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121 results on '"Abdou, Wahabou"'

4. Reduction of Data Transmission in an IoT Wireless Sensor Network

Author

Njoya, Arouna Ndam, Salifu, Amina, Djedouboum, Assidé Christian, Tchangmena, Allassan A. Nken, Ari, Ado Adamou Abba, Adouane, Amine Mohamed, Abdou, Wahabou, Gueroui, Abdelhak Mourad, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Ngatched Nkouatchah, Telex Magloire, editor, Woungang, Isaac, editor, Tapamo, Jules-Raymond, editor, and Viriri, Serestina, editor

Published
2023
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5. Reinforcement Learning-Based Dynamic Path Allocation in IoT Systems

Author

Njoya, Arouna Ndam, Yefou, Uriel Nguefack, Ari, Ado Adamou Abba, Rockefeller, Djedouboum, Assidé Christian, Abdou, Wahabou, Thiare, Ousmane, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Ngatched Nkouatchah, Telex Magloire, editor, Woungang, Isaac, editor, Tapamo, Jules-Raymond, editor, and Viriri, Serestina, editor

Published
2023
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6. Leader Election And Local Identifiers For 3D Programmable Matter

Author

Gastineau, Nicolas, Abdou, Wahabou, Mbarek, Nader, and Togni, Olivier

Subjects
Computer Science - Discrete Mathematics, Computer Science - Data Structures and Algorithms, Computer Science - Networking and Internet Architecture
Abstract

In this paper, we present two deterministic leader election algorithms for programmable matter on the face-centered cubic grid. The face-centered cubic grid is a 3-dimensional 12-regular infinite grid that represents an optimal way to pack spheres (i.e., spherical particles or modules in the context of the programmable matter) in the 3-dimensional space. While the first leader election algorithm requires a strong hypothesis about the initial configuration of the particles and no hypothesis on the system configurations that the particles are forming, the second one requires fewer hypothesis about the initial configuration of the particles but does not work for all possible particles' arrangement. We also describe a way to compute and assign-local identifiers to the particles in this grid with a memory space not dependent on the number of particles. A-local identifier is a variable assigned to each particle in such a way that particles at distance at most each have a different identifier.

Published
2020

7. Application of LSTM architectures for next frame forecasting in Sentinel-1 images time series

Author

Moskolaï, Waytehad, Abdou, Wahabou, Dipanda, Albert, and Kolyang, Dina Taiwe

Subjects
Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

L'analyse pr{\'e}dictive permet d'estimer les tendances des {\'e}v{\`e}nements futurs. De nos jours, les algorithmes Deep Learning permettent de faire de bonnes pr{\'e}dictions. Cependant, pour chaque type de probl{\`e}me donn{\'e}, il est n{\'e}cessaire de choisir l'architecture optimale. Dans cet article, les mod{\`e}les Stack-LSTM, CNN-LSTM et ConvLSTM sont appliqu{\'e}s {\`a} une s{\'e}rie temporelle d'images radar sentinel-1, le but {\'e}tant de pr{\'e}dire la prochaine occurrence dans une s{\'e}quence. Les r{\'e}sultats exp{\'e}rimentaux {\'e}valu{\'e}s {\`a} l'aide des indicateurs de performance tels que le RMSE et le MAE, le temps de traitement et l'index de similarit{\'e} SSIM, montrent que chacune des trois architectures peut produire de bons r{\'e}sultats en fonction des param{\`e}tres utilis{\'e}s.

Published
2020

8. Distributed leader election and computation of local identifiers for programmable matter

Author

Gastineau, Nicolas, Abdou, Wahabou, Mbarek, Nader, and Togni, Olivier

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Discrete Mathematics, Computer Science - Data Structures and Algorithms, Computer Science - Networking and Internet Architecture
Abstract

The context of this paper is programmable matter, which consists of a set of computational elements, called particles, in an infinite graph. The considered infinite graphs are the square, triangular and king grids. Each particle occupies one vertex, can communicate with the adjacent particles, has the same clockwise direction and knows the local positions of neighborhood particles. Under these assumptions, we describe a new leader election algorithm affecting a variable to the particles, called the k-local identifier, in such a way that particles at close distance have each a different k-local identifier. For all the presented algorithms, the particles only need a O(1)-memory space.

Published
2018

9. Priority Levels Based Multi-hop Broadcasting Method for Vehicular Ad hoc Networks

Author

Abdou, Wahabou, Darties, Benoit, and Mbarek, Nader

Subjects
Computer Science - Networking and Internet Architecture
Abstract

This paper deals with broadcasting problem in vehicular ad hoc networks (VANETs). This communication mode is commonly used for sending safety messages and traffic information. However, designing an efficient broadcasting protocol is hard to achieve since it has to take into account some parameters related to the network environment, for example, the network density, in order to avoid causing radio interferences. In this paper, we propose a novel Autonomic Dissemination Method (ADM) which delivers messages in accordance with given priority and density levels. The proposed approach is based on two steps: an offline optimization process and an adaptation to the network characteristics. The first step uses a genetic algorithm to find solutions that fit the network context. The second one relies on the Autonomic Computing paradigm. ADM allows each vehicle to dynamically adapt its broadcasting strategy not only with respect to the network density, but also in accordance to the priority level of the message to send. The experimental results show that ADM effectively uses the radio resources even when there are globally many messages to send simultaneously. Moreover, ADM allows to increase the message delivery ratio and to reduce the latency and radio interferences.

Published
2017
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10. Transmission of Genetic Properties in Permutation Problems: Study of Lehmer Code and Inversion Table Encoding

Author

Khalil, Carine, Abdou, Wahabou, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Rutkowski, Leszek, editor, Scherer, Rafał, editor, Korytkowski, Marcin, editor, Pedrycz, Witold, editor, Tadeusiewicz, Ryszard, editor, and Zurada, Jacek M., editor

Published
2021
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12. Trade-Off Between Diversity and Convergence in Multi-objective Genetic Algorithms

Author

Abdou, Wahabou, Bloch, Christelle, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Adjallah, Kondo H., editor, Birregah, Babiga, editor, and Abanda, Henry Fonbeyin, editor

Published
2020
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13. Improving Coverage Area in Sensor Deployment Using Genetic Algorithm

Author

Tossa, Frantz, Abdou, Wahabou, Ezin, Eugène C., Gouton, Pierre, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Krzhizhanovskaya, Valeria V., editor, Závodszky, Gábor, editor, Lees, Michael H., editor, Dongarra, Jack J., editor, Sloot, Peter M. A., editor, Brissos, Sérgio, editor, and Teixeira, João, editor

Published
2020
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14. Behaviour Study of an Evolutionary Design for Permutation Problems

Author

Ali, Hind Mohammed, Bloch, Christelle, Abdou, Wahabou, Chatonnay, Pascal, Spies, François, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Yang, Xin-She, editor, Sherratt, Simon, editor, Dey, Nilanjan, editor, and Joshi, Amit, editor

Published
2019
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15. Distributed Leader Election and Computation of Local Identifiers for Programmable Matter

Author

Gastineau, Nicolas, Abdou, Wahabou, Mbarek, Nader, Togni, Olivier, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Gilbert, Seth, editor, Hughes, Danny, editor, and Krishnamachari, Bhaskar, editor

Published
2019
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19. Adaptive-Segmentation and Flexible-Delay Based Broadcasting Protocol for VANETs

Author

Hafi, Houda, Abdou, Wahabou, Merniz, Salah, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Koucheryavy, Yevgeni, editor, Mamatas, Lefteris, editor, Matta, Ibrahim, editor, Ometov, Aleksandr, editor, and Papadimitriou, Panagiotis, editor

Published
2017
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22. Broadcasting Information in Variably Dense Environment Using Connectionless Data Exchange (CoLDE)

Author

Abu Oun, Osama, Abdou, Wahabou, Bloch, Christelle, Spies, François, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Mellouk, Abdelhamid, editor, Fowler, Scott, editor, Hoceini, Saïd, editor, and Daachi, Boubaker, editor

Published
2014
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24. A Machine Learning Scheme for Speed Prediction in Intelligent Transportation Systems Using a Bi-LSTM Based Model

Author

Njoya, Arouna Ndam, Wachira, Alice Wangui, Abba Ari, Ado Adamou, Rockefeller, Rockefeller, Gueroui, Abdelhak Mourad, Thron, Christopher, Kallel, Sondes Khemiri, Abdou, Wahabou, and Tonye, Emmanuel

Abstract

Congestion has become a big issue in major cities throughout the world. Numerous transportation activities have been affected, and travel times have increased as a result of many travelers spending lengthy hours on the road. To overcome these challenges, the Intelligent Transportation System (ITS), which provides efficient traffic service and management, has sparked widespread attention. Collection and analysis of traffic data has been made possible by the algorithms implemented by the ITS. Huge volumes of data are produced by the vast wide range of sensors used in the Internet of Things (IoT), enabling the collection of a variety of traffic information. Development of short-term traffic speed prediction, has been made possible using deep learning models such as Long Short Term Memory (LSTM) and Bidirectional LSTM. Numerous variables, including the weather, the state of the roads, and traffic congestion, can have long-term dependencies and influence traffic speed. The bidirectional architecture of Bi-LSTMs enables them to handle long-term dependencies in sequences and efficiently capture both past and future context in a sequence, which is crucial for producing accurate forecasts of traffic speed. In this paper, the upstream and downstream flow of traffic speed on various pathways has been investigated using a traffic path planning algorithm based on Bi-LSTM models. The algorithm considers the factors affecting the flow of traffic at different seasons and time of the day and tries to predict the average speed associated to that path several timeslots ahead. The experimental results demonstrated that the Bi-LSTM model has the benefit of predicting speed for various timeslots while retaining a high level of accuracy.

Published
2023
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26. Designing Smart Adaptive Flooding in MANET Using Evolutionary Algorithm

Author

Abdou, Wahabou, Bloch, Christelle, Charlet, Damien, Dhoutaut, Dominique, Spies, François, Akan, Ozgur, Series editor, Bellavista, Paolo, Series editor, Cao, Jiannong, Series editor, Dressler, Falko, Series editor, Ferrari, Domenico, Series editor, Gerla, Mario, Series editor, Kobayashi, Hisashi, Series editor, Palazzo, Sergio, Series editor, Sahni, Sartaj, Series editor, Shen, Xuemin (Sherman), Series editor, Stan, Mircea, Series editor, Xiaohua, Jia, Series editor, Zomaya, Albert, Series editor, Coulson, Geoffrey, Series editor, Venkatasubramanian, Nalini, editor, Getov, Vladimir, editor, and Steglich, Stephan, editor

Published
2012
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27. Multi-Pareto-Ranking Evolutionary Algorithm

Author

Abdou, Wahabou, Bloch, Christelle, Charlet, Damien, Spies, François, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Hao, Jin-Kao, editor, and Middendorf, Martin, editor

Published
2012
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37. A Workflow for Collecting and Preprocessing Sentinel-1 Images for Time Series Prediction Suitable for Deep Learning Algorithms.

Author

Moskolaï, Waytehad Rose, Abdou, Wahabou, Dipanda, Albert, and Kolyang

Subjects
DEEP learning, REMOTE-sensing images, TIME series analysis, IMAGE processing, ENVIRONMENTAL management
Abstract

The satellite image time series are used for several applications such as predictive analysis. New techniques such as deep learning (DL) algorithms generally require long sequences of data to perform well; however, the complexity of satellite image preprocessing tasks leads to a lack of preprocessed datasets. Moreover, using conventional collection and preprocessing methods is time- and storage-consuming. In this paper, a workflow for collecting, preprocessing, and preparing Sentinel-1 images to use with DL algorithms is proposed. The process mainly consists of using scripts for collecting and preprocessing operations. The goal of this work is not only to provide the community with easily modifiable programs for image collection and batch preprocessing but also to publish a database with prepared images. The experimental results allowed the researchers to build three time series of Sentinel-1 images corresponding to three study areas, namely the Bouba Ndjida National Park, the Dja Biosphere Reserve, and the Wildlife Reserve of Togodo. A total of 628 images were processed using scripts based on the SNAP graph processing tool (GPT). In order to test the effectiveness of the proposed methodology, three DL models were trained with the Bouba Ndjida and Togodo images for the prediction of the next occurrence in a sequence. [ABSTRACT FROM AUTHOR]

Published
2022
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41. A multi-objective evolutionary scheme for control points deployment in intelligent transportation systems

Author

Mfenjou, Martin Luther, ABBA ARI, Ado Adamou, Njoya, Arouna Ndam, Abdou, Wahabou, Gueroui, Abdelhak Mourad, Laboratoire d'Informatique Parallélisme Réseaux Algorithmes Distribués (LI-PaRAD), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Université de Bourgogne (UB)

Subjects
Deployment, Performance evaluation, ComputingMilieux_LEGALASPECTSOFCOMPUTING, Control points, Multi-objective evolutionary, Intelligent transportation system, Roadway network, Algorithms, [SPI.TRON]Engineering Sciences [physics]/Electronics
Abstract

International audience; One of the problems that hinder emergency in developing countries is the problem of monitoring a number of activities on inter-urban roadway networks. In the literature, the use of control points is proposed in the context of these countries in order to ensure efficient monitoring, by ensuring a good coverage while minimizing the installation costs as well as the number of accidents across these road networks. In this work, we propose an optimal deployment of these control points from several optimization methods based on some evolutionary multi-objective algorithms: the Non dominated sorting genetic algorithm-II (NSGA-II); the multi-objective particle swarm optimization (MOPSO); the strength pareto evolutionary algorithm-II (SPEA-II); and the pareto envelope based selection algorithm-II (PESA-II). We performed the tests and compared these deployments using pareto front and performance indicators like the spread and hypervolume and the inverted generational distance (IGD). The results obtained show that the NSGA-II method is the most adequate in the deployment of these control points.

Published
2021

45. Leader election and local identifiers for three‐dimensional programmable matter.

Author

Gastineau, Nicolas, Abdou, Wahabou, Mbarek, Nader, and Togni, Olivier

Subjects
LOCAL elections, SPHERE packings, ELECTIONS, PACKING problem (Mathematics)
Abstract

Summary: In this article, we present two deterministic leader election algorithms for programmable matter on the face‐centered cubic grid. The face‐centered cubic grid is a three‐dimensional 12‐regular infinite grid that represents an optimal way to pack spheres (i.e., spherical particles or modules in the context of the programmable matter) in the three‐dimensional space. While the first leader election algorithm requires a strong hypothesis about the initial configuration of the particles and no hypothesis on the system configurations that the particles are forming, the second one requires fewer hypothesis about the initial configuration of the particles but does not work for all possible particles' arrangement. We also describe a way to compute and assign ℓ‐local identifiers to the particles in this grid with a memory space not dependent on the number of particles. A ℓ‐local identifier is a variable assigned to each particle in such a way that particles at distance at most ℓ each have a different identifier. [ABSTRACT FROM AUTHOR]

Published
2022
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50. Control points deployment in an Intelligent Transportation System for monitoring inter-urban network roadway.

Author

Mfenjou, Martin Luther, Ari, Ado Adamou Abba, Njoya, Arouna Ndam, Mbogne, David Jaures Fotsa, Kolyang, Abdou, Wahabou, and Spies, François

Subjects
INTELLIGENT transportation systems, DEVELOPING countries, GENETIC algorithms, ROAD safety measures
Abstract

The constant evolution of transportation systems and traffic in developing countries is nowadays confronted with a problem of road safety and therefore of a high accident rate, especially in the context of inter-urban road transport. In this work, we propose a communication architecture for an Intelligent Transport System (ITS) to provide surveillance in an inter-urban transport network in the context of developing countries. We introduce two types of control points: Relay Control Points (RCP) and Treatment Control Points (TrCP). We also designed two multi-objective models for the deployment of these points. In order to ensure good coverage, to minimize the cost of installation and to put more emphasis in the areas having a high number of accidents. To ensure optimal deployment of these points, we have used the Non-Dominated Sorted Genetic Algorithm II (NSGA-II) that will allow to realize the Pareto front of non-dominated solutions. The results of the simulations show the effectiveness of our proposal. [ABSTRACT FROM AUTHOR]

Published
2022
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