移动边缘计算环境下的动态资源分配策略

在通讯设备爆炸式增长的时代,移动边缘计算作为5G通讯技术的核心技术之一,对其进行合理的资源分配显得尤为重要。移动边缘计算的思想是把云计算中心下沉到基站部署(边缘云),使云计算中心更加靠近用户,以快速解决计算资源分配问题。但是,相对于大型的云计算中心,边缘云的计算资源有限,传统的虚拟机分配方式不足以灵活应对边缘云的计算资源分配问题。为解决此问题,提出一种根据用户综合需求变化的动态计算资源和频谱分配算法(DRFAA),采用"分治"策略,并将资源模拟成"流体"资源进行分配,以寻求较大的吞吐量和较低的传输时延。实验仿真结果显示,动态计算资源和频谱分配算法可以有效地降低用户与边缘云之间的传输时延,也可以提高边缘云的吞吐量。     

Study on the removal of olefins from naphtha by clay loaded with trifluoromethanesulfonic acid

Journal of Porous Materials - In this work, a trifluoromethanesulfonic acid (TFOH) modified clay (TFOH-Clay) was developed for the removal of trace olefins in heavy naphtha. 5%TFOH-Clay can...     

A spatio-temporal fusion method for remote sensing data Using a linear injection model and local neighbourhood information

This paper presents a spatio-temporal fusion method for remote sensing images by using a linear injection model and local neighbourhood information. In this method, the linear injection model is first introduced to generate an initial fused image, the spatial details are extracted from the fine-resolution image at the base date, and are weighted by a proper injection gains. Then, the spatial details and the relative spectral information from the coarse-resolution images are blended to generate the fusion result. To further enhance its robustness to the noise, the local neighbourhood information, derived from the fine-resolution image and the fused result simultaneously, is introduced to refine the initial fused image to obtain a more accurate prediction result. The algorithm can effectively capture phenology change or land-cover-type change with minimum input data. Simulated data and two types of real satellite images with seasonal changes and land-cover-type changes are employed to test the performance of the proposed method. Compared with a spatial and temporal adaptive reflectance fusion model (STARFM) and a flexible spatio-temporal fusion algorithm (FSDAF), results show that the proposed approach improves the accuracy of fused images in phenology change area and effectively captures land-cover-type reflectance changes.     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

Crystallographic characteristics and microwave dielectric properties of Ni-modified MgTa2O6 ceramics

Ni²⁺ modified MgTa₂O₆ ceramics with a trirutile phase and space group P4₂/mnm were obtained. The correlations between crystallographic characteristics and microwave dielectric performance of MgTa₂O₆ ceramics were systematically studied based on the chemistry bond theory (PVL theory) for the first time. The results indicate that the introduction of Ni²⁺ causes a change in polarizability and the Mg–O bond ionicity, which contributes to the variation of dielectric constant. Moreover, the lattice energy, and packing fraction, full width at half maximum of the Raman peak of Ta–O bond, as the quantitative characterization of crystallographic parameters, regulate the dielectric loss of MgTa₂O₆ ceramics in GHz frequency band. In addition, the study of sintering behavior shows that the densification and micromorphology are the crucial factors affecting the microwave dielectric performance. Typically, Ni²⁺ doping on the A-site of MgTa₂O₆ can effectively promote the Q × f values to 173,000 GHz (at 7.43 GHz), which ensures its applicability in 5G communication technology.     

Investigation of crystal characteristics,Raman spectra,and microwave dielectric properties of Mg1-xZnxTa2O6 ceramics

Mg_(1-x)Zn_xTa₂O₆ (x = 0.00?0.08) dielectric ceramics were synthesized via the traditional solid-state reaction method. We used XRD and Rietveld refinement to demonstrate that a pure Mg_(1-x)Zn_xTa₂O₆ phase with trirutile structure was formed. Zn²⁺ substitution helped to decrease the Raman full width at half width of the A_1g mode at 703 cm^?1, which resulted in an increase in the order and rigidity of the TaO₆ octahedron, this in turn contributed to improving the Q×f values. Additionally, the introduction of Zn²⁺ significantly promoted grain growth and increased the dense, and the molecular polarizability, these factors lead to a higher permittivity. Moreover, enhanced Ta-O bond energy resulted in a more stable TaO₆ octahedron in the Mg_(1?x)Zn_xTa₂O₆ system, which contributed to enhanced τ_f values via substitution of Zn²⁺ doped on the A-site. Correspondingly, the microwave dielectric properties were significantly improved for 0.04-doped samples, obtaining: ε_r = 27, Q × f = 185,000 GHz (at 7.47 GHz), τ_f =32 ppm/°C.     

Fabrication and characterizations of Cr3+-doped ZnGa2O4 transparent ceramics with persistent luminescence

0.5 at.% Cr:ZnGa₂O₄ precursor was synthesized by the co-precipitation method with nitrates as raw materials, using ammonium carbonate as the precipitant. Low-agglomerated Cr:ZnGa₂O₄ powders with an average particle size of 43 nm were obtained by calcining the precursor at 900℃ for 4 h. Using the powders as starting materials, 0.5 at.% Cr:ZnGa₂O₄ ceramics with an average grain size of about 515 nm were prepared by presintering at 1150℃ for 5 h in air and HIP post-treatment at 1100℃ for 3 h under 200 MPa Ar. The in-line transmittance of 0.5 at.% Cr:ZnGa₂O₄ ceramics with a thickness of 1.3 mm reaches 59.5% at the wavelength of 700 nm. The Cr:ZnGa₂O₄ ceramics can be effectively excited by visible light and produce persistent luminescence at 700 nm. For Cr:ZnGa₂O₄ transparent ceramics, the brightness of afterglow was larger than 0.32 mcd/m² after 30 min, which is far superior to that of Cr:ZnGa₂O₄ persistent luminescence powders.     

Traffic identification method based on multiple probabilistic neural network model

Neural Computing and Applications - Traffic identification is currently an important challenge for network management and security. In this paper, we propose a novel application identification...