M.Phil / MS

Permanent URI for this collectionhttps://repository.cuilahore.edu.pk/handle/123456789/36

This collection archives the complete set of theses produced by students of the COMSATS University Islamabad, Lahore Campus.

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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.