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Khalid Mahmood Awan

Researcher at COMSATS Institute of Information Technology

Publications -  36
Citations -  748

Khalid Mahmood Awan is an academic researcher from COMSATS Institute of Information Technology. The author has contributed to research in topics: Routing protocol & Wireless sensor network. The author has an hindex of 11, co-authored 36 publications receiving 417 citations. Previous affiliations of Khalid Mahmood Awan include Universiti Teknologi Malaysia.

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Underwater Wireless Sensor Networks: A Review of Recent Issues and Challenges

TL;DR: A survey of UWSN regarding underwater communication channel, environmental factors, localization, media access control, routing protocols, and effect of packet size on communication is conducted.
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Machine learning-assisted signature and heuristic-based detection of malwares in Android devices

TL;DR: An efficient hybrid framework is presented for detection of malware in Android Apps that considers both signature and heuristic-based analysis for Android Apps, and results show improved accuracy in malware detection.
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A Data Augmentation-Based Framework to Handle Class Imbalance Problem for Alzheimer’s Stage Detection

TL;DR: A transfer learning-based technique using data augmentation for 3D Magnetic Resonance Imaging (MRI) views from OASIS dataset outperformed the existing techniques for Alzheimer disease stages.
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A Heterogeneous IoV Architecture for Data Forwarding in Vehicle to Infrastructure Communication

TL;DR: A heterogeneous network architecture incorporating multiple wireless interfaces installed on the on-board units to meet the requirements of pervasive connectivity for vehicular ad hoc networks to make them scalable and adaptable for IoV supporting a range of emergency services is proposed.
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A priority-based congestion-avoidance routing protocol using IoT-based heterogeneous medical sensors for energy efficiency in healthcare wireless body area networks:

TL;DR: This work proposes a multi-hop Priority-based Congestion-avoidance Routing Protocol using IoT based heterogeneous sensors for energy efficiency in wireless body area networks and uses the data aggregation and filtration technique to reduce the network traffic load and energy consumption.