Offload decision models and the price of anarchy in mobile cloud application ecosystems

With the maturity of technologies, such as HTML5 and JavaScript, and with the increasing popularity of cross-platform frameworks, such as Apache Cordova, mobile cloud computing as a new design paradigm of mobile application developments is becoming increasingly more accessible to developers. Following this trend, future on-device mobile application ecosystems will not only comprise a mixture of native and remote applications, but also include multiple hybrid mobile cloud applications. The resource competition in such ecosystems and its impact over the performance of mobile cloud applications has not yet been studied. In this paper, we study this competition from a game theoretical perspective and examine how it affects the behavior of mobile cloud applications. Three offload decision models of cooperative and non-cooperative nature are constructed and their efficiency compared. We present an extension to the classic load balancing game to model the offload behaviors within a non-cooperative environment. Mixed-strategy Nash equilibria are derived for the non-cooperative offload game with complete information, which further quantifies the price of anarchy in such ecosystems. We present simulation results that demonstrate the differences between each decision model’s efficiency. Our modeling approach facilitates further research in the design of the offload decision engines of mobile cloud applications. Our extension to the classic load balancing game broadens its applicability to real-life applications

Optical polarization rogue waves from supercontinuum generation in zero dispersion fiber pumped by dissipative soliton

Optical rogue waves emerge in nonlinear optical systems with extremely large amplitudes, and leave without a trace. In this work, we reveal the emergence of optical polarization rogue waves in supercontinuum generation from a zero-dispersion fiber, pumped by a dissipative soliton laser. Flat spectral broadening is achieved by modulation instability, followed by cascaded four-wave-mixing. In this process, we identify the emergence of optical polarization rogue waves, based on the probability density function of the relative distance among polarization states. Experimental results show that optical polarization rogue waves originate from vector multi-wave-mixing. Besides, we observe double peaks, and even triple peaks in the histogram of the state of polarization. This is a new and intriguing property, never observed so far in optical rogue waves, for example those emerging in the statistics of pulse intensities. Our polarization domain statistical analysis provides a new insight into the still debated topic of the mechanism for rogue wave generation in optical supercontinuum

A Revisit of Shape Editing Techniques: from the Geometric to the Neural Viewpoint

3D shape editing is widely used in a range of applications such as movie production, computer games and computer aided design. It is also a popular research topic in computer graphics and computer vision. In past decades, researchers have developed a series of editing methods to make the editing process faster, more robust, and more reliable. Traditionally, the deformed shape is determined by the optimal transformation and weights for an energy term. With increasing availability of 3D shapes on the Internet, data-driven methods were proposed to improve the editing results. More recently as the deep neural networks became popular, many deep learning based editing methods have been developed in this field, which is naturally data-driven. We mainly survey recent research works from the geometric viewpoint to those emerging neural deformation techniques and categorize them into organic shape editing methods and man-made model editing methods. Both traditional methods and recent neural network based methods are reviewed

Does non-stationarity of extreme precipitation exist in the Poyang Lake Basin of China?

Study region Poyang Lake Basin, China. Study focus This study aimed to investigate whether there are non-stationary characteristics of extreme precipitation in the Poyang Lake Basin (PLB) of China, and the trends of non-stationary characteristics from 1959 to 2019. The spatio-temporal variations of extreme precipitation were analysed from three fundamental aspects: duration, frequency, and intensity, based on the prewhitening Mann-Kendall (PWMK) test. Non-stationary variations and the risk of extreme precipitation were investigated based on the generalized additive models for location, scale, and shape (GAMLSS). New hydrological insights for the region (1) the intensity and frequency of extreme precipitation increased significantly, whereas there was a significant decrease in extreme precipitation duration in the PLB. (2) The duration of extreme precipitation showed significant non-stationary characteristics in the western PLB. At the Nanchang site, 83.3 % of the extreme precipitation intensity indices showed non-stationary characteristics. The RX1day (maximum 1-day precipitation amount) and RX5day (maximum 5-day precipitation amount) increased significantly for different return periods under non-stationary conditions in the northwestern PLB. (3) The risk of extreme precipitation can be captured using the GAMLSS. The stationary method underestimated the extreme precipitation intensity (e.g., RX1day) compared to the GAMLSS for longer return periods in the PLB. More attention should be paid to the increase and fluctuation of the return period of extreme precipitation caused by the mean non-stationarity and variance non-stationarity

Extended State Observer-Based Sliding-Mode Control for Three-Phase Power Converters

This paper proposes an extended state observer (ESO) based second-order sliding-mode (SOSM) control for three-phase two-level grid-connected power converters. The proposed control technique forces the input currents to track the desired values, which can indirectly regulate the output voltage while achieving a user-defined power factor. The presented approach has two control loops. A current control loop based on an SOSM and a dc-link voltage regulation loop which consists of an ESO plus SOSM. In this work, the load connected to the dc-link capacitor is considered as an external disturbance. An ESO is used to asymptotically reject this external disturbance. Therefore, its design is considered in the control law derivation to achieve a high performance. Theoretical analysis is given to show the closed-loop behavior of the proposed controller and experimental results are presented to validate the control algorithm under a real power converter prototyp

PSNet : fast data structuring for hierarchical deep learning on point cloud

In order to retain more feature information of local areas on a point cloud, local grouping and subsampling are the necessary data structuring steps in most hierarchical deep learning models. Due to the disorder nature of the points in a point cloud, the significant time cost may be consumed when grouping and subsampling the points, which consequently results in poor scalability. This paper proposes a fast data structuring method called PSNet (Point Structuring Net). PSNet transforms the spatial features of the points and matches them to the features of local areas in a point cloud. PSNet achieves grouping and sampling at the same time while the existing methods process sampling and grouping in two separate steps (such as using FPS plus kNN). PSNet performs feature transformation pointwise while the existing methods uses the spatial relationship among the points as the reference for grouping. Thanks to these features, PSNet has two important advantages: 1) the grouping and sampling results obtained by PSNet is stable and permutation invariant; and 2) PSNet can be easily parallelized. PSNet can replace the data structuring methods in the mainstream point cloud deep learning models in a plug-and-play manner. We have conducted extensive experiments. The results show that PSNet can improve the training and reasoning speed significantly while maintaining the model accuracy

Adaptive Redundant Lifting Wavelet Transform Based on Fitting for Fault Feature Extraction of Roller Bearings

A least square method based on data fitting is proposed to construct a new lifting wavelet, together with the nonlinear idea and redundant algorithm, the adaptive redundant lifting transform based on fitting is firstly stated in this paper. By variable combination selections of basis function, sample number and dimension of basis function, a total of nine wavelets with different characteristics are constructed, which are respectively adopted to perform redundant lifting wavelet transforms on low-frequency approximate signals at each layer. Then the normalized lP norms of the new node-signal obtained through decomposition are calculated to adaptively determine the optimal wavelet for the decomposed approximate signal. Next, the original signal is taken for subsection power spectrum analysis to choose the node-signal for single branch reconstruction and demodulation. Experiment signals and engineering signals are respectively used to verify the above method and the results show that bearing faults can be diagnosed more effectively by the method presented here than by both spectrum analysis and demodulation analysis. Meanwhile, compared with the symmetrical wavelets constructed with Lagrange interpolation algorithm, the asymmetrical wavelets constructed based on data fitting are more suitable in feature extraction of fault signal of roller bearings

Single-shot measurement of wavelength-resolved state of polarization dynamics in ultrafast lasers using dispersed division-of-amplitude

Characterization of the state of polarization (SOP) of ultrafast laser emission is relevant in several application fields such as field manipulation, pulse shaping, testing of sample characteristics, and biomedical imaging. Nevertheless, since high-speed detection and wavelength-resolved measurements cannot be simultaneously achieved by commercial polarization analyzers, single-shot measurements of the wavelength-resolved SOP of ultrafast laser pulses have rarely been reported. Here, we propose a method for single-shot, wavelength-resolved SOP measurements that exploits the method of division-of-amplitude under far-field transformation. A large accumulated chromatic dispersion is utilized to time-stretch the laser pulses via dispersive Fourier transform, so that spectral information is mapped into a temporal waveform. By calibrating our test matrix with different wavelengths, wavelength-resolved SOP measurements are achieved, based on the division-of-amplitude approach, combined with high-speed opto-electronic processing. As a proof-of-concept demonstration, we reveal the complex wavelength-dependent SOP dynamics in the build-up of dissipative solitons. The experimental results show that the dissipative soliton exhibits far more complex wavelength-related polarization dynamics, which are not shown in single-shot spectrum measurement. Our method paves the way for single-shot measurement and intelligent control of ultrafast lasers with wavelength-resolved SOP structures, which could promote further investigations of polarization-related optical signal processing techniques, such as pulse shaping and hyperspectral polarization imaging