0000000000181907
AUTHOR
Mohamed Ayoub Messous
showing 8 related works from this author
Toward a lightweight and efficient UAV‐aided VANET
2019
International audience; Connectivity in a smart vehicular network is quite sensitive and highly affected by its dynamic network topology. Issues related to the intermittent nature of connectivity may arise due to the high mobility of nodes and network heterogeneity. In sparse areas, a vehicular network is basically a disruption‐tolerant network suffering from frequent disconnections, long delays, and messages loss. Facing these issues, and specifically for time‐sensitive applications, Unmanned Aerial Vehicle (UAV) can provide valuable assistance to Vehicular Ad Hoc Network (VANET) by assuming a relay node role between disconnected segments in the road. In such scenarios, effective communica…
Network Connectivity and Area Coverage for UAV Fleet Mobility Model with Energy Constraint
2016
International audience; Our main focus through the present paper is on developing an original distributed mobility model for autonomous fleet of interconnected UAVs (Unmanned Aerial Vehicles) performing an area exploration mission. The UAVs, equipped with wireless ad-hoc capabilities, are required to optimally explore an area while maintaining connectivity with their neighboring UAVs and the base station. Because energy is a scarce resource, especially for UAVs, its wise management is quite beneficial for the network lifetime and mission success. Hence, the proposed mobility model, compared to other models in the literature, is the first to ever include the remaining energy level as decisio…
Multi-agent control architecture for RFID cyberphysical robotic systems initial validation of tagged objects detection and identification using Playe…
2016
International audience; The objective of this paper is to describe and validate a multi-agent architecture proposed to control RFID Cyber-Physical Robotic Systems. This environment may contain human operators, robots (mobiles, manipulators, mobile manipulators, etc.), places (workrooms, walls, etc.) and other objects (tables, chairs, etc.). The proposed control architecture is composed of two types of agents dispatched on two levels. We find at the Organization level a Supervisory agent to allow operators to configure, manage and interact with the overall control system. At the Control level, we distinguish the Robots agents, to each robot (mobiles, manipulators or mobile manipulators) is a…
Theoretical Game Approach for Mobile Users Resource Management in a Vehicular Fog Computing Environment
2018
Vehicular Cloud Computing (VCC) is envisioned as a promising approach to increase computation capabilities of vehicle devices for emerging resource-hungry mobile applications. In this paper, we introduce the new concept of Vehicular Fog Computing (VFC). The Fog Computing (FC) paradigm evolved and is employed to enhance the quality of cloud computing services by extending it to the edge of the network using one or more collaborative end-user clients or near-user edge devices. The VFC is similar to the VCC concept but uses vehicles resources located at the edge of the network in order to serve only local on-demand mobile applications. The aim of this paper is to resolve the problem of admissi…
Decentralized Lightweight Group Key Management for Dynamic Access Control in IoT Environments
2020
Rapid growth of Internet of Things (IoT) devices dealing with sensitive data has led to the emergence of new access control technologies in order to maintain this data safe from unauthorized use. In particular, a dynamic IoT environment, characterized by a high signaling overhead caused by subscribers' mobility, presents a significant concern to ensure secure data distribution to legitimate subscribers. Hence, for such dynamic environments, group key management (GKM) represents the fundamental mechanism for managing the dissemination of keys for access control and secure data distribution. However, existing access control schemes based on GKM and dedicated to IoT are mainly based on ce…
How to prevent cyber-attacks in inter-vehicle communication network?
2015
In this work, we aim to secure communication in a vehicular network by providing a proactive mechanism that can detect and predict with a high accuracy the future behavior of malicious attacker. In fact, the mechanisms proposed in the literature consider only detection mechanisms and do not prevent attacks that may arise in the network. Simulation results show that our mechanism has a high detection rate, low false positive rate while generating a low communication overhead.
A Sequential Game Approach for Computation-Offloading in an UAV Network
2017
International audience; Small drones are currently emerging as versatile nascent technology that can be used in exploration and surveillance missions. However, most of the underlying applications require very often complex and time-consuming calculations. Although, the limited resources available onboard the small drones, their mobility, the computation delays and energy consumption make the operation of these applications very challenging. Nevertheless, computation-offloading solutions provide feasible resolves to mitigate the issues facing these constrained devices. In this context, we address in this paper the problem of offloading highly intensive computation tasks, performed by a fleet…
Deep Learning-Based Real-Time Object Detection in Inland Navigation
2019
International audience; Semi-autonomous and fully-autonomous systems must have knowledge about the objects in their environment to ensure a safe navigation. Modern approaches implement deep learning techniques to train a neural network for object detection. This project will study the effectiveness of using several promising algorithms such as Faster R-CNN, SSD, and different versions of YOLO, to detect, classify, and track objects in near real-time fluvial domain. Since no dataset is available for this purpose in literature, we first started by annotating a dataset of 2488 images with almost 35 400 annotations for training the convolutional neural network architectures. We made this data s…