Browsing by Author "Dr. Tahir Maqsood"

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Congestion Aware Bandwidth Optimization for Secure Healthcare Data Transmission Using Edge Computing
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Aiza Ijaz; CIIT/SP23-RCS-003/LHR; Dr. Tahir Maqsood; LHR TP 9700
The increasing dependence on telemedicine and remote patient monitoring between IoT wearable medical devices has revolutionized modern healthcare services. However, managing security, privacy and effective communication of huge amounts of sensitive healthcare data remains a critical challenge. Existing blockchain systems, still promising and guaranteeing data integrity and decentralized control, clash with scalability, transaction delays and network traffic, especially when processing real time medical IoT data. These limitations block the timely delivery of critical healthcare information, probably affecting patient outcomes. This thesis presents the development of a blockchain telehealth system combined with Software Defined Networking (SDN) to reduce these challenges. The proposed framework employed the Ethereum blockchain smart contract for secure, decentralized authorization and access control of healthcare data, integrated with edge computing for temporary off-ledger data storage to relieve blockchain scalability issues. Furthermore, SDN is employed to allocate bandwidth, ensuring low latency transmission of critical patient data, especially during emergencies. The primary objectives of this research involve guaranteeing the security and privacy of healthcare data. Using edge computing improves storage and transmission efficiency and optimizes bandwidth allocation using SDN techniques. The proposed system introduces a novel solution by integrating SDN and blockchain. Experimental results show that the framework visibly improves bandwidth utilization, reduces latency for emergencies and increases overall system efficiency compared to old blockchain approaches. This research bridged the gap between data security and transmission efficiency in healthcare IoT systems. Future work will focus on integrating AI driven routing algorithms and energy efficient IoT models to further optimize performance and support large scale healthcare deployments.
Secure and Reliable Medical Data Offloading in Mobile Edge Computing Leveraging Software Defined Networking and Blockchain
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Asmara Maryam; CIIT/SP23-RCS-009/LHR; Dr. Tahir Maqsood; LHR TP 9702
The volume of medical data is growing rapidly due to the increasing popularity of the Internet of Things and other sophisticated medical devices, making medical data processing more and more difficult. As healthcare systems become increasingly data- driven, the need for secure and real-time access to patient information has grown significantly particularly during emergencies and critical procedures. However, the limited processing capacity of traditional hospital infrastructure makes it challenging to manage and transmit the large volumes of data generated by IoT-based medical devices. In this work, we present a framework that securely and reliably offloads patient data using a combination of Software-Defined Networking (SDN), Blockchain, and Mobile Edge Computing (MEC) technologies. Using mobile edge computing, cloud computing processing capacity can be distributed and mapped closer to users at the network edge, allowing healthcare systems to offload data efficiently. The proposed system enables healthcare data to be offloaded to nearby edge nodes with minimal delay, while ensuring that only authorized individuals such as doctors with patient consent can access or modify the information. SDN intelligently selects the best network paths based on real-time bandwidth and latency, while smart contracts deployed on the Ethereum blockchain manage access control, consent verification, emergency overrides, and data logging. However, ensuring reliability of offloading is critical because failure to process medical data may have catastrophic effects. Similarly, ensuring privacy and security of medical data is another challenge that needs to be addressed. We developed a three-layer architecture involving IoT devices, edge nodes, and the blockchain, and implemented modular smart contracts for various healthcare tasks, including usage tracking and ML model validation. Performance was evaluated using NS-3 for SDN simulation and Remix IDE for smart contract testing. Results show that our approach improved reliability, achieving a 96.5% packet delivery ratio, a 99.8% data integrity (hash match) rate, and a 24% reduction in average latency compared to traditional models. This demonstrates the potential of SDN and blockchain in making healthcare data offloading both secure and efficient.
Tutor Finder Application
(Library Information Services, CUI Lahore, 2024) Hammad Hassan Hadi; FA20-BCS-014; Dr. Tahir Maqsood
Tutor Finder" is a simple and easy-to-use application that connects students, parents, and local tutors. It serves as a bridge between those who want to learn and those who want to teach. The platform helps find tutors quickly and efficiently, and it offers easy registration and profile creation for tutors, students, and parents. Tutors can easily display their qualifications, personal information, educational background, and subject expertise to attract potential students. The search function is robust and allows students to find tutors based on specific subjects, ensuring a perfect match. Feedback and ratings are highly valued, enabling informed decisions when selecting a tutor. The process of choosing the right tutor is streamlined, considering feedback, ratings, and expertise. The scheduling feature simplifies session planning, allowing students and tutors to share availability for an optimized learning experience. An administrator panel ensures the smooth operation of "Tutor Finder" by overseeing accounts and moderating feedback, and ratings. "Tutor Finder" is a comprehensive solution for establishing seamless and effective tutoring connections in today's dynamic educational landscape.