All Outputs (16)

Defeating Eavesdroppers with Ambient Backscatter Communications (2023)
Conference Proceeding
Huynh, N. V., Quang Hieu, N., Chu, N. H., Nguyen, D. N., Hoang, D. T., & Dutkiewicz, E. (2023). Defeating Eavesdroppers with Ambient Backscatter Communications. In 2023 IEEE Wireless Communications and Networking Conference (WCNC) Proceedings. https://doi.org/10.1109/wcnc55385.2023.10118774

Unlike conventional anti-eavesdropping methods that always require additional energy or computing resources (e.g., in friendly jamming and cryptography-based solutions), this work proposes a novel anti-eavesdropping solution that comes with mostly no... Read More about Defeating Eavesdroppers with Ambient Backscatter Communications.

Dynamic Optimal Coding and Scheduling for Distributed Learning over Wireless Edge Networks (2021)
Conference Proceeding
Van Huynh, N., Hoang, D. T., Nguyen, D. N., & Dutkiewicz, E. (2021). Dynamic Optimal Coding and Scheduling for Distributed Learning over Wireless Edge Networks. In 2021 IEEE Global Communications Conference (GLOBECOM). https://doi.org/10.1109/globecom46510.2021.9685719

This paper proposes a novel framework that can effectively address key challenges for the development of distributed learning over wireless edge networks. In particular, we first introduce a highly effective distributed learning model leveraging the... Read More about Dynamic Optimal Coding and Scheduling for Distributed Learning over Wireless Edge Networks.

Defeating Reactive Jammers with Deep Dueling-based Deception Mechanism (2021)
Conference Proceeding
Van Huynh, N., Nguyen, D. N., Hoang, D. T., & Dutkiewicz, E. (2021). Defeating Reactive Jammers with Deep Dueling-based Deception Mechanism. In ICC 2021 - IEEE International Conference on Communications. https://doi.org/10.1109/icc42927.2021.9500391

Conventional anti-jamming solutions like frequency hopping and rate adaptation that are more suitable for proactive jammers are not effective in dealing with reactive jammers. These advanced jammers with recent advances in signal detection can discer... Read More about Defeating Reactive Jammers with Deep Dueling-based Deception Mechanism.

Fast or Slow: An Autonomous Speed Control Approach for UAV-assisted IoT Data Collection Networks (2021)
Conference Proceeding
Chu, N. H., Hoang, D. T., Nguyen, D. N., Huynh, N. V., & Dutkiewicz, E. (2021). Fast or Slow: An Autonomous Speed Control Approach for UAV-assisted IoT Data Collection Networks. In 2021 IEEE Wireless Communications and Networking Conference (WCNC). https://doi.org/10.1109/wcnc49053.2021.9417563

Unmanned Aerial Vehicles (UAVs) have been emerging as an effective solution for IoT data collection networks thanks to their outstanding flexibility, mobility, and low operation costs. However, due to the limited energy and uncertainty from the data... Read More about Fast or Slow: An Autonomous Speed Control Approach for UAV-assisted IoT Data Collection Networks.

Optimal Beam Association in mmWave Vehicular Networks with Parallel Reinforcement Learning (2020)
Conference Proceeding
Van Huynh, N., Nguyen, D. N., Hoang, D. T., & Dutkiewicz, E. (2020). Optimal Beam Association in mmWave Vehicular Networks with Parallel Reinforcement Learning. In GLOBECOM 2020 - 2020 IEEE Global Communications Conference. https://doi.org/10.1109/globecom42002.2020.9348240

This paper develops a beam association framework for mm Wave vehicular networks to improve the system performance in terms of handover, disconnection time, and data rate under the high mobility of vehicles. In particular, we recruit the semi Markov d... Read More about Optimal Beam Association in mmWave Vehicular Networks with Parallel Reinforcement Learning.

Energy Trading and Time Scheduling for Energy-Efficient Heterogeneous Low-Power IoT Networks (2020)
Conference Proceeding
Nguyen, N., Nguyen, D. N., Hoang, D. T., Van Huynh, N., Nguyen, H., Nguyen, Q. T., & Dutkiewicz, E. (2020). Energy Trading and Time Scheduling for Energy-Efficient Heterogeneous Low-Power IoT Networks. In GLOBECOM 2020 - 2020 IEEE Global Communications Conference. https://doi.org/10.1109/globecom42002.2020.9322418

In this paper, an economic model is proposed to jointly optimize profits for participants in a heterogeneous IoT wireless-powered backscatter communication network. In the network under considerations, a power beacon and IoT devices (with various com... Read More about Energy Trading and Time Scheduling for Energy-Efficient Heterogeneous Low-Power IoT Networks.

Defeating Smart and Reactive Jammers with Unlimited Power (2020)
Conference Proceeding
Huynh, N. V., Hoang, D. T., Nguyen, D. N., Dutkiewicz, E., & Mueck, M. (2020). Defeating Smart and Reactive Jammers with Unlimited Power. In 2020 IEEE Wireless Communications and Networking Conference (WCNC). https://doi.org/10.1109/wcnc45663.2020.9120650

Among all wireless jammers, dealing with reactive ones is most challenging. This kind of jammer attacks the channel whenever it detects transmission from legitimate radios. With recent advances in self-interference suppression or in-band full-duplex... Read More about Defeating Smart and Reactive Jammers with Unlimited Power.

Defeating Jamming Attacks with Ambient Backscatter Communications (2020)
Conference Proceeding
Huynh, N. V., Nguyen, D. N., Hoang, D. T., Dutkiewicz, E., Mueck, M., & Srikanteswara, S. (2020). Defeating Jamming Attacks with Ambient Backscatter Communications. In 2020 International Conference on Computing, Networking and Communications (ICNC). https://doi.org/10.1109/icnc47757.2020.9049826

While the existing anti-jamming solutions tend to “escape” the attacks by finding another communication channel or adapting, waiting until the attacks cease, this work proposes an unprecedented method to combat jammers by leveraging the jamming signa... Read More about Defeating Jamming Attacks with Ambient Backscatter Communications.

Real-Time Network Slicing with Uncertain Demand: A Deep Learning Approach (2019)
Conference Proceeding
Van Huynh, N., Hoang, D. T., Nguyen, D. N., & Dutkiewicz, E. (2019). Real-Time Network Slicing with Uncertain Demand: A Deep Learning Approach. In ICC 2019 - 2019 IEEE International Conference on Communications (ICC). https://doi.org/10.1109/icc.2019.8761907

Practical and efficient network slicing often faces real-time dynamics of network resources and uncertain customer demands. This work provides an optimal and fast resource slicing solution under such dynamics by leveraging the latest advances in deep... Read More about Real-Time Network Slicing with Uncertain Demand: A Deep Learning Approach.

Energy Management and Time Scheduling for Heterogeneous IoT Wireless-Powered Backscatter Networks (2019)
Conference Proceeding
Nguyen, N., Van Huynh, N., Hoang, D. T., Nguyen, D. N., Nguyen, N., Nguyen, Q., & Dutkiewicz, E. (2019). Energy Management and Time Scheduling for Heterogeneous IoT Wireless-Powered Backscatter Networks. In ICC 2019 - 2019 IEEE International Conference on Communications (ICC). https://doi.org/10.1109/icc.2019.8761314

In this paper, we propose a novel approach to jointly address energy management and network throughput maximization problems for heterogeneous IoT low-power wireless communication networks. In particular, we consider a low-power communication network... Read More about Energy Management and Time Scheduling for Heterogeneous IoT Wireless-Powered Backscatter Networks.

Reinforcement Learning Approach for RF-Powered Cognitive Radio Network with Ambient Backscatter (2018)
Conference Proceeding
Huynh, N. V., Hoang, D. T., Nguyen, D. N., Dutkiewicz, E., Niyato, D., & Wang, P. (2018). Reinforcement Learning Approach for RF-Powered Cognitive Radio Network with Ambient Backscatter. In 2018 IEEE Global Communications Conference (GLOBECOM). https://doi.org/10.1109/glocom.2018.8647862

For an RF-powered cognitive radio network with ambient backscattering capability, while the primary channel is busy, the RF-powered secondary user (RSU) can either backscatter the primary signal to transmit its own data or harvest energy from the pri... Read More about Reinforcement Learning Approach for RF-Powered Cognitive Radio Network with Ambient Backscatter.

Offloading Energy Efficiency with Delay Constraint for Cooperative Mobile Edge Computing Networks (2018)
Conference Proceeding
Vu, T. T., Huynh, N. V., Hoang, D. T., Nguyen, D. N., & Dutkiewicz, E. (2018). Offloading Energy Efficiency with Delay Constraint for Cooperative Mobile Edge Computing Networks. In 2018 IEEE Global Communications Conference (GLOBECOM). https://doi.org/10.1109/glocom.2018.8647856

We propose a novel edge computing network architecture that enables edge nodes to cooperate in sharing computing and radio resources to minimize the total energy consumption of mobile users while meeting their delay requirements. To find the optimal... Read More about Offloading Energy Efficiency with Delay Constraint for Cooperative Mobile Edge Computing Networks.

Physical-virtual topological visualization of OF@TEIN SDN-enabled multi-site cloud (2017)
Conference Proceeding
Usman, M., Risdianto, A. C., Jungsu Han, Kim, J., & Nguyen Van Huynh. (2017). Physical-virtual topological visualization of OF@TEIN SDN-enabled multi-site cloud. In 2017 International Conference on Information Networking (ICOIN). https://doi.org/10.1109/icoin.2017.7899571

Infrastructure visualization based on monitored resource status is essential for the effective operation of modern SDN (Software-Defined Networking)-enabled cloud. More specifically, collecting and visualizing visibility information about both physic... Read More about Physical-virtual topological visualization of OF@TEIN SDN-enabled multi-site cloud.

An Energy-Aware Embedding Algorithm for Virtual Data Centers (2016)
Conference Proceeding
Nam, T. M., Huynh, N. V., Dai, L. Q., & Thanh, N. H. (2016). An Energy-Aware Embedding Algorithm for Virtual Data Centers. In 2016 28th International Teletraffic Congress (ITC 28). https://doi.org/10.1109/itc-28.2016.112

Cloud computing has emerged in the recent years as a promising paradigm that facilitates such new service models as Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS). As the number of cloud service prov... Read More about An Energy-Aware Embedding Algorithm for Virtual Data Centers.

Reducing Middle Nodes Mapping Algorithm for Energy Efficiency in Network Virtualization (2016)
Conference Proceeding
Nam, T. M., Huynh, N. V., & Thanh, N. H. (2017). Reducing Middle Nodes Mapping Algorithm for Energy Efficiency in Network Virtualization. In Advances in Information and Communication Technology: Proceedings of the International Conference, ICTA 2016 (500-509). https://doi.org/10.1007/978-3-319-49073-1_54

For the future of the Internet, Network Virtualization and Software-Defined Networking (SDN) are recognized as key technologies. They reshape computing and network architectures, provide a number of advantages including centralized management, scalab... Read More about Reducing Middle Nodes Mapping Algorithm for Energy Efficiency in Network Virtualization.

Constructing Energy-Aware Software- Defined Network Virtualization (2015)
Conference Proceeding
Nam, T. M., Thanh, N. H., Van, N. H., Long, K. B., Nguyen, H., Lam, N. D., & Ca, N. V. (2015). Constructing Energy-Aware Software- Defined Network Virtualization. In Proceedings of the Asia-Pacific Advanced Network. https://doi.org/10.7125/40.3

Energy consumption, as well as carbon emission, from ITC is growing extremely. Such a growth trend therefore needs to be facilitated by the creation of an energy-efficient network as an effort in developing the future Internet. Network Virtualization... Read More about Constructing Energy-Aware Software- Defined Network Virtualization.