Resource-aware distributed epilepsy monitoring using self-awareness from edge to cloud
F Forooghifar, A Aminifar… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
The integration of wearable devices in humans' daily lives has grown significantly in recent
years and still continues to affect different aspects of high-quality life. Thus, ensuring the …
years and still continues to affect different aspects of high-quality life. Thus, ensuring the …
Online learning for orchestration of inference in multi-user end-edge-cloud networks
Deep-learning-based intelligent services have become prevalent in cyber-physical
applications, including smart cities and health-care. Deploying deep-learning-based …
applications, including smart cities and health-care. Deploying deep-learning-based …
Exploring computation offloading in IoT systems
Abstract Internet of Things (IoT) paradigm raises challenges for devising efficient strategies
that offload applications to the fog or the cloud layer while ensuring the optimal response …
that offload applications to the fog or the cloud layer while ensuring the optimal response …
An edge-assisted and smart system for real-time pain monitoring
EK Naeini, S Shahhosseini… - 2019 IEEE/ACM …, 2019 - ieeexplore.ieee.org
In the healthcare sector, there is a strong demand for accurate objective pain assessment as
a key for effective pain management. Real-time and accurate objective pain assessment …
a key for effective pain management. Real-time and accurate objective pain assessment …
Context-aware sensing via dynamic programming for edge-assisted wearable systems
Healthcare applications supported by the Internet of Things enable personalized monitoring
of a patient in everyday settings. Such applications often consist of battery-powered sensors …
of a patient in everyday settings. Such applications often consist of battery-powered sensors …
Dynamic iFogSim: A framework for full-stack simulation of dynamic resource management in IoT systems
D Seo, S Shahhosseini, MA Mehrabadi… - … Conference on Omni …, 2020 - ieeexplore.ieee.org
Complex Internet of Things (IoT) applications such as Healthcare IoT include a variety of
compute, data, and communication kernel intensities and have diverse sensitivities of QoS …
compute, data, and communication kernel intensities and have diverse sensitivities of QoS …
A survey of phase classification techniques for characterizing variable application behavior
K Criswell, T Adegbija - IEEE Transactions on Parallel and …, 2019 - ieeexplore.ieee.org
Adaptable computing is an increasingly important paradigm that specializes system
resources to variable application requirements, environmental conditions, or user …
resources to variable application requirements, environmental conditions, or user …
Hybrid learning for orchestrating deep learning inference in multi-user edge-cloud networks
Deep-learning-based intelligent services have become prevalent in cyber-physical
applications including smart cities and health-care. Collaborative end-edge-cloud …
applications including smart cities and health-care. Collaborative end-edge-cloud …
Edge-centric optimization of multi-modal ml-driven ehealth applications
Smart eHealth applications deliver personalized and preventive digital healthcare services
to clients through remote sensing, continuous monitoring, and data analytics. Smart eHealth …
to clients through remote sensing, continuous monitoring, and data analytics. Smart eHealth …
Efficient training of deep convolutional neural networks by augmentation in embedding space
Recent advances in the field of artificial intelligence have been made possible by deep
neural networks. In applications where data are scarce, transfer learning and data …
neural networks. In applications where data are scarce, transfer learning and data …