S
Simone Silvestri
Researcher at University of Kentucky
Publications - 87
Citations - 1299
Simone Silvestri is an academic researcher from University of Kentucky. The author has contributed to research in topics: Wireless sensor network & Network topology. The author has an hindex of 17, co-authored 83 publications receiving 1030 citations. Previous affiliations of Simone Silvestri include Imperial College London & Pennsylvania State University.
Papers
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Journal ArticleDOI
Autonomous Deployment of Heterogeneous Mobile Sensors
TL;DR: VorLag is introduced, a generalization of the Voronoi-based approach which exploits the Laguerre geometry, and it is shown that VorLag provides a very stable sensor behavior, with fast and guaranteed termination and moderate energy consumption.
Proceedings ArticleDOI
Reducing power consumption in wired networks
Erol Gelenbe,Simone Silvestri +1 more
TL;DR: This paper examines some approaches for dynamically managing wired packet networks to minimise energy consumption while meeting users' QoS needs, by automatically turning link drivers and/or routers on/off in response to changes in network load.
Posted Content
Push & Pull: autonomous deployment of mobile sensors for a complete coverage
TL;DR: Performance comparisons between Push & Pull and one of the most acknowledged algorithms show how the former can efficiently reach a more uniform and complete coverage under a wide range of working scenarios.
Journal ArticleDOI
Managing Contingencies in Smart Grids via the Internet of Things
TL;DR: The proposed framework provides the Welch-based reactive appliance prediction (WRAP) algorithm to predict the user behavior and maximize utility, and shows that power system components at risk can be quickly alleviated by adjusting a large number of small smart loads.
Journal ArticleDOI
Push & Pull: autonomous deployment of mobile sensors for a complete coverage
TL;DR: In this article, the authors propose a distributed algorithm for the autonomous deployment of mobile sensors called Push & Pull, which does not require any prior knowledge of the operating conditions or any manual tuning of key parameters.