CAE Adaptive Compression, Transmission Energy and Cost Optimization for m-Health Systems
Author | Al-Marridi A.Z. |
Author | Mohamed A. |
Author | Erbad A. |
Author | Guizani M. |
Available date | 2022-04-21T08:58:21Z |
Publication Date | 2021 |
Publication Name | IEEE International Conference on High Performance Switching and Routing, HPSR |
Resource | Scopus |
Identifier | http://dx.doi.org/10.1109/HPSR52026.2021.9481807 |
Abstract | The rapid increase in the number of patients requiring constant monitoring inspires researchers to investigate the area of mobile health (m-Health) systems for intelligent and sustainable remote healthcare applications. Extensive real-time medical data transmission using battery-constrained devices is challenging due to the dynamic network and the medical system constraints. Such requirements include end-to-end delay, bandwidth, transmission energy consumption, and application-level Quality of Services (QoS) requirements. As a result, adaptive data compression based on network and application resources before data transmission would be beneficial. A minimal distortion can be assured by applying Convolutional Auto-encoder (CAE) compression approach. This paper proposes a cross-layer framework that considers the patients' movement while compressing and transmitting EEG data over heterogeneous wireless environments. The main objective of the framework is to minimize the trade-off between the transmission energy consumption along with the distortion ratio and monetary costs. Simulation results show that an optimal trade-off between the optimization objectives is achieved considering networks and application QoS requirements for m-Health systems. 2021 IEEE. |
Sponsor | Qatar Foundation;Qatar National Research Fund |
Language | en |
Publisher | IEEE Computer Society |
Subject | Data transfer Economic and social effects Energy utilization mHealth Quality of service Remote patient monitoring Adaptive compression Compression approach Cross-layer framework Health care application Medical data transmission Mobile Health (M-Health) Transmission energy consumption Wireless environment Data communication systems |
Type | Conference Paper |
Volume Number | 2021-June |
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