Yazar
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A Multiscale Algorithm for Joint Forecasting-Scheduling to Solve the Massive Access Problem of IoT
Rodoplu, V.; Nakip, M.; Eliiyi, D.T.; Guzelis, C. (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2020)The massive access problem of the Internet of Things (IoT) is the problem of enabling the wireless access of a massive number of IoT devices to the wired infrastructure. In this article, we describe a multiscale algorithm ... -
Characterization of Line-of-Sight Link Availability in Indoor Visible Light Communication Networks Based on the Behavior of Human Users
Rodoplu, V.; Hocaoglu, K.; Adar, A.; Cikmazel, R.O.; Saylam, A. (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2020)We characterize the line-of-sight (LOS) link availability in indoor visible light communication (VLC) networks based on the behavior of human users. The VLC link availability is impacted by humans in three distinct ways: ... -
Comparative Study of Forecasting Schemes for IoT Device Traffic in Machine-to-Machine Communication
Nakip, M.; Gul, B.C.; Rodoplu, V.; Guzelis, C. (ASSOC COMPUTING MACHINERY, 2019)We present a comparative study of Autoregressive Integrated Moving Average (ARIMA), Multi-Layer Perceptron (MLP), 1-Dimensional Convolutional Neural Network (1-D CNN), and Long-Short Term Memory (LSTM) models on the problem ... -
An End-to-End Trainable Feature Selection-Forecasting Architecture Targeted at the Internet of Things
Nakip, M.; Karakayali, K.; Guzelis, C.; Rodoplu, V. (Institute of Electrical and Electronics Engineers Inc., 2021)We develop a novel end-to-end trainable feature selection-forecasting (FSF) architecture for predictive networks targeted at the Internet of Things (IoT). In contrast with the existing filter-based, wrapper-based and ...
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