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In a recent work [1], we proposed LTE4V2X, a novel framework for a centralized vehicular network organization based on 4G LTE network. We demonstrated the efficiency of our framework for an FCD (Floating Car Data) application. Such applications are based on data collected from vehicles (localization, speed, direction, etc.) in order to feed a traffic management server. In the continuity of this work,...
The IEEE 802.11p or Wireless Access in Vehicular Environment (WAVE) has been adopted as a main technology for vehicular ad hoc networks (VANETs). Its Medium Access Control (MAC) protocol is based on the Distributed Coordination Function (DCF) of the IEEE 802.11 which has low performance and high collision rate especially when using a single channel. Therefore, many clustering-based multi-channel MAC...
Due to vehicles high mobility, there have been many clustering-based MAC protocols proposed to control Vehicular Ad hoc Network topology more effectively. Cluster head (CH) selection and cluster formation is of paramount importance in a highly dynamic environment such as VANETs. In this paper, we propose a novel cluster head selection criteria where cluster heads are selected based on their relative...
Due to the size and density of small satellite networks (SSNs), the traditional clustering algorithms of large monolithic satellite networks are often limited. This paper proposes a novel distributed weight-based dominating set clustering algorithm to address the clustering problems in the stochastically deployed SSNs. Considering the unique features of small satellites, this algorithm is able to...
In this paper, we present a novel approach to early diagnosis, through a video processing-based approach, of the presence of neonatal seizures. In particular, image processing and gesture recognition techniques are first used to characterize typical gestures of neonatal seizures. More precisely, gesture trajectories are characterized by extracting some relevant features. In particular, selecting the...
This paper considers the Slepian-Wolf coding based energy minimization clustering (SWEMC) problem in a wireless sensor network (WSN), which aims to minimize the amount of data generated within each cluster and the overall energy cost for data transmission in the network. To solve the problem, we propose a Slepian-Wolf coding based energy-efficient clustering (SWEEC) algorithm, which is based on a...
Data gathering is one basic functional operation provided by wireless sensor networks. Most existing clustering protocols suffer from unbalanced energy consumption among nodes, which shortens the lifetime of the network and limits their application in many fields. In this paper, an energy-balanced dominating set based clustering scheme (EBDSC) is proposed to prolong the network lifetime by balancing...
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