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

Abstract

Abstract-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 inthe-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.

The Internet of Things for Health Care: A Comprehensive Survey

“…3 describes how a heterogeneous computing grid collects enormous amounts of vital signs and sensor data such as blood pressure (BP), body temperature, electrocardiograms (ECG), and oxygen saturation and forms a VOLUME 3, 2015 typical IoThNet topology. It transforms the heterogeneous computing and storage capability of static and mobile electronic devices such as laptops, smartphones, and medical terminals into hybrid computing grids [15]. Fig.…”

Advanced internet of things for personalised healthcare systems: A survey

“…But for IoT enabled PHS, the topology needs to be a heterogeneous computing grids for collecting enormous amount of vital signs and health data, such as blood sugar, physical activity, blood pressure, oxygen saturation, etc. Viswanathan et.al [85] presents a new mobile grid computing topology 'hybrid static/mobile computing grid' for data-and patient-centric IoT enabled healthcare systems. It transfers the heterogeneous computing and storage capability of static and mobile electronic devices into hybrid computing grids by employing self-optimization and self-healing.…”

Survei IoT Healthcare Device

“…Gambar 4 menjelaskan bagaimana grid komputasi heterogen mengumpulkan sejumlah besar tanda-tanda vital dan data sensor seperti tekanan darah (BP), suhu tubuh, elektrokardiogram (ECG), dan saturasi oksigen dan membentuk topologi khas IoThNet. Grid ini mengubah komputasi heterogen dan kemampuan penyimpanan perangkat elektronik statis dan mobile seperti laptop, smartphone, dan terminal medis menjadi grid komputasi hybrid [8].…”