279 research outputs found
Distributed Indexing Schemes for k-Dominant Skyline Analytics on Uncertain Edge-IoT Data
Skyline queries typically search a Pareto-optimal set from a given data set
to solve the corresponding multiobjective optimization problem. As the number
of criteria increases, the skyline presumes excessive data items, which yield a
meaningless result. To address this curse of dimensionality, we proposed a
k-dominant skyline in which the number of skyline members was reduced by
relaxing the restriction on the number of dimensions, considering the
uncertainty of data. Specifically, each data item was associated with a
probability of appearance, which represented the probability of becoming a
member of the k-dominant skyline. As data items appear continuously in data
streams, the corresponding k-dominant skyline may vary with time. Therefore, an
effective and rapid mechanism of updating the k-dominant skyline becomes
crucial. Herein, we proposed two time-efficient schemes, Middle Indexing (MI)
and All Indexing (AI), for k-dominant skyline in distributed edge-computing
environments, where irrelevant data items can be effectively excluded from the
compute to reduce the processing duration. Furthermore, the proposed schemes
were validated with extensive experimental simulations. The experimental
results demonstrated that the proposed MI and AI schemes reduced the
computation time by approximately 13% and 56%, respectively, compared with the
existing method.Comment: 13 pages, 8 figures, 12 tables, to appear in IEEE Transactions on
Emerging Topics in Computin
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
Interference-Aware Deployment for Maximizing User Satisfaction in Multi-UAV Wireless Networks
In this letter, we study the deployment of Unmanned Aerial Vehicle mounted
Base Stations (UAV-BSs) in multi-UAV cellular networks. We model the multi-UAV
deployment problem as a user satisfaction maximization problem, that is,
maximizing the proportion of served ground users (GUs) that meet a given
minimum data rate requirement. We propose an interference-aware deployment
(IAD) algorithm for serving arbitrarily distributed outdoor GUs. The proposed
algorithm can alleviate the problem of overlapping coverage between adjacent
UAV-BSs to minimize inter-cell interference. Therefore, reducing co-channel
interference between UAV-BSs will improve user satisfaction and ensure that
most GUs can achieve the minimum data rate requirement. Simulation results show
that our proposed IAD outperforms comparative methods by more than 10% in user
satisfaction in high-density environments.Comment: 5 pages, 3 figures, to appear in IEEE Wireless Communications Letter
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α-Lactosylceramide Protects Against iNKT-Mediated Murine Airway Hyperreactivity and Liver Injury Through Competitive Inhibition of Cd1d Binding.
Invariant natural killer T (iNKT) cells, which are activated by T cell receptor (TCR)-dependent recognition of lipid-based antigens presented by the CD1d molecule, have been shown to participate in the pathogenesis of many diseases, including asthma and liver injury. Previous studies have shown the inhibition of iNKT cell activation using lipid antagonists can attenuate iNKT cell-induced disease pathogenesis. Hence, the development of iNKT cell-targeted glycolipids can facilitate the discovery of new therapeutics. In this study, we synthesized and evaluated α-lactosylceramide (α-LacCer), an α-galactosylceramide (α-GalCer) analog with lactose substitution for the galactose head and a shortened acyl chain in the ceramide tail, toward iNKT cell activation. We demonstrated that α-LacCer was a weak inducer for both mouse and human iNKT cell activation and cytokine production, and the iNKT induction by α-LacCer was CD1d-dependent. However, when co-administered with α-GalCer, α-LacCer inhibited α-GalCer-induced IL-4 and IFN-γ production from iNKT cells. Consequently, α-LacCer also ameliorated both α-GalCer and GSL-1-induced airway hyperreactivity and α-GalCer-induced neutrophilia when co-administered in vivo. Furthermore, we were able to inhibit the increases of ConA-induced AST, ALT and IFN-γ serum levels through α-LacCer pre-treatment, suggesting α-LacCer could protect against ConA-induced liver injury. Mechanistically, we discerned that α-LacCer suppressed α-GalCer-stimulated cytokine production through competing for CD1d binding. Since iNKT cells play a critical role in the development of AHR and liver injury, the inhibition of iNKT cell activation by α-LacCer present a possible new approach in treating iNKT cell-mediated diseases
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