Outputs (10)

Short-long term anomaly detection in wireless sensor networks based on machine learning and multi-parameterized edit distance (2018)
Journal Article
Cauteruccio, F., Fortino, G., Guerrieri, A., Liotta, A., Mocanu, D. C., Perra, C., …Torres Vega, M. (2019). Short-long term anomaly detection in wireless sensor networks based on machine learning and multi-parameterized edit distance. Information Fusion, 52, 13-30. https://doi.org/10.1016/j.inffus.2018.11.010

Heterogeneous wireless sensor networks are a source of large amount of different information representing environmental aspects such as light, temperature, and humidity. A very important research problem related to the analysis of the sensor data is... Read More about Short-long term anomaly detection in wireless sensor networks based on machine learning and multi-parameterized edit distance.

Interference graphs to monitor and control schedules in low-power WPAN (2018)
Journal Article
van der Lee, T., Liotta, A., & Exarchakos, G. (2019). Interference graphs to monitor and control schedules in low-power WPAN. Future Generation Computer Systems, 93, 111-120. https://doi.org/10.1016/j.future.2018.10.014

Highlights • This study presents the complete and slotted interference graph model. • The service uses the complete interference graph to evaluate the network. • Slotted interference graphs are used to reschedule problematic connections. • Rea... Read More about Interference graphs to monitor and control schedules in low-power WPAN.

Deep learning with multi-scale feature fusion in remote sensing for automatic oceanic eddy detection (2018)
Journal Article
Du, Y., Song, W., He, Q., Huang, D., Liotta, A., & Su, C. (2019). Deep learning with multi-scale feature fusion in remote sensing for automatic oceanic eddy detection. Information Fusion, 49, 89-99. https://doi.org/10.1016/j.inffus.2018.09.006

Oceanic eddies are ubiquitous in global oceans and play a major role in ocean energy transfer and nutrients distribution, thus being significant for understanding ocean current circulation and marine climate change. They are characterized by a combin... Read More about Deep learning with multi-scale feature fusion in remote sensing for automatic oceanic eddy detection.

Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science (2018)
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), Article 2383. 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 the network properties of biological neural networks (e.g. sparsity, scale-... Read More about Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.

An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0 (2018)
Journal Article
Pace, P., Aloi, G., Gravina, R., Caliciuri, G., Fortino, G., & Liotta, A. (2019). An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0. IEEE Transactions on Industrial Informatics, 15(1), 481-489. https://doi.org/10.1109/tii.2018.2843169

Edge computing paradigm has attracted many interests in the last few years as a valid alternative to the standard cloud-based approaches to reduce the interaction timing and the huge amount of data coming from Internet of Things (IoT) devices toward... Read More about An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0.

On-Line Building Energy Optimization Using Deep Reinforcement Learning (2018)
Journal Article
Mocanu, E., Mocanu, D. C., Nguyen, P. H., Liotta, A., Webber, M. E., Gibescu, M., & Slootweg, J. G. (2019). On-Line Building Energy Optimization Using Deep Reinforcement Learning. IEEE Transactions on Smart Grid, 10(4), 3698-3708. https://doi.org/10.1109/tsg.2018.2834219

Unprecedented high volumes of data are becoming available with the growth of the advanced metering infrastructure. These are expected to benefit planning and operation of the future power systems and to help customers transition from a passive to an... Read More about On-Line Building Energy Optimization Using Deep Reinforcement Learning.

A Review of Predictive Quality of Experience Management in Video Streaming Services (2018)
Journal Article
Torres Vega, M., Perra, C., De Turck, F., & Liotta, A. (2018). A Review of Predictive Quality of Experience Management in Video Streaming Services. IEEE Transactions on Broadcasting, 64(2), 432-445. https://doi.org/10.1109/tbc.2018.2822869

Satisfying the requirements of devices and users of online video streaming services is a challenging task. It requires not only managing the network quality of service but also to exert real-time control, addressing the user's quality of experience (... Read More about A Review of Predictive Quality of Experience Management in Video Streaming Services.

Self-Learning Power Control in Wireless Sensor Networks (2018)
Journal Article
Chincoli, M., & Liotta, A. (2018). Self-Learning Power Control in Wireless Sensor Networks. Sensors, 18(2), Article 375. https://doi.org/10.3390/s18020375

Current trends in interconnecting myriad smart objects to monetize on Internet of Things applications have led to high-density communications in wireless sensor networks. This aggravates the already over-congested unlicensed radio bands, calling for... Read More about Self-Learning Power Control in Wireless Sensor Networks.

Decentralized dynamic understanding of hidden relations in complex networks (2018)
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 such networks, on the order of billions and higher, which makes it impossibl... Read More about Decentralized dynamic understanding of hidden relations in complex networks.

Resilience of Video Streaming Services to Network Impairments (2018)
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 emerges as an end-to-end factor, for it is particularly sensitive to the end-u... Read More about Resilience of Video Streaming Services to Network Impairments.