Optimizing Energy-Distortion Trade-off for Vital Signs Delivery in Mobile Health Applications

Healthcare is considered a top priority worldwide, considering the swift increase in the number of chronic patients who require continuous monitoring. This motivates the researchers to develop scalable remote health applications. However, transmitting massive medical data through a dynamic network imposes multiple challenges in terms of both application and network requirements. Therefore, many researchers propose compression approaches that facilitate the transmission of the data. In this work, the movement of the patients was considered while running a multi-objective optimization problem between transmission energy and the distortion ratio of the reconstructed medical data. Spatio-TEmporal Parametric Stepping (STEPS) and Random WayPoint (RWP) mobility models were used for patient movement simulation. STEPS showed better performance than RWP. This makes it a more preferable mobility model to be used while simulating in-doors medical scenarios, with minimal patient movements.