1,194 research outputs found
VeryFL: A Verify Federated Learning Framework Embedded with Blockchain
Blockchain-empowered federated learning (FL) has provoked extensive research
recently. Various blockchain-based federated learning algorithm, architecture
and mechanism have been designed to solve issues like single point failure and
data falsification brought by centralized FL paradigm. Moreover, it is easier
to allocate incentives to nodes with the help of the blockchain. Various
centralized federated learning frameworks like FedML, have emerged in the
community to help boost the research on FL. However, decentralized
blockchain-based federated learning framework is still missing, which cause
inconvenience for researcher to reproduce or verify the algorithm performance
based on blockchain. Inspired by the above issues, we have designed and
developed a blockchain-based federated learning framework by embedding Ethereum
network. This report will present the overall structure of this framework,
which proposes a code practice paradigm for the combination of FL with
blockchain and, at the same time, compatible with normal FL training task. In
addition to implement some blockchain federated learning algorithms on smart
contract to help execute a FL training, we also propose a model ownership
authentication architecture based on blockchain and model watermarking to
protect the intellectual property rights of models. These mechanism on
blockchain shows an underlying support of blockchain for federated learning to
provide a verifiable training, aggregation and incentive distribution procedure
and thus we named this framework VeryFL (A Verify Federated Learninig Framework
Embedded with Blockchain). The source code is avaliable on
https://github.com/GTMLLab/VeryFL
Data-Driven 3D Placement of UAV Base Stations for Arbitrarily Distributed Crowds
In this paper, we consider an Unmanned Aerial Vehicle (UAV)-assisted cellular
system which consists of multiple UAV base stations (BSs) cooperating the
terrestrial BSs. In such a heterogeneous network, for cellular operators, the
problem is how to determine the appropriate number, locations, and altitudes of
UAV-BSs to improve the system sumrate as well as satisfy the demands of
arbitrarily flash crowds on data rates. We propose a data-driven 3D placement
of UAV-BSs for providing an effective placement result with a feasible
computational cost. The proposed algorithm searches for the appropriate number,
location, coverage, and altitude of each UAV-BS in the serving area with the
maximized system sumrate in polynomial time so as to guarantee the minimum data
rate requirement of UE. The simulation results show that the proposed approach
can improve system sumrate in comparison with the case without UAV-BSs.Comment: 6 pages, 3 figures, accepted by 2019 IEEE Global Communications
Conference: Wireless Communications (Globecom2019 WC
Ultrafast Relaxation Dynamics of Photoexcited Dirac Fermion in The Three Dimensional Dirac Semimetal Cadmium Arsenide
Three dimensional (3D) Dirac semimetals which can be seen as 3D analogues of
graphene have attracted enormous interests in research recently. In order to
apply these ultrahigh-mobility materials in future electronic/optoelectronic
devices, it is crucial to understand the relaxation dynamics of photoexcited
carriers and their coupling with lattice. In this work, we report ultrafast
transient reflection measurements of the photoexcited carrier dynamics in
cadmium arsenide (Cd3As2), which is one of the most stable Dirac semimetals
that have been confirmed experimentally. By using low energy probe photon of
0.3 eV, we probed the dynamics of the photoexcited carriers that are
Dirac-Fermi-like approaching the Dirac point. We systematically studied the
transient reflection on bulk and nanoplate samples that have different doping
intensities by tuning the probe wavelength, pump power and lattice temperature,
and find that the dynamical evolution of carrier distributions can be retrieved
qualitatively by using a two-temperature model. This result is very similar to
that of graphene, but the carrier cooling through the optical phonon couplings
is slower and lasts over larger electron temperature range because the optical
phonon energies in Cd3As2 are much lower than those in graphene
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