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Ines Khoufi
Researcher at French Institute for Research in Computer Science and Automation
Publications - 31
Citations - 477
Ines Khoufi is an academic researcher from French Institute for Research in Computer Science and Automation. The author has contributed to research in topics: Wireless sensor network & Key distribution in wireless sensor networks. The author has an hindex of 9, co-authored 31 publications receiving 316 citations. Previous affiliations of Ines Khoufi include Conservatoire national des arts et métiers & Telecom SudParis.
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Journal ArticleDOI
A Survey of Recent Extended Variants of the Traveling Salesman and Vehicle Routing Problems for Unmanned Aerial Vehicles
TL;DR: This study proposes a review of existing literature devoted to such UAV path optimization problems, focusing specifically on the sub-class of problems that consider the mobility on a macroscopic scale, related to the two existing general classic ones—the Traveling Salesman Problem and the Vehicle Routing Problem.
Journal ArticleDOI
Survey of deployment algorithms in wireless sensor networks: coverage and connectivity issues and challenges
TL;DR: This study presents a general and detailed analysis of deployment problems in WSNs, highlighting the impacting factors, the common assumptions and models adopted in the literature, as well as performance criteria for evaluation purposes.
Journal ArticleDOI
A comprehensive survey on the Multiple Traveling Salesman Problem: Applications, approaches and taxonomy
TL;DR: In this paper, the authors provide a comprehensive review of existing studies on MTSP and highlight the approaches applied to solve the MTSP as well as its application domains, and propose a taxonomy and a classification of recent studies.
Proceedings ArticleDOI
Three dimensional mobile wireless sensor networks redeployment based on virtual forces
TL;DR: The design is the design of 3D-DVFA, a distributed deployment algorithm based on virtual forces in three dimensional wireless sensor networks where sensor nodes are assumed to be mobile and autonomous and demonstrates the effectiveness of the 3D algorithm proposed that provides full 3D area coverage and network connectivity.
Proceedings ArticleDOI
Analyzing Traces from a Google Data Center
TL;DR: The strong heterogeneity of jobs and the medium heterogeneity of machine configurations are characterized and the off-periods of machines are analyzed, which shows a high disparity in job execution durations.