0000000000790143

AUTHOR

Sidi-mohamed Senouci

RBCR: a Relay-Based Cooperative Routing Protocol for Cooperative Wireless Sensor Network

International audience; In wireless sensor networks several constraints decrease communications performances. The main objective of this paper is to present a multi-objective routing algorithm RBCR that computes routing path based on the energy consumption and channel qualities. Additionally, the channel qualities are evaluated based on the presence of relay nodes. Compared to AODV and AODV associated to a cooperative MAC protocol, RBCR provides better performances.

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ECAR: an Energy/Channel Aware Routing Protocol For Cooperative Wireless Sensor Networks

International audience; The proliferation of low power networks like Wireless Sensor Networks (WSN) rose up new challenges. Power conservation and channel quality become the most important parameters. Obviously, hop count based routing protocols are no more adapted to such networks having power limitations and channel problems. Several alternatives were suggested to cope with these constraints. In MAC layer for example, cooperative protocols were designed to enhance the channel use: the neighbor nodes help the source to retransmit its packets. However, if the path proposed by the routing protocol contains poor channels, the cooperative communications will not save all the packets. Therefore…

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A combined relay-selection and routing protocol for cooperative wireless sensor networks

International audience; In wireless sensor networks several constraints decrease communications performances. In fact, channel randomness and energy restrictions make classical routing protocols inefficient. Therefore, the design of new routing protocols that cope with these constraints become mandatory. The main objective of this paper is to present a multi-objective routing algorithm RBCR that computes routing path based on the energy consumption and channel qualities. Additionally, the channel qualities are evaluated based on the presence of relay nodes. Compared to AODV and AODV associated to a cooperative MAC protocol, RBCR provides better performances in term of delivery ratio, power …

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Deep Learning-Based Real-Time Object Detection in Inland Navigation

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…

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