On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks

Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting—both in terms of data and energy—data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios

Remote management of left ventricular device assisted patients

Ventricular Assist Devices (VADs) have been lately considered as an efficient destination therapy for heart disease, achieving remarkable survival scores. This paper presents an integrated end-to-end VAD patient architecture consisting of a web-based HL7 compatible Specialist Monitoring Application, an Android-based Patient Monitoring Application and a portable embedded Auto-Regulation Unit is described, delivering for the first time an interconnected solution that not only combines the characteristics of EHR systems and allows the efficient monitoring of patients' and VAD status, but also enables the remote control, configuration and auto-regulation of any VAD