F
Flavia C. Delicato
Researcher at Federal Fluminense University
Publications - 207
Citations - 3059
Flavia C. Delicato is an academic researcher from Federal Fluminense University. The author has contributed to research in topics: Wireless sensor network & Cloud computing. The author has an hindex of 27, co-authored 192 publications receiving 2515 citations. Previous affiliations of Flavia C. Delicato include University at Albany, SUNY & University of Rio Grande.
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Journal ArticleDOI
On the interplay of Internet of Things and Cloud Computing
Everton Cavalcante,Jorge Pereira,Marcelo Pitanga Alves,Pedro Maia,Roniceli Moura,Thais Batista,Flavia C. Delicato,Paulo F. Pires +7 more
TL;DR: The main outcomes of the performed systematic mapping are confirmed the increasing interest on the integration of IoT and Cloud Computing by both presenting an overview of the state of the art on the investigated topic and shedding light on important challenges and potential directions to future research.
Journal ArticleDOI
System modelling and performance evaluation of a three-tier Cloud of Things
Wei Li,Igor Leão dos Santos,Flavia C. Delicato,Paulo F. Pires,Luci Pirmez,Wei Wei,Houbing Song,Albert Y. Zomaya,Samee U. Khan +8 more
TL;DR: A three-tier system architecture is proposed and mathematically characterize each tier in terms of energy consumption and latency so that the transmission latency and bandwidth burden caused by cloud computing can be effectively reduced.
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Efficient allocation of resources in multiple heterogeneous Wireless Sensor Networks
Wei Li,Flavia C. Delicato,Paulo F. Pires,Young Choon Lee,Albert Y. Zomaya,Claudio Miceli,Luci Pirmez +6 more
TL;DR: It is argued that a middleware platform is required to manage heterogeneous WSNs and efficiently share their resources while satisfying user needs in the emergent scenarios of WoT.
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Adaptive Energy-Aware Computation Offloading for Cloud of Things Systems
TL;DR: An online algorithm, Lyapunov optimization on time and energy cost (LOTEC), based on the technique of Lyap unov optimization is described, which is able to make control decision on application offloading by adjusting the two-way tradeoff between average response time and average cost.
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On Enabling Sustainable Edge Computing with Renewable Energy Resources
Wei Li,Ting Yang,Flavia C. Delicato,Paulo F. Pires,Zahir Tari,Samee U. Khan,Albert Y. Zomaya +6 more
TL;DR: A unified energy management framework for enabling a sustainable edge computing paradigm with distributed renewable energy resources is proposed and it is demonstrated that renewable energy is fully capable of supporting the reliable running of edge computing devices in the prototype system during most of the experimental period.