Content Details | NUML Online Research Repository

Title QUEUE AWARE CONGESTION AVOIDANCE FOR HEALTHCARE DATA SHARING IN INTERNET OF THINGS

Author(s) Muhammad Zafarullah

Abstract The Internet of Healthcare Things (IoHT) emerged in order to assist with healthcare operations and patient monitoring by collecting continuous data from health sensors attached to the body of the patients. Because of the huge volume of the data collected from the sensor, it is difficult to control congestion at intermediary devices.Following research problems are addressed in this thesis; i) The number of congestion detection approaches in IoHT fail early detection since the sender is uninformed of the residual queue size. This proposed scheme introduces a Queue aware priority-based queuing strategy for delaying congestion in the IoHT while dealing with the huge volume of messages exchanged, particularly during emergencies scenario. The proposed approach presents a novel algorithm that employs a queue-aware strategy for early congestion detection, which is beneficial for early prevention of congestion. ii) The Internet of Healthcare Things (IoHT) emerged to help healthcare operations with use of an IoT and sensor networks. Delays in the processing of emergency packets in IoT-based healthcare systems can have fatal repercussions, including patient death. This study addresses the handling of emergent packets in high and low priority queues having high severity level. Depending on the severity level, packets are routed to the appropriate queues for immediate processing. This approach intends to improve data handling efficiency for packets carrying emergent data while also reducing queue congestion. iii) The Internet of Healthcare Things (IoHT) uses sensors attached to patients to continuously monitor health metrics and transfer data to the cloud for further analysis. However, the huge amount of data created creates a challenge, particularly in managing congestion at intermediary devices. To solve this issue, this work provides a queue-aware, priority-based queuing technique for efficiently managing data flow, particularly during emergencies. The suggested method eliminates unnecessary data transmission by providing simply a flag signal when sensor data does not change significantly or when there are no emergencies. This method enables the system to focus on essential, real-time data during emergencies while reducing congestion in normal circumstances.

Type Thesis/Dissertation PhD

Faculty Engineering and Computer Science

Department Computer Science

Language English

Publication Date

Subject

Publisher

Contributor(s)

Format

Identifier

Source

Relation

Coverage

Rights