A multi-step time-series clustering-based Seq2Seq LSTM learning for a single household electricity load forecasting

Z Masood, R Gantassi, Y Choi - Energies, 2022 - mdpi.com
The deep learning (DL) approaches in smart grid (SG) describes the possibility of shifting
the energy industry into a modern era of reliable and sustainable energy networks. This …

A reinforcement learning based routing protocol for software-defined networking enabled wireless sensor network forest fire detection

N Moussa, E Nurellari, K Azbeg, A Boulouz… - Future Generation …, 2023 - Elsevier
Abstract Critical event reporting Wireless Sensor Networks (WSNs) applications need vital
requirements (extended network lifetime, reliability, real time responsiveness, and …

Enhancing QoS and residual energy by using of grid-size clustering, K-means, and TSP algorithms with MDC in LEACH protocol

R Gantassi, Z Masood, Y Choi - IEEE Access, 2022 - ieeexplore.ieee.org
Some recent researches have shown that the energy consumption problem caused by data
collection in a wireless sensor network (WSN) based on a static data collector is a main …

Traffic prediction in SDN for explainable QoS using deep learning approach

G Wassie, J Ding, Y Wondie - Scientific Reports, 2023 - nature.com
The radical increase of multimedia applications such as voice over Internet protocol (VOIP),
image processing, and video-based applications require better quality of service (QoS) …

Enhanced Network QoS in Large Scale and High Sensor Node Density Wireless Sensor Networks Using (IR-DV-Hop) localization algorithm and mobile data collector …

R Gantassi, S Messous, Z Masood, QA Sias… - IEEE Access, 2024 - ieeexplore.ieee.org
This paper poses new challenges, especially when designing routing protocols to improve
the quality of service (QoS) criteria and the lifetime of large-scale wireless sensor networks …

A Review on Routing Protocols in Mobile IoT Networks based on SDN

SV Panwar, H Boukabous - 2024 3rd International Conference …, 2024 - ieeexplore.ieee.org
In mobile Internet of things (IoT) networks, SDN with routing protocols delivers a novel and
promising approach to these settings' dynamic and diversified issues. SDN principles and …

Regularized least square multi-hops localization algorithm for wireless sensor networks

H Liouane, S Messous, O Cheikhrouhou, M Baz… - IEEE …, 2021 - ieeexplore.ieee.org
Position awareness is very important for many sensor network applications. However, the
use of Global Positioning System receivers to every sensor node is very costly. Therefore …

Data traffic based shape independent adaptive unequal clustering for heterogeneous wireless sensor networks

T Shafique, AH Soliman, A Amjad - IEEE Access, 2024 - ieeexplore.ieee.org
Due to the technological advancements in wireless communication and their continuously
increasing applications in collaborative and cooperative smart infrastructures, energy …

Performance analysis of machine learning algorithms with clustering protocol in wireless sensor networks

R Gantassi, Z Masood, S Lim, QA Sias… - … Artificial Intelligence in …, 2023 - ieeexplore.ieee.org
In wireless sensor networks (WSN), machine learning (ML) algorithms have an important
role in cluster head (CH) selection according to several quality of service (QoS) metrics. This …

EFTVG: An Energy Efficient Fuzzy–Timer Clustering Approach in an Adaptive Virtual Grid Cluster Based WSN

A Mazinani, SM Mazinani, MJM Alyasiri - Wireless Personal …, 2024 - Springer
Clustering is an effective way that improves WSN lifetime. In this paper, unlike the other
approaches, an adaptive virtual grid is conducted to form cluster boundaries during a …