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Leonard Barolli

Researcher at Fukuoka Institute of Technology

Publications -  1256
Citations -  11175

Leonard Barolli is an academic researcher from Fukuoka Institute of Technology. The author has contributed to research in topics: Wireless mesh network & Node (networking). The author has an hindex of 47, co-authored 1145 publications receiving 9969 citations. Previous affiliations of Leonard Barolli include Polytechnic University of Catalonia & Polytechnic University of Tirana.

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Proceedings ArticleDOI

Emergency Broadcast Protocol for Inter-Vehicle Communications

TL;DR: This paper presents an emergency broadcast protocol designed for sensor inter-vehicle communications and based in geographical routing, and shows that the proposed protocol is more effective compared to existing inter- vehicle protocols.
Journal ArticleDOI

Towards a smart world and ubiquitous intelligence: A walkthrough from smart things to smart hyperspaces and UbicKids

TL;DR: The potential trends and related challenges toward the smart world and ubiquitous intelligence from smart things to smart spaces and then to smart hyperspaces are discussed and efforts in developing a smart hyperspace of ubiquitous care for kids, called UbicKids are shown.
Proceedings ArticleDOI

Ad Hoc and Neighborhood Search Methods for Placement of Mesh Routers in Wireless Mesh Networks

TL;DR: Ad hoc and neighborhood search methods for optimal placement of mesh routers as more powerful methods for achieving near optimal placements of mesh router nodes are considered.
Journal ArticleDOI

JXTA-Overlay: A P2P Platform for Distributed, Collaborative, and Ubiquitous Computing

TL;DR: The Juxtapose (JXTA)-Overlay is presented, which is a JXTA-based peer-to-peer (P2P) platform designed with the aim to leverage capabilities of Java, JxTA, and P2P technologies to support distributed and collaborative systems.
Journal ArticleDOI

Genetic algorithms for satellite scheduling problems

TL;DR: This paper presents some relevant formulations of the satellite scheduling viewed as a family of problems and identifies various forms of optimization objectives and focuses on the version of ground station scheduling, for which computational results obtained with Genetic Algorithms using the STK simulation toolkit are presented.