Center for Electronics, Optoelectronics and Telecommunications

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Publications

Adaptive spectrum allocation for 5G wireless communication scenarios

Publication . Correia, Noélia; Al-Tam, Faroq; Rodriguez, J.

5G resources should be properly planned for users to have a good quality of service. This planning includes defining the most suitable numerology indexes and best spectrum allocation considering the requirements of current traffic, which may change over time. Furthermore, when accounting for changes in traffic pattern, any necessary reconfigurations should be minimized. Here in this article, an optimization model is developed for the planning of spectrum allocation to the best mix numerology. The model considers adapting the operating numerology mix according to the current presence (or not) of traffic requirements. The model also works under any wireless communication scenario in 5G, and under any traffic pattern.

2020Conference object

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Attention-based model and deep reinforcement learning for distribution of event processing tasks

Publication . Mazayev, Andriy; Al-Tam, Faroq; Correia, Noélia

Event processing is the cornerstone of the dynamic and responsive Internet of Things (IoT). Recent approaches in this area are based on representational state transfer (REST) principles, which allow event processing tasks to be placed at any device that follows the same principles. However, the tasks should be properly distributed among edge devices to ensure fair resources utilization and guarantee seamless execution. This article investigates the use of deep learning to fairly distribute the tasks. An attention-based neural network model is proposed to generate efficient load balancing solutions under different scenarios. The proposed model is based on the Transformer and Pointer Network architectures, and is trained by an advantage actorcritic reinforcement learning algorithm. The model is designed to scale to the number of event processing tasks and the number of edge devices, with no need for hyperparameters re-tuning or even retraining. Extensive experimental results show that the proposed model outperforms conventional heuristics in many key performance indicators. The generic design and the obtained results show that the proposed model can potentially be applied to several other load balancing problem variations, which makes the proposal an attractive option to be used in real-world scenarios due to its scalability and efficiency.

2022-07Journal article

Open Access

Radio Resource Scheduling with Deep Pointer Networks and Reinforcement Learning

Publication . Al-Tam, Faroq; Mazayev, Andriy; Correia, Noélia; Rodriguez, J.

This article presents an artificial intelligence (AI) adaptable solution to handle the radio resource scheduling (RRS) task in 5G networks. RRS is one of the core tasks in radio resource management (RRM) and aims to efficiently allocate frequency domain resources to users. The proposed solution is an advantage pointer critic (APC) deep reinforcement learning (DRL) agent. It is built with a deep pointer network architecture and trained by the policy gradient algorithm. The proposed agent is deployed in a system level simulator and the experimental results demonstrate its adaptability to network dynamics and efficiency when compared to baseline algorithms.

2020Conference object

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Callose synthase and xyloglucan endotransglucosylase gene expression over time in Citrus × clementina and Citrus × sinensis infected with citrus tristeza virus

Publication . da Silva, Melina; Germano, Sandra; Duarte, Amilcar; Pinto, Patrícia; Marques, Natália

Citrus tristeza virus (CTV) is a virus that already caused great losses in citrus producing regions. The cell wall of plant cells plays an important role in the defence response to viruses. Following several studies indicating that cell wall enzyme transcripts of callose synthase 7 (calS7) and xyloglucan endotransglucosylase 9 (xth9) are modified during a viral infection, transcript expression of calS7 isoform x5 (calS7x5) and xth9 was evaluated over time in Citrus x sinensis 'Valencia Late' (VL) and Citrus x clementina 'Fina' (CL), infected with the severe CTV isolate T318A, by quantitative (q) PCR. qPCR analysis of healthy and CTV infected citrus was performed at 15 days, 10 months and at 31 months post-inoculation (dpi/mpi), respectively. The CTV titer, evaluated at the three time-points by qPCR, increased over time in bark tissues, with VL plants exhibiting a titer about 5 times higher than CL 31 mpi. CTV infection did not cause significant changes in calS7x5 gene expression over time in both citrus cultivars. However, CTV infection was associated with significant up-regulation of xth9 in VL compared to controls 31 mpi. This study highlights that CTV infection can affect the expression of specific cell wall-associated genes over time and that this influence was distinct for VL and CL. This study provides further insight into the CTV-citrus host interaction, with the long-term response of VL to a severe CTV isolate involving a high expression of the xth9 gene.

2023Journal article

Open Access

Resource design in federated sensor networks using RELOAD/CoAP overlay architectures

Publication . Rodrigues, Luis; Guerreiro, Joel; Correia, Noélia

Sensor networks can be federated for wide-area geographical coverage using RELOAD/CoAP architectures. In this case, proxy nodes of constrained environments form a P2P overlay to announce device resources or sensor data. Although this is a standard-based solution, consistency problems may arise because P2P resources (data objects stored at the overlay network) may end up including similar device resource entries. This is so because device resource entries, or sensor data, can be announced under different P2P resource umbrellas, meaning that any update to them will require changing multiple P2P resources. Here in this article, a multi-layer approach is proposed to solve this issue, allowing for a more efficient storage/retrieval of IoT data. Information at the overlay network is kept consistent, although additional P2P anonymous resources must be created. A mathematical model is proposed for the planning of such multi-layer organization of P2P resources, together with a heuristic algorithm. A required overlay service is also discussed.

2021Journal article

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