Performance of Cognitive Radio Sensor Networks Using Hybrid Automatic Repeat ReQuest: Stop-and-Wait
Journal Article
Khan, F., ur Rehman, A., Usman, M., Tan, Z., & Puthal, D. (2018)
Performance of Cognitive Radio Sensor Networks Using Hybrid Automatic Repeat ReQuest: Stop-and-Wait. Mobile Networks and Applications, https://doi.org/10.1007/s11036-018-1020-4
The enormous developments in the field of wireless communication technologies have made the unlicensed spectrum bands crowded, resulting uncontrolled interference to the tradi...
Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines
Journal Article
Mocanu, D. C., Bou Ammar, H., Puig, L., Eaton, E., & Liotta, A. (2017)
Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines. Pattern Recognition, 69, 325-335. https://doi.org/10.1016/j.patcog.2017.04.017
Estimation, recognition, and near-future prediction of 3D trajectories based on their two dimensional projections available from one camera source is an exceptionally difficul...
A Chain Topology for Efficient Monitoring of Food Grain Storage using Smart Sensors
Conference Proceeding
Kumar Mishra, A., Kumar Tripathy, A., Obaidat, M. S., Tan, Z., Prasad, M., Sadoun, B., & Puthal, D. (2018)
A Chain Topology for Efficient Monitoring of Food Grain Storage using Smart Sensors. In Proceedings of the 15th International Joint Conference on e-Business and Telecommunications, (89-98). https://doi.org/10.5220/0006850602550264
Due to lack of an efficient monitoring system to periodically record environmental parameters for food grain storage, a huge loss of food grains in storage is reported every y...
A topological insight into restricted Boltzmann machines
Journal Article
Mocanu, D. C., Mocanu, E., Nguyen, P. H., Gibescu, M., & Liotta, A. (2016)
A topological insight into restricted Boltzmann machines. Machine Learning, 104(2-3), 243-270. https://doi.org/10.1007/s10994-016-5570-z
Restricted Boltzmann Machines (RBMs) and models derived from them have been successfully used as basic building blocks in deep artificial neural networks for automatic feature...
Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach
Journal Article
Di Mauro, M., & Liotta, A. (2019)
Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach. IEEE Transactions on Network and Service Management, 16(4), 1493-1506. https://doi.org/10.1109/tnsm.2019.2943776
The Next Generation 5G Networks can greatly benefit from the synergy between virtualization paradigms, such as the Network Function Virtualization (NFV), and service provision...
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
Journal Article
Mocanu, D. C., Mocanu, E., Stone, P., Nguyen, P. H., Gibescu, M., & Liotta, A. (2018)
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science. Nature Communications, 9(1), 1-12. https://doi.org/10.1038/s41467-018-04316-3
Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from ...
Fast Millimeter Wave Assisted Beam-Steering for Passive Indoor Optical Wireless Networks
Journal Article
Torres Vega, M., Koonen, A. M. J., Liotta, A., & Famaey, J. (2018)
Fast Millimeter Wave Assisted Beam-Steering for Passive Indoor Optical Wireless Networks. IEEE Wireless Communications Letters, 7(2), 278-281. https://doi.org/10.1109/lwc.2017.2771771
In light of the extreme radio congestion, the time has come to consider the upper parts of the electromagnetic spectrum. Optical beam-steered wireless communications offer gre...
Decentralized dynamic understanding of hidden relations in complex networks
Journal Article
Mocanu, D. C., Exarchakos, G., & Liotta, A. (2018)
Decentralized dynamic understanding of hidden relations in complex networks. Scientific Reports, 8(1), https://doi.org/10.1038/s41598-018-19356-4
Almost all the natural or human made systems can be understood and controlled using complex networks. This is a difficult problem due to the very large number of elements in s...
Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks
Journal Article
Savaglio, C., Pace, P., Aloi, G., Liotta, A., & Fortino, G. (2019)
Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks. IEEE Access, 7, 29355-29364. https://doi.org/10.1109/access.2019.2902371
High-density communications in wireless sensor networks (WSNs) demand for new approaches to meet stringent energy and spectrum requirements. We turn to reinforcement learning,...
Resilience of Video Streaming Services to Network Impairments
Journal Article
Torres Vega, M., Perra, C., & Liotta, A. (2018)
Resilience of Video Streaming Services to Network Impairments. IEEE Transactions on Broadcasting, 64(2), 220-234. https://doi.org/10.1109/tbc.2017.2781125
When dealing with networks, performance management through conventional quality of service (QoS)-based methods becomes difficult and is often ineffective. In fact, quality eme...