Mobile grid computing for data- and patient-centric ubiquitous healthcare

A new context-aware data- and patient-centric paradigm for ubiquitous healthcare is central to deliver personalized healthcare solutions to the elderly and the physically challenged. However, this new paradigm requires real-time in-the-field processing of wirelessly collected vital signs using inherently complex physiological models and analysis of the processed information (derived physiological parameters) under context (e.g., location, ambient conditions, current physical activity) to extract knowledge about the health condition of patients. As the computational capabilities of biomedical sensor nodes are insufficient to run these models, an innovative resource provisioning framework that harnesses the computing capabilities of under-utilized electronic devices in the vicinity (e.g., smart phones, laptops, tablets, DVRs, medical terminals) to form a mobile computing grid is presented. The framework is imparted with self-optimization and self-healing capabilities for efficiency and robustness under uncertainty, respectively. The proposed mobile grid management framework serves as a key enabling technology for Internet-of-Things- (IoT-) based next-generation ubiquitous healthcare solutions.