future Directions
TL;DR: The Edge computing and ICN provide an opportunity to reduce latency, support mobility, security, and scalability, and potential directions for future research in the field of ICN over Edge computing are described.
Journal ArticleDOI
SEDG: Scalable and Efficient Data Gathering Routing Protocol for Underwater WSNs
Naveed Ilyas,Mariam Akbar,Rehmat Ullah,Muhammad Khalid,Arsalan Arif,Abdul Hafeez,Umar Qasim,Zahoor Ali Khan,Nadeem Javaid +8 more
TL;DR: A novel scalable data gathering scheme called Scalable and Efficient Data Gathering SEDG routing protocol is presented, that increases the packet delivery ratio as well as conserves limited energy by optimal assignment of member nodes with GN.
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ICN with edge for 5G: Exploiting in-network caching in ICN-based edge computing for 5G networks
TL;DR: An ICN-capable RAN architecture for 5G edge computing environments that offers device to device communication and ICN application layer support at base stations is proposed and a content prefetching strategy based on ICN naming is provided.