… In order to recommend high-quality services to users in edge computing … QoS prediction.
To this end, this paper proposes a QoS prediction method based on deep feature learning, as …

… a QoS prediction framework for service recommendation in mobile edge computing environment,
which is based on deep … We propose a new neural network model based on denoising …

… propose the adaptive QoS prediction strategies to realize adaptive QoS prediction for MEC …
can predict the fitted QoS of MEC services. We develop a set of adaptive QoS prediction strate…

… eg, from one edge server to another) often makes service QoS prediction values deviate from
… approach based on collaborative filtering and make QoS prediction based on user mobility. …

… to predict the QoS values in real edge computing environments with improved accuracy. To
this end, we propose a GAIN-QoS … The GAIN model is a deep learning model that generates …

… of the CF-based methods, especially in an edge computing environment. The most important
… , including global features learning and local features learning. In global features learning, …

… Joint Deep Networks based Multi-source Feature Learning (JDNMFL) framework for QoS
prediction in … feature learning in edge computing environment,” Mobile Netw. Appl., vol. 25, pp. …

… predicting the peak value of the traffic flow. For a multi-site case, we present an intelligent
IoT-based mobile traffic prediction… dispatching communication and computing resources. In our …

… [18] propose a denoising auto-encoder with fuzzy clustering and a recombination embedding
network for the edge computing environment to predict QoS values. However, their method …

… deep learning based IoT QoS prediction methods usually treat one-hot encoding vector of
user u and service s as input features to predict the QoS … characteristics of raw IoT QoS dataset…