Abdelhak Boulaalam

Abdelhak Boulaalam

Université Sidi Mohamed Ben Abdellah

H-index: 10

Africa-Morocco

About Abdelhak Boulaalam

Abdelhak Boulaalam, With an exceptional h-index of 10 and a recent h-index of 10 (since 2020), a distinguished researcher at Université Sidi Mohamed Ben Abdellah, specializes in the field of Computer science, Internet of Things, Intelligent Product, PLM.

Abdelhak Boulaalam Information

University

Université Sidi Mohamed Ben Abdellah

Position

National School of Applied Sciences

Citations(all)

272

Citations(since 2020)

256

Cited By

59

hIndex(all)

10

hIndex(since 2020)

10

i10Index(all)

12

i10Index(since 2020)

11

Email

University Profile Page

Université Sidi Mohamed Ben Abdellah

Abdelhak Boulaalam Skills & Research Interests

Computer science

Internet of Things

Intelligent Product

PLM

Top articles of Abdelhak Boulaalam

An efficient model-based clustering via joint multiple sink placement for WSNs

Wireless sensor networks consist of many restrictive sensor nodes with limited abilities, including limited power, low bandwidth and battery, small storage space, and limited computational capacity. Sensor nodes produce massive amounts of data that are then collected and transferred to the sink via single or multihop pathways. Since the nodes’ abilities are limited, ineffective data transmission across the nodes makes the network unstable due to the rising data transmission delay and the high consumption of energy. Furthermore, sink location and sensor-to-sink routing significantly impact network performance. Although there are suggested solutions for this challenge, they suffer from low-lifetime networks, high energy consumption, and data transmission delay. Based on these constrained capacities, clustering is a promising technique for reducing the energy use of wireless sensor networks, thus improving their performance. This paper models the problem of multiple sink deployment and sensor-to-sink routing using the clustering technique to extend the lifetime of wireless sensor networks. The proposed model determines the sink placements and the most effective way to transmit data from sensor nodes to the sink. First, we propose an improved ant clustering algorithm to group nodes, and we select the cluster head based on the chance of picking factor. Second, we assign nodes to sinks that are designated as data collectors. Third, we provide optimal paths for nodes to relay the data to the sink by maximizing the network’s lifetime and improving data flow. The results of simulation on a real network dataset demonstrate that our proposal …

Authors

Soukaina Bouarourou,Abderrahim Zannou,El Habib Nfaoui,Abdelhak Boulaalam

Journal

Future Internet

Published Date

2023/2/15

Data Gathering from IoT Networks

The Internet of Things (IoT) is a new paradigm where anything can be connected to Internet using heterogeneous networks; they have an unstable structure according to the constraint devices that are the main characteristic of this paradigm. Also, edge computing is becoming a fast base for most IoT devices, especially in smart cities. It is the ideal solution for providing devices with the connectivity needed to deliver low-latency services to end-users. However, selecting nodes that can participate in data gathering by edge computing or by other nodes must be efficient in terms of the performance of these constrained devices. To deal with these issues, we propose a clustering mechanism to group the nodes based on their capabilities using the k-means algorithm, and then the selection phase can be lanced to select the most capable node, where two phases are performed by the edge server. The simulation results …

Authors

Abderrahim Zannou,Abdelhak Boulaalam,Naoufal El Allali,Mourad Fariss

Published Date

2023/12/16

IoT-Based Intelligent Handicraft System Using NFC Technology

Craft manufacturing activities are rapidly developing all over the world as the global economy grows. Meanwhile, the handcrafted industry is boom ing, particularly traditional crafts that have been passed down through gen erations. Customers, such as tourists, require more scientific and practical guidance to ensure that a craft product is genuine in these circumstances. An Internet of Things (IoT)-based craft system is presented in this chapter to track the craft product in its life cycle, especially, when it reaches its des tination. The embedded system provides suggestions for end-users and the manufacturing actors using a product identification label. During the process of manufacturing products and shopping, the collected data are exchanged between the embedded sensors and the customer’s smartphone. This data will then be submitted to cloud computing for processing to extract beneficial guiding information for consumers and artisans. A detailed implementation of the various system components is also presented in the rest of this chapter.

Authors

Youssef Aounzou,Fahd Kalloubi,Abdelhak Boulaalam

Journal

Smart Embedded Systems and Applications

Published Date

2023/2/20

Toward an IoT-Based System to Ensure Product Identification of Moroccan Handicrafts

With the rapid growth of the global economy, craft manufacturing activities have known significant progress in recent decades. Consequently, the handmade industry is booming thanks to a rise in demand for artisan products. However, customers such as tourists need more scientific and practical guidance to be sure that the handmade product is original. Throughout this paper, we will introduce a targeted solution for products identification based on the Internet of Things to monitor products in their lifecycle. Also, our system aims to protect from counterfeiting the artistic and brand values of traditional handicrafts handed down from generation to generation. To prove the effectiveness of our proposal we implemented a prototype that allows product identification of Moroccan handicraft products using labeling strategies and scientific methods.

Authors

Youssef Aounzou,Fahd Kalloubi,Abdelhak Boulaalam

Published Date

2022/1/28

Iot based smart agriculture monitoring system with predictive analysis

Internet of things (IoT) is one of the fastest-growing technologies in the last few years. This technology might be used widely in real-life agriculture. In this paper, we have proposed a low-cost and easy accessible IoT-based smart agriculture monitoring system along with double-tier data storage facility to store and secure such a huge volume of data by an IoT device. Tier-1 focuses on collecting data from different sensors and stores it locally using the SD card. Tier-2 uses a cloud server for storing the large volume of IoT sensors data. Farmer or analyzer can be able to monitor the actual condition of the agricultural field remotely using a smartphone application or a computer. There exists a scope to store data for further analysis.

Authors

MD Safayet Ahmad,Akhlak Uz Zaman

Published Date

2020

Data Flow Optimization in the Internet of Things

The Internet of Things (IoT) is constituted of an important number of constrained nodes limited in terms of power energy, computation capacity, storage capacity. They produce a considerable amount of data, which increases the data flflow in the network. The ineffificient transmission of data via constrained nodes makes the network unstable, the energy consumption increases rapidly, and the data delay increases strictly. To overcome these limitations, we propose a new approach that allows nodes to select the effificient path to transmit data from source nodes to base stations (BSs) to optimize the data flflow in the constrained network. First, we grouped nodes using a density peaks (DP) clustering algorithm based on the coordinate’s location of these nodes. Second, using the group nodes, the assignment of nodes to BSs that are considered as the collectors of data is performed. Third, the nodes make a dynamic and automated path plan to optimize the data flflow in the constrained network. Simulation results on a real network data set demonstrate that our proposal outperforms the state-of-the-art approaches in terms of the number of hops to achieve the cluster head (CH) node, the data delay, the network lifetime, and the number of the alive nodes.

Authors

Abderrahim Zannou,Abdelhak Boulaalam

Journal

Statistics, Optimization & Information Computing

Published Date

2022/2/8

Sensors Deployment in IoT Environment

The rapid growth of wireless sensor networks (WSNs) demand creates numerous Internet of Things (IoT) applications applied in several domains. On account of its wide-ranging application, WSNs that can monitor specific sensing range is the most adopted IoT platform. Therefore, the search for preferable placements and the optimal number of sensor node deployments can reduce computation, energy, cost, and communication overhead, which are the most factors that directly impact the coverage network. To address the problem, we propose a deployment and connectivity model bonded to sensor networks to ensure sensor deployment on a grid for target coverage while allowing connectivity. The model focuses on the k-coverage problem, which necessitates selecting a minimum subset of nodes such that at least k sensor nodes cover each point of a field of interest. The simulation results proved the proposed …

Authors

Soukaina Bouarourou,Abderrahim Zannou,Abdelhak Boulaalam,El Habib Nfaoui

Published Date

2022/1/28

Query Processing in IoT Based on Spatial and Temporal Information

As the Internet of Things (IoT) advances, the relevance of modeling and analyzing IoT data has expanded significantly. Because of the huge number of smart objects and the large scale of the network, classic query processing approaches aren’t always applicable, as processing large amounts of data collected in real-time from a diversity of IoT devices remains a challenge. We propose a novel approach for query processing in this study, where the queries are provided by end-users to locate the effective edge devices inexpensively way. We suggest a predictive model based on a query’s geographical and temporal information to search the data/service from the most potential devices. Results have demonstrated a high level of performance in terms of accuracy and recall, as well as, the proposed methodology can reach the destinations within a brief time frame, which speeds up the search process across a huge …

Authors

Chaimae Kanzouai,Abderrahim Zannou,El Habib Nfaoui,Abdelhak Boulaalam

Published Date

2022/1/28

An optimal base stations positioning for the internet of things devices

Internet of Things (IoT) consists of an enormous number of devices and networks. The IoT's principal parameters are energy consumption, network lifetime, processing capacity, data collection, and data delay. Data transmission from nodes via multi-hop communication to a base station (BS) is expensive in terms of delay and energy consumption, where the nodes near the base station will consume more energy than others. To resolve this problem, we deal with the placement of multiple base stations; the objective is to make the most of nodes connected to base stations via one-hop communication and other nodes via an optimal path. To do this, we improved an algorithm of clustering to be suitable to our scenario to make the most of nodes connected to BS via one-hop, and a new method allows the out-clustering nodes to be connected via an optimal path. The simulation results on real data sets show that our …

Authors

Abderrahim Zannou,Abdelhak Boulaalam

Published Date

2021/5/19

IoT and AI based intelligent system to fight against COVID-19

In this global health crisis, several efforts have been launched to monitor and control the spread of the COVID-19 pandemic. Those efforts require the support of new technologies like the Internet of Things, Artificial Intelligence, Image and Video Processing, Big Data, and Machine Learning to tackle various problems related to this viral pandemic. In these circumstances, public places such as hospitals, public transportation, and supermarkets need a more scientific and practical system/guidance to identify the probable COVID-19 cases. In this paper, we design an Internet of Things-Artificial Intelligence IoT-AI based intelligent system to monitor the suspect cases in public places. Based on implicit/Explicit data acquisition flow, the system provides information to public authorities. In a public place, the actions of suspicious people are collected by sensors such as thermal cameras, connected cameras, and Smartphone …

Authors

Asmae Bouchareb,Abdelhak Boulaalam,Insaf Bellamine

Published Date

2021/4/1

A bio-inspired adaptive model for search and selection in the Internet of Things environment

The Internet of Things (IoT) is a paradigm that can connect an enormous number of intelligent objects, share large amounts of data, and produce new services. However, it is a challenge to select the proper sensors for a given request due to the number of devices in use, the available resources, the restrictions on resource utilization, the nature of IoT networks, and the number of similar services. Previous studies have suggested how to best address this challenge, but suffer from low accuracy and high execution times. We propose a new distributed model to efficiently deal with heterogeneous sensors and select accurate ones in a dynamic IoT environment. The model’s server uses and manages multiple gateways to respond to the request requirements. First, sensors were grouped into three semantic categories and several semantic sensor network types in order to define the space of interest. Second, each type’s sensors were clustered using the Whale-based Sensor Clustering (WhaleCLUST) algorithm according to the context properties. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was improved to search and select the most adequate sensor matching users’ requirements. Experimental results from real data sets demonstrate that our proposal outperforms state-of-the-art approaches in terms of accuracy (96%), execution time, quality of clustering, and scalability of clustering.

Authors

Soukaina Bouarourou,Abdelhak Boulaalam

Journal

PeerJ Computer Science

Published Date

2021/12/1

Relevant node discovery and selection approach for the Internet of Things based on neural networks and ant colony optimization

The Internet of Things (IoT) brings opportunities to create new services and change how services are sold and consumed. The IoT is overpopulated by a large number of networks, millions of objects and a huge number of services and interactions. Despite this, the nature of IoT networks, such as the heterogeneity of resources, the dynamic topology, and the large number of similar services, makes service discovery a complex task in terms of accuracy and the time required. Furthermore, the discovery task can offer a set of providers for a given request, so selection of the most relevant provider node must take into account the available resources, such as the power energy and the period of time. In this paper, to overcome these limitations, we propose an approach for service discovery and selection in the IoT. The discovery phase is performed by an edge server using a neural network. The selection phase is …

Authors

Abderrahim Zannou,Abdelhak Boulaalam

Journal

Pervasive and Mobile Computing

Published Date

2021/1/1

Intelligent Mechanisms for Node Search and Task Offloading in the Internet of Things Networks

The Internet of Things (IoT) is a new paradigm of a global network of things. It makes everything and everyone connected and interacted from anywhere, at any time, and using any path and network. IoT nodes can generate enormous amounts of data, perform certain analyses, and make decisions to provide efficient and smart services. Furthermore, a new communication mechanism among nodes is adopted, named Social Internet of Things (SIoT), where the objects can create relationships as human beings do to provide or consume a given service.However, building a searching mechanism for the large number nodes and services makes the space of interest immense and the available solutions diversified, which increases the time required and decreases the accuracy. Furthermore, the IoT networks are characterized by the constrained nodes and the heterogeneity of resources such as energy consumption, storage capacity, processing capacity; therefore, searching the IoT nodes that provide services responding to the request requirements without considering these constraints can lead to decrease the IoT network lifetime. The problem of node search in IoT networks is the discovery and selection of services considering the constraints of IoT nodes and networks. In this thesis, we have proposed three contributions. In the first one, we proposed an approach for service discovery and selection in the IoT. The discovery phase is performed by an edge server using a neural network. The selection phase is performed by nodes to select the adequate node from the set of relevant nodes using Ant Colony Optimization (ACO). The simulation results …

Authors

Zannou Abderrahim

Published Date

2021/7/12

Incorporating LDA with LSTM for followee recommendation on Twitter network

PurposeThe purpose of this study is to facilitate the task of finding appropriate information to read about, and searching for people who are in the same field of interest. Knowing that more people keep up with new streaming information on Twitter micro-blogging service. With the immense number of micro-posts shared via the follower/followee network graph, Twitter users find themselves in front of millions of tweets, which makes the task crucial.

Authors

Brahim Dib,Fahd Kalloubi,Abdelhak Boulaalam

Journal

International Journal of Web Information Systems

Published Date

2021/6/14

Artificial Intelligence Systems and the Internet of Things in the Digital Era: Proceedings of EAMMIS 2021

This book brings together intelligence systems and the Internet of Things, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations which will help societies (economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, and students) to better understand, use, and control AI and IoT to develop future strategies and to achieve sustainability goals. EAMMIS 2021 was organized by the Bridges Foundation in cooperation with the Istanbul Medeniyet University, Istanbul, Turkey, on March 19–20, 2021. EAMMIS 2021 theme was Artificial Intelligence Systems and the Internet of Things in the digital era. The papers presented at the conference provide a holistic view of AI education, MIS, cybersecurity, blockchain, Internet of Ideas (IoI), and knowledge management.

Authors

Abdalmuttaleb MA Musleh Al-Sartawi,Anjum Razzaque,Muhammad Mustafa Kamal

Published Date

2021/5/28

Embedded Systems and Artificial Intelligence: Proceedings of ESAI 2019, Fez, Morocco

This book gathers selected research papers presented at the First International Conference on Embedded Systems and Artificial Intelligence (ESAI 2019), held at Sidi Mohamed Ben Abdellah University, Fez, Morocco, on 2–3 May 2019. Highlighting the latest innovations in Computer Science, Artificial Intelligence, Information Technologies, and Embedded Systems, the respective papers will encourage and inspire researchers, industry professionals, and policymakers to put these methods into practice.

Authors

Hassan SATORI Bhateja,Vikrant

Published Date

2020

Services search techniques architecture for the Internet of Things

As we are moving towards the Internet of Things (IoT) with web services and cloud computing, we will have thousands of connected sensors and their data to handle and benefit from their services. With the enormous number of sensors available in the IoT environment, effectively and efficiently searching and selecting the best sensors regarding the user’s requirement has recently become a crucial challenge. In this paper, we propose an effective context-aware method to cluster sensors in three categories in the form of the Semantic category (SC). Firstly, sensors of each SC are grouped based on their type to create Semantic Type Sensor Network (SSTN), in which sensors with similar context information are gathered into one cluster.

Authors

Soukaina Bouarourou,Abdelhak Boulaalam,El Habib Nfaoui

Published Date

2020

Product identification of Handicrafts product using Mobile Radio Frequency Identification (RFID) and Near Field Communication (NFC)

In this paper we present an approach to guarantee the authenticity and identity of Handicraft Product by using specific types of sensors such as Radio Frequency Identification (RFID) and Near Field Communication (NFC) technology to track the product from the factory to the stores with the objective of protecting Handicraft product brand in Morocco. In this research an effective method is proposed to identify the authenticity status through a smart system based on Internet of things (IoT).

Authors

Youssef Aounzou,Abdelhak Boulaalam

Published Date

2020/12/1

INTELLIGENT PRODUCT LIFECYCLE MANAGEMENT THROUGH THE INTERNET OF THINGS VISION

INTELLIGENT PRODUCT LIFECYCLE MANAGEMENT THROUGH THE INTERNET OF THINGS VISION Catalogue des thèses Marocaine en cour INTELLIGENT PRODUCT LIFECYCLE MANAGEMENT THROUGH THE INTERNET OF THINGS VISION Le Catalogue Collectif des Thèses en Afrique Se connecter Le Catalogue Marocain des Thèses En Cours → Université Sidi Mohammed Ben Abdellah - Fès → CEDoc - Sciences et Techniques de l’Ingénieur → Voir la Thèse INTELLIGENT PRODUCT LIFECYCLE MANAGEMENT THROUGH THE INTERNET OF THINGS VISION BOUCHAREB ASMAE URI: http://otrohati.imist.ma/handle/123456789/60648 Date: 2019-11-30 Discipline: Ingénierie, Systèmes et Applications Centre d'Etudes Doctorales (CED): Faculté des Sciences et Techniques, Fès Encadrant: ABDELHAK BOULAALAM Fichiers dans ce document Fichiers Taille Format Voir Il n'ya pas de fichiers associés …

Authors

BOUCHAREB ASMAE

Published Date

2020/3/21

SMART ARTISANAL ECOSYSTEM BASED ON ARTIFICIAL INTELLIGENCE AND INTERNET OF THINGS

SMART ARTISANAL ECOSYSTEM BASED ON ARTIFICIAL INTELLIGENCE AND INTERNET OF THINGS Catalogue des thèses Marocaine en cour SMART ARTISANAL ECOSYSTEM BASED ON ARTIFICIAL INTELLIGENCE AND INTERNET OF THINGS Le Catalogue Collectif des Thèses en Afrique Se connecter Le Catalogue Marocain des Thèses En Cours → Université Sidi Mohammed Ben Abdellah - Fès → CEDoc - Sciences et Techniques de l’Ingénieur → Voir la Thèse SMART ARTISANAL ECOSYSTEM BASED ON ARTIFICIAL INTELLIGENCE AND INTERNET OF THINGS AOUNZOU YOUSSEF URI: http://otrohati.imist.ma/handle/123456789/60598 Date: 2019-11-30 Discipline: Ingénierie, Systèmes et Applications Centre d'Etudes Doctorales (CED): Faculté des Sciences et Techniques, Fès Encadrant: ABDELHAK BOULAALAM Fichiers dans ce document Fichiers Taille Format Voir Il n'ya pas de fichiers …

Authors

AOUNZOU YOUSSEF

Published Date

2020/3/20

Overview on SDN and NFV based architectures for IoT environments: Challenges and solutions

The Internet of Things (IoT) is a novel paradigm that ensures connections between the real and virtual world. Generally, connected things form the real world where components are equipped with wireless interfaces. Accordingly, a huge number of smart devices can interact and communicate directly or through a network infrastructure. As a result, a big amount of data will be generated. However, IoT based networks are not adapted to support data management. Thus, a new architecture design seems to be an efficient solution to deal with the fast growth of data in an IoT environment. In this sens, Software-Defined Networking (SDN) and Network Function Virtualization (NFV) are two techniques which can help to overcome these IoT challenges. The first one enables centralized control of the network. The second one separates the software and hardware of the network function. This paper gives an overview of SDN …

Authors

Manare Zerifi,Abdellatif Ezzouhairi,Abdelhak Boulaalam

Published Date

2020/10/21

Design of a Tourism Recommendation System Based on User’s Profile

The growing tourism sector encourages the development of a system that can assist tourists in finding the best tourist attractions. The system that is being popularly developed in tourism is the recommendation system. It provides recommendations for tourist attractions based on several parameters. One of the parameters that can help in developing a recommender system is tourist satisfaction. Tourist satisfaction can be known by sentiment analysis on reviews on social media or tourism sites. One way of sentiment analysis is using machine learning. However, machine learning requires quite a lot of data labeled for learning. This process takes a lot of time, especially for a large amount of data, so the idea arose to use a lexicon dictionary. In this study, we tested two Indonesian datasets with four classifiers SVM, Random Forest, KNN, and LSTM. Its classifiers will combine with lexicon corpus, BOW (Bag of Words), and …

Authors

Elan Lubihana

Published Date

2022/11/8

Siot: A new strategy to improve the network lifetime with an efficient search process

The Social Internet of Things (SIoT) means that every node can use a set of nodes that are considered as friends to search for a specific service. However, this is a slow process because each node is required to manage a high number of friends. Thus, the SIoT issue consists of how to select the right friends that improve the network navigability. The enhancement of the network navigability boosts the search for a service to be rapid but not guaranteed. Furthermore, sending requests from the shortest paths involves the rapid search, but the network lifetime can be reduced due to the number of requests that can be transmitted and processed by the nodes that have low power energy. This paper proposes a new approach that improves the network navigability, speeds up the search process, and increases the network lifetime. This approach aims at creating groups dynamically by nodes where each group has a master node, second, using a consensus algorithm between master nodes to agree with a specific capability, finally adopting a friendship selection method to create a social network. Thus, the friends will be sorted periodically for the objective of creating simultaneously a balance between the energy consumption and the rapid search process. Simulation results on the Brightkite location-based online social network dataset demonstrate that our proposal outperforms baseline methods in terms of some parameters of network navigability, path length to reach the providers, and network lifetime.

Authors

Abderrahim Zannou,Abdelhak Boulaalam,El Habib Nfaoui

Journal

Future Internet

Published Date

2020/12/29

A node capability classification in internet of things

The Internet of Things (IoT) is an advanced paradigm of the Internet, it makes everything and everyone to be connected and interacted from anywhere, at any time, and using any path and network. This new paradigm is characterized by constraint nodes and lossy networks where the available resources are limited and the network structure is unstable. The random execution of requests can lead to the failure of some nodes, as a consequence, the network lifetime will be reduced. In this paper, we proposed a new strategy to classify the nodes into three levels based on their capabilities and using a neural network. The classification allows the nodes to be aware of the best nodes that can execute or process a given service or a task, by predicting the capability of a joined node in the lossy network. The simulation results show that our proposed model has a high accuracy for prediction nodes and makes the network …

Authors

Abderrahim Zannou,Abdelhak Boulaalam

Published Date

2020/6/9

Expedient and Non-expedient Nodes in the Internet of Things

The Internet of Things (IoT) is a network where every object and everything can be transformed into an intelligent device and an efficient element in communication. The IoT is categorized by constraint networks which are interconnected by lossy links, support low data rates, and include mobile nodes. Therefore, the constructed nodes have insufficient power energy, limited storage, and limited processing. On another side, a node is surrounded by a set of constraint nodes that are used as transmitters or executors of the incoming requests, in which the random choice of those nodes leads to the failure of the constraint networks. To overcome these limitations, we classify the nodes into expedient and non-expedient types, using a neural network algorithm to get the prediction model. The training phase of the model is performed by a high node capability or by a server, then the obtained model is sent to the nodes for …

Authors

Abderrahim Zannou,Abdelhak Boulaalam,El Habib Nfaoui

Published Date

2020/12/21

Advanced Intelligent Systems for Sustainable Development (AI2SD'2019)

The purpose of this volume is to honour myself and all colleagues around the world that we have been able to collaborate closely for extensive research contributions which have enriched the field of Applied Computer Science. Applied Computer Science presents a appropriate research approach for developing a high-level skill that will encourage various researchers with relevant topics from a variety of disciplines, encourage their natural creativity, and prepare them for independent research projects. We think this volume is a testament to the benefits and future possibilities of this kind of collaboration, the framework for which has been put in place. v

Authors

Mostafa Ezziyyani,Ditzinger,Ezziyyani

Published Date

2020

Leveraging topic feature for followee recommendation on Twitter network

With the fast growth of the Twitter network, users are overwhelmed by the huge amount of information, which is shared via the follower/followee social network, to overcome this problem, finding like-minded users becomes a very important task. Thus, a system to assist users in such a task is recommended. In this paper, we propose a followee recommendation system by leveraging the topic feature, for topic modeling, and the follower/followee topology, searching for similar users to recommend, based on topic similarities. To show the effectiveness of our approach, we evaluate it using a dataset in gathered from the Twitter platform. The experiment results indicate that our model outperforms the lexical-based [reference?] approach and semantic-based approach [reference?], achieving a recall value of more than 23% on recommending 10 followees, proving that dealing with users' topics of interest in microblogging …

Authors

Brahim Dib,Fahd Kalloubi,Abdelhak BOULAALAM

Published Date

2020/6/9

System service provider–customer for IoT (SSPC-IoT)

Internet of things (IoT) is a new promising paradigm based on the interconnection of heterogeneous objects, which aims to provide specific services anywhere, anytime by anything and anyone. IoT systems include different devices and use different protocols and technologies. Whereas IoT is now a reality, many IoT challenges are not resolved such as horizontal silos, defined level communication services in the case of constraint things, trust object services, etc. Some IoT architectures for global communication are proposed for resolving those challenges, but they are deployed on specific applications for resolving some constraints such as power energy, capacity of calculation, etc. This paper proposes a System Service Provider–Customer (SSPC) to manage and control communication of things and related services in IoT systems. SSPC is a system that consists of discovering services by considering constraints of …

Authors

Abderrahim Zannou,Abdelhak Boulaalam,El Habib Nfaoui

Published Date

2020

Path length optimization in heterogeneous network for internet of things

The internet of things (IoT) is composed of a significant portion of constrained nodes, which are limited in terms of power energy, computation capacity, storage, and stability links. As a result, data collection and dissemination for IoT, especially in wireless sensor networks (WSN), requiring sufficient energy and a minimum number of hops from a source node to sink or to another node with a short period of time. To deal with these limitations, we propose a lightweight algorithm, where a cluster head (CH) is selected among the IoT devices of WSN to maintain a reliable network with efficient data transmission, and then the communication is performed among CHs to distribute the routing information, thus the transmission of data and requests lanced by nodes and users to respond of the given requirements. The simulation results show that our proposed algorithm increases the network lifetime and minimizes the number …

Authors

Abderrahim Zannou,Abdelhak Boulaalam

Published Date

2020/12/2

See List of Professors in Abdelhak Boulaalam University(Université Sidi Mohamed Ben Abdellah)

Abdelhak Boulaalam FAQs

What is Abdelhak Boulaalam's h-index at Université Sidi Mohamed Ben Abdellah?

The h-index of Abdelhak Boulaalam has been 10 since 2020 and 10 in total.

What are Abdelhak Boulaalam's top articles?

The articles with the titles of

An efficient model-based clustering via joint multiple sink placement for WSNs

Data Gathering from IoT Networks

IoT-Based Intelligent Handicraft System Using NFC Technology

Toward an IoT-Based System to Ensure Product Identification of Moroccan Handicrafts

Iot based smart agriculture monitoring system with predictive analysis

Data Flow Optimization in the Internet of Things

Sensors Deployment in IoT Environment

Query Processing in IoT Based on Spatial and Temporal Information

...

are the top articles of Abdelhak Boulaalam at Université Sidi Mohamed Ben Abdellah.

What are Abdelhak Boulaalam's research interests?

The research interests of Abdelhak Boulaalam are: Computer science, Internet of Things, Intelligent Product, PLM

What is Abdelhak Boulaalam's total number of citations?

Abdelhak Boulaalam has 272 citations in total.

What are the co-authors of Abdelhak Boulaalam?

The co-authors of Abdelhak Boulaalam are El Habib Nfaoui, OMAR EL BEQQALI, ABDERRAHIM ZANNOU.

    Co-Authors

    H-index: 13
    El Habib Nfaoui

    El Habib Nfaoui

    Université Sidi Mohamed Ben Abdellah

    H-index: 10
    OMAR EL BEQQALI

    OMAR EL BEQQALI

    Université Sidi Mohamed Ben Abdellah

    H-index: 8
    ABDERRAHIM ZANNOU

    ABDERRAHIM ZANNOU

    Université Sidi Mohamed Ben Abdellah

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