A5005132068- Energy Efficient Wireless Sensor Networks
- IoT and Edge/Fog Computing
- Distributed Sensor Networks and Detection Algorithms
- Context-Aware Activity Recognition Systems
- Wireless Body Area Networks
- Water Quality Monitoring Technologies
- Energy Harvesting in Wireless Networks
- Molecular Communication and Nanonetworks
- Anomaly Detection Techniques and Applications
- Opportunistic and Delay-Tolerant Networks
- Air Quality Monitoring and Forecasting
- Blockchain Technology Applications and Security
- Traffic Prediction and Management Techniques
- Complex Network Analysis Techniques
- Underwater Vehicles and Communication Systems
- Vehicular Ad Hoc Networks (VANETs)
- Security in Wireless Sensor Networks
- Modular Robots and Swarm Intelligence
- Neural Networks and Applications
- Indoor and Outdoor Localization Technologies
- IoT-based Smart Home Systems
- Network Security and Intrusion Detection
- Data Management and Algorithms
- Advanced Graph Neural Networks
- Time Series Analysis and Forecasting
American University of the Middle East
2022-2025
American University of Culture and Education
2017-2023
Lebanese University
2014-2022
Antonine University
2018-2021
Centre National de la Recherche Scientifique
2017-2020
University of California, Merced
2020
Université de Bretagne Occidentale
2019-2020
Laboratoire des Sciences et Techniques de l’Information de la Communication et de la Connaissance
2019-2020
École nationale supérieure de techniques avancées Bretagne
2019-2020
Franche-Comté Électronique Mécanique Thermique et Optique - Sciences et Technologies
2014-2018
The use of wireless sensor network for industrial applications has attracted much attention from both academic and sectors. It enables a continuous monitoring, controlling, analyzing the processes, contributes significantly to finding best performance operations. Sensors are typically deployed gather data environment transmit it periodically end user. Since sensors resource constrained, effective energy management should include new collection techniques an efficient utilization sensors. In...
Underwater wireless sensor networks (UWSNs) have recently been proposed as a way to observe and explore aquatic environments. Sensors in such are used perform pollution monitoring, disaster prevention, or assisted navigation send monitored data the sink. Compared with traditional networks, sensors UWSNs consume more energy due acoustic technology under water communications. Node clustering is common method organize traffic reduce in-network communications while improving scalability...
Nowadays, keeping a strong and good health is one of the main concern general public or governments. The Internet Things (IoT) has been emerged as an efficient solution to build smart healthcare systems deployed either at hospitals in-home. Such networks rely on biomedical sensors which are used in electronics-based medical equipment remotely collect vital signs patients (pressure, temperature, hart rate, oxygen saturation etc.). Generally, these biosensors implemented inside patient's body...
Wireless sensor networks (WSNs) are almost everywhere, they exploited for thousands of applications in a densely distributed manner. Such deployment makes WSNs one the highly anticipated key contributors big data nowadays. Hence, aggregation is attracting much attention from researchers as efficient way to reduce huge volume generated by eliminating redundancy among sensing data. In this paper, we propose an technique clustering-based periodic wireless networks. Further local at node level,...
In-network data aggregation becomes an important technique to achieve efficient transmission in wireless sensor networks (WSN). Energy efficiency, latency and accuracy are the major key elements evaluating performance of in-network technique. The trade-offs among them largely depends on specific application. For instance, prefix frequency filtering (PFF) is a good recently example for that optimizing energy consumption accuracy. objective PFF find similar sets generated by neighboring nodes...
Monitoring phenomena and environments is an emergent required field in our today systems applications. Hence, wireless sensor networks (WSNs) have attracted considerable attention from the research community as efficient way to explore various kinds of environments. Sensor applications can be useful different domains (terrestrial, underwater, space exploration, etc.). However, one major constraints such energy consumption that increases when data transmission increases. Consequently,...
The Internet of Things (IoT) is expanding rapidly, but the security IoT devices remains a noteworthy concern due to resource limitations and existing conventions. This research investigates proposes use Light certificate with Constrained Application Protocol (CoAP) instead X509 based on traditional PKI/CA. We start by analyzing impediments current CoAP over DTLS mode CA root in constrained device suggest implementation LightCert4IoT for DTLS. paper also describes new modified handshake...
Background: Devices connected to the internet are increasing day by day, and era of Internet Things (IoT) is anticipated. However, handling big data generated IoT networks will present considerable challenge for decision makers.Wireless sensor (WSNs) one sources in IoT. In such networks, a wide range areas monitored thousands sensors where gathered sent sink node. Unfortunately, WSNs impose many challenges compared other types networks. Data management mainly challenging task due huge amount...
In the last years, world has witnessed a potential increasing in patient number resulted from of aged persons along with emergence new virus and diseases. This imposes high pressure on hospitals that suffer shortage medical staff, personal equipment adequate interventions to overcome such challenge. Particularly, nurse scheduling is becoming crucial operation order efficiently handing patents performance health system. this paper, we present an efficient Nurse-Patient Scheduling (NPS)...
We present MOFA, an open-source generative AI (GenAI) plus simulation workflow for high-throughput generation of metal-organic frameworks (MOFs) on large-scale high-performance computing (HPC) systems. MOFA addresses key challenges in integrating GPU-accelerated GPU-intensive GenAI tasks, including distributed training and inference, alongside CPU- GPU-optimized tasks screening filtering AI-generated MOFs using molecular dynamics, density functional theory, Monte Carlo simulations. These...
In wireless sensor networks (WSNs), redundant collected measures and the resulting packets to sendto sink are likely happen repeatedly. As transmission is an expensive issue in term of energy, eliminating data redundancy reducing communication load can minimize energy consumption extend whole network lifetime. this paper, we propose adaptive protocol composed two phases, called aggregation (ATP), that operates on each node separately order reduce its save energy. We consider a cluster-based...
Nowadays, the increasing number of patients accompanied with emergence new symptoms and diseases makes heath monitoring assessment a complicated task for medical staff hospitals. Indeed, processing big heterogeneous data collected by biomedical sensors along need patients’ classification disease diagnosis become major challenges several health-based sensing applications. Thus, combination between remote devices technologies have been proven as an efficient low cost solution healthcare In...
Limited battery power and high transmission energy consumption in wireless sensor networks make in-network aggregation prediction a challenging area for researchers. The most consumable operation is transmitting data by node, comparing it with the of computation which negligible. trade-off between communication provides applications benefit when processing at network side rather than simply data. In this study, authors consider cluster-based technique sent periodically from nodes to their...
Today, we are awash in a flood of data coming from different generating sources. Wireless sensor networks (WSNs) one the big contributors, where being collected at unprecedented scale. Unfortunately, much these no interest, meaningless, and redundant. Hence, reduction is becoming fundamental operation order to decrease communication costs enhance mining WSNs. In this paper, propose two-level approach for networks. The first level operated by nodes consists compressing while using Pearson...
Data aggregation in wireless sensor networks (WSN) has been proven as an effective technique for eliminating redundancy and forwarding only the extracted information from raw data. Furthermore, by doing so data can often reduce communication cost extend whole network lifetime. In this paper we study a new prefix-suffix filtering periodic (PSN). We investigate problem of finding all pair nodes generating similar sets. added suffix frequency filter to existing prefix filtering. Our goal is...
Popularity of wireless sensor networks (WSNs) is increasing day a where hundreds or thousands applications are explored. In most such applications, the need gathering data periodically about monitored environment beside limited, generally irreplaceable, power sources make energy conservation and big reduction two fundamental challenges in networks. this paper, we propose an Adaptive Distributed Data Gathering (ADiDaG) technique for saving periodic WSN applications. ADiDaG works into rounds...
The need for remote healthcare monitoring systems that utilize limited resources’ biosensors is growing. These increase the amount of transmitted data across Internet Healthcare Things (IoHT) network. Therefore, it necessary to decrease and make a decision at edge gateway save energy produce quick response medical staff. This paper proposes an energy-efficient multisensor adaptive sampling aggregation (EMASA) patient in computing-based IoHT networks. In edge-based network, EMASA operates on...
Data reduction is an effective technique for energy saving in wireless sensor networks. It consists on reducing sensing and transmitting data while conserving a high quality of collected information. In this letter, we propose online model based Kruskal-Wallis test that allows nodes to adapt their rates the variance. Then, local aggregation algorithm reduce further set size before sending sink. Experimentation real telosB network testbed shows effectiveness our approach transmitted over thus energy.