Author
Now showing items 1-10 of 10
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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 Access, 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: ... -
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 ... -
Comparative study of forecasting schemes for IoT device traffic in machine-to-machine communication
Nakip, M.; Gul, B.C.; Rodoplu, V.; Guzelis, C. (ACM International Conference Proceeding Series, 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 ... -
Design of a Low-Cost Visible Light Communication (VLC) System for Music and Video Streaming
Hocaoglu, K.; Adar, A.; Arikok, Y.A.; Rodoplu, V. (Proceedings - 2019 Innovations in Intelligent Systems and Applications Conference, ASYU 2019, 2019)In this paper, we describe our design of an end-to-end Visible Light Communication (VLC) system prototype that is able to stream music and video. Our system is able to transmit and receive video and audio signals and is ... -
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 ... -
Joint Forecasting-Scheduling for the Internet of Things
Nakip, M.; Rodoplu, V.; Guzelis, C.; Tursel Eliiyi, D. (2019 IEEE Global Conference on Internet of Things, GCIoT 2019, 2019)We present a joint forecasting-scheduling (JFS) system, to be implemented at an IoT Gateway, in order to alleviate the Massive Access Problem of the Internet of Things. The existing proposals to solve the Massive Access ... -
Multi-Layer Perceptron Decomposition Architecture for Mobile IoT Indoor Positioning
Cakan, E.; Sahin, A.; Nakip, M.; Rodoplu, V. (IEEE, 2021)We develop a Multi-Layer Perceptron (MLP) Decomposition architecture for mobile Internet Things (IoT) indoor positioning. We demonstrate the performance of our architecture on an indoor system that utilizes ultra-wideband ... -
Subspace-Based Emulation of the Relationship between Forecasting Error and Network Performance in Joint Forecasting-Scheduling for the Internet of Things
Nakip, M.; Helva, A.; Guzelis, C.; Rodoplu, V. (IEEE, 2021)We develop a novel methodology that discovers the relationship between the forecasting error and the performance of the application that utilizes the forecasts. In our methodology, an Artificial Neural Network (ANN) learns ...

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