Articles scientifiqueshttp://dspace.univ-msila.dz:8080//xmlui/handle/123456789/2592024-03-29T07:11:21Z2024-03-29T07:11:21ZAgent-Based Simulation of Crowd Evacuation Through Complex SpacesMohamed ChatraMustapha Bourahlahttp://dspace.univ-msila.dz:8080//xmlui/handle/123456789/427162024-03-25T11:56:13Z2023-01-01T00:00:00ZAgent-Based Simulation of Crowd Evacuation Through Complex Spaces
Mohamed Chatra; Mustapha Bourahla
In this paper, we have developed a description of an agent-based model for simulating the
evacuation of crowds from complex physical spaces for escaping dangerous situations. The
model describes a physical space containing a set of differently shaped fences, and
obstacles, and an exit door. The pedestrians comprising the crowd and moving in this space
in order to be evacuated are described as intelligent agents with supervised machine learning
using perception-based data to perceive a particular environment differently. The
description of this model is developed with the Python language where its execution
represents its simulation. Before the simulation, the model can be validated using an
animation written with the same language to fix possible problems in the model description.
A model performance evaluation is presented using an analysis of simulation results,
showing that these results are very encouraging
2023-01-01T00:00:00ZFast approach for link prediction in complex networks based on graph decompositionAbdelhamid SaifFarid NouiouaSamir Akhroufhttp://dspace.univ-msila.dz:8080//xmlui/handle/123456789/422862024-02-11T12:23:06Z2023-01-01T00:00:00ZFast approach for link prediction in complex networks based on graph decomposition
Abdelhamid Saif; Farid Nouioua; Samir Akhrouf
Social networks such as Facebook, Twitter, etc. have dramatically increased in recent years. These databases are huge and
their use is time consuming. In this work, we present an optimal calculation in graph mining for link prediction to reduce
the runtime. For that purpose, we propose a novel approach that operates on the connected components of a network instead
of the whole network. We show that thanks to this decomposition, the results of all link prediction algorithms using local
and path-based similarity measure scan be achieved with much less amount of computations and hence within much shorter
runtime. We show that this gain depends on the distribution of nodes in components and may be captured by the Gini and
the variance measures. We propose a parallel architecture of the link prediction process based on the connected components
decomposition. To validate this architecture, we have carried out an experimental study on a wide range of well-known
datasets. The obtained results clearly confrm the efciency of exploiting the decomposition of the network into connected
components in link prediction
2023-01-01T00:00:00ZA scalable time-division-based emergency messages broadcast scheme for connected and autonomous vehicles in urban environmentSalah GuesmiaFouzi SemchedineSoufiene Djahelhttp://dspace.univ-msila.dz:8080//xmlui/handle/123456789/401032023-07-09T09:39:00Z2022-01-01T00:00:00ZA scalable time-division-based emergency messages broadcast scheme for connected and autonomous vehicles in urban environment
Salah Guesmia; Fouzi Semchedine; Soufiene Djahel
Connected and Autonomous Vehicles (CAVs) technology promises to revolutionize the transportation
sector by solving many safety and traffic efficiency challenges while significantly enhancing passengers’
and drivers’ comfort. Most of these applications are built upon multi-hop broadcast of information
among vehicles, leading to an increased contention and thus higher collision probability due to the
limited bandwidth available for vehicular communications. In this paper, we propose a novel TimeDivision-based Broadcast (TDB) scheme to mitigate interferences originating from hidden nodes (i.e.,
vehicles) to meet the stringent safety applications requirements. Then, we use this broadcast scheme
as a basis for designing a new efficient and scalable protocol for emergency messages dissemination in
urban vehicular networks (UV-TDB: an Urban, Vehicular and Time-Division-based Broadcast protocol). The
simulation experiments show that UV-TDB significantly improves the performance of multi-hop broadcast
and outperforms two state of the art protocols in terms of the achieved reduction in broadcast overhead
(up to 77.9%), packet collisions ratio (up to 93.5%), interference rate (up to 43.5%) and increase in message
reception rate (up to 337.7%). The results highlight also that UV-TDB adapts better to varying levels of
vehicle density, making it more scalable
2022-01-01T00:00:00ZComputers and Electrical EngineeringBoubakeur MoussaouiNoureddine ChikoucheHacène Fouchalhttp://dspace.univ-msila.dz:8080//xmlui/handle/123456789/400882023-07-09T09:22:40Z2023-01-01T00:00:00ZComputers and Electrical Engineering
Boubakeur Moussaoui; Noureddine Chikouche; Hacène Fouchal
In Cooperative Intelligent Transport Systems (C-ITS), vehicles and Road Side Units (RSU)
exchange various messages about safety, traffic control, and weather conditions. These messages
are broadcast to all neighbors. Each message should be authenticated and should protect
users’ privacy, mainly by hiding their locations. The authentication is achieved by signing
messages using a private key related to the Pseudonym Certificate (PC), provided by a Trusted
Authority (TA). The PC is delivered together with messages so that receivers can authenticate
the messages. Privacy is ensured by changing PCs many times during a journey, so that trackers
cannot get drivers’ traces. This paper proposes a novel approach to manage PC switching
periods between vehicles. The proposed method uses a Common PC (CPC) during a short period
before switching to a new PC. Vehicles use the same shared PC during this period to sign their
messages. Simulations have been conducted in an OMNET++ environment, showing significant
improvement in privacy protection compared to well-known privacy schemes
2023-01-01T00:00:00Z