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Feng Xiao

Publications and source records attributed to Feng Xiao.

At least 91 records · Page 5Linked to original sources

Discontinuity-resolving shock-capturing schemes on unstructured grids

Solving compressible flows containing discontinuities remains a major challenge for numerical methods especially on unstructured grids. Thus in this work, we make contributions to shock capturing schemes on unstructured grids with aim of resolving discontinuities with low numerical dissipation. Different from conventional shock capturing schemes which only use polynomials as interpolation functions on unstructured grids, the proposed scheme employs the linear polynomial as well as non-polynomial as reconstruction candidates. For linear polynomial, the second order MUSCL scheme with the MLP (Multi-dimensional Limiting Process) slope limiter is adopted. The multi-dimensional THINC (Tangent of Hyperbola for INterface Capturing) function with quadratic surface representation and Gaussian quadrature, so-called THINC/QQ, is used as the non-polynomial reconstruction candidate. With these reconstruction candidates, a multi-stage boundary variation diminishing (BVD) algorithm which aims to minimize numerical dissipation is designed on unstructured grids to select the final reconstruction function. The resulted shock capturing scheme is named as MUSCL-THINC/QQ-BVD. The performance of the proposed scheme is demonstrated through solving compressible single-phase and multi-phase problems where the discontinuity is the typical flow structure. The numerical results show that the proposed scheme is capable of capturing sharp discontinuous profiles without numerical oscillations as well as resolving vortices associated with Kelvin-Helmholtz instabilities along shear layers and material interfaces. In comparison with schemes only replying on high order polynomials, the proposed scheme shows significant improvement of resolution across discontinuities. Thus, this work provides an accurate and robust shock-capturing scheme to resolve discontinuities in compressible flows.

physics.comp-ph↗

ICSTrace: A Malicious IP Traceback Model for Attacking Data of Industrial Control System

Considering the attacks against industrial control system are mostly organized and premeditated actions, IP traceback is significant for the security of industrial control system. Based on the infrastructure of the Internet, we have developed a novel malicious IP traceback model-ICSTrace, without deploying any new services. The model extracts the function codes and their parameters from the attack data according to the format of industrial control protocol, and employs a short sequence probability method to transform the function codes and their parameter into a vector, which characterizes the attack pattern of malicious IP addresses. Furthermore, a Partial Seeded K-Means algorithm is proposed for the pattern's clustering, which helps in tracing the attacks back to an organization. ICSTrace is evaluated basing on the attack data captured by the large-scale deployed honeypots for industrial control system, and the results demonstrate that ICSTrace is effective on malicious IP traceback in industrial control system.

cs.CR↗

SolidityCheck : Quickly Detecting Smart Contract Problems Through Regular Expressions

As a blockchain platform that has developed vigorously in recent years, Ethereum is different from Bitcoin in that it introduces smart contracts into blockchain.Solidity is one of the most mature and widely used smart contract programming language,which is used to write smart contracts and deploy them on blockchain. However, once the data in the blockchain is written, it cannot be modified. Ethereum smart contract is stored in the block chain, which makes the smart contract can no longer repair the code problems such as re-entrancy vulnerabilities or integer overflow problems. Currently, there still lacks of an efficient and effective approach for detecting these problems in Solidity. In this paper, we first classify all the possible problems in Solidity, then propose a smart contract problem detection approach for Solidity, namely SolidityCheck. The approach uses regular expressions to define the characteristics of problematic statements and uses regular matching and program instrumentation to prevent or detect problems. Finally, a large number of experiments is performed to show that SolidityCheck is superior to existing approaches.

cs.SE↗

THINC-scaling scheme that unifies VOF and level set methods

We present a novel interface-capturing scheme, THINC-scaling, to unify the VOF (volume of fluid) and the level set methods, which have been developed as two completely different approaches widely used in various applications. The THINC-scaling scheme preserves at the samectime the advantages of both VOF and level set methods, i.e. the mass/volume conservation of the VOF method and the geometrical faithfulness of the level set method. THINC-scaling scheme allows to represent interface with high-order polynomials, and has algorithmic simplicity which eases its implementation in unstructured grids.

math.NA↗

Optimizing Online Matching for Ride-Sourcing Services with Multi-Agent Deep Reinforcement Learning

Ride-sourcing services are now reshaping the way people travel by effectively connecting drivers and passengers through mobile internets. Online matching between idle drivers and waiting passengers is one of the most key components in a ride-sourcing system. The average pickup distance or time is an important measurement of system efficiency since it affects both passengers' waiting time and drivers' utilization rate. It is naturally expected that a more effective bipartite matching (with smaller average pickup time) can be implemented if the platform accumulates more idle drivers and waiting passengers in the matching pool. A specific passenger request can also benefit from a delayed matching since he/she may be matched with closer idle drivers after waiting for a few seconds. Motivated by the potential benefits of delayed matching, this paper establishes a two-stage framework which incorporates a combinatorial optimization and multi-agent deep reinforcement learning methods. The multi-agent reinforcement learning methods are used to dynamically determine the delayed time for each passenger request (or the time at which each request enters the matching pool), while the combinatorial optimization conducts an optimal bipartite matching between idle drivers and waiting passengers in the matching pool. Two reinforcement learning methods, spatio-temporal multi-agent deep Q learning (ST-M-DQN) and spatio-temporal multi-agent actor-critic (ST-M-A2C) are developed. Through extensive empirical experiments with a well-designed simulator, we show that the proposed framework is able to remarkably improve system performances.

cs.MA↗

Constructing high-order discontinuity-capturing schemes with linear-weight polynomials and boundary variation diminishing algorithm

In this study, a new framework of constructing very high order discontinuity-capturing schemes is proposed for finite volume method. These schemes, so-called $\mathrm{P}_{n}\mathrm{T}_{m}-\mathrm{BVD}$ (polynomial of $n$-degree and THINC function of $m$-level reconstruction based on BVD algorithm), are designed by employing high-order linear-weight polynomials and THINC (Tangent of Hyperbola for INterface Capturing) functions with adaptive steepness as the reconstruction candidates. The final reconstruction function in each cell is determined with a multi-stage BVD (Boundary Variation Diminishing) algorithm so as to effectively control numerical oscillation and dissipation. We devise the new schemes up to eleventh order in an efficient way by directly increasing the order of the underlying upwind scheme using linear-weight polynomials. The analysis of the spectral property and accuracy tests show that the new reconstruction strategy well preserves the low-dissipation property of the underlying upwind schemes with high-order linear-weight polynomials for smooth solution over all wave numbers and realizes $n+1$ order convergence rate. The performance of new schemes is examined through widely used benchmark tests, which demonstrate that the proposed schemes are capable of simultaneously resolving small-scale flow features with high resolution and capturing discontinuities with low dissipation. With outperforming results and simplicity in algorithm, the new reconstruction strategy shows great potential as an alternative numerical framework for computing nonlinear hyperbolic conservation laws that have discontinuous and smooth solutions of different scales.

physics.comp-ph↗

A fifth-order shock capturing scheme with BVD algorithm

A novel 5th-order shock capturing scheme is presented in this paper. The scheme, so-called P4-THINC-BVD (4th degree polynomial and THINC reconstruction based on BVD algorithm), is formulated as a two-stage cascade BVD (Boundary Variation Diminishing) algorithm following the BVD principle that minimizes the jumps of reconstructed values at cell boundaries. In the P4-THINC-BVD scheme, polynomial of degree four and THINC (Tangent of Hyperbola for INterface Capturing) functions with adaptive steepness are used as the candidate reconstruction functions. The final reconstruction function is selected from the candidate functions by a two-stage cascade BVD algorithm so as to effectively control numerical oscillation and dissipation. Spectral analysis and numerical verifications show that the P4-THINC-BVD scheme possesses the following desirable properties: 1) it effectively suppresses spurious numerical oscillation in the presence of strong shock or discontinuity; 2) it substantially reduces numerical dissipation errors; 3) it automatically retrieves the underlying linear 5th-order upwind scheme for smooth solution over all wave numbers; 4) it is able to resolve both smooth and discontinuous flow structures of all scales with substantially improved solution quality in comparison to other existing methods; and 5) it faithfully maintains the free-mode solutions in long term computation. P4-THINC-BVD, as well as the underlying idea presented in this paper, provides an innovative and practical approach to design high-fidelity numerical schemes for compressible flows involving strong discontinuities and flow structures of wide range scales.

physics.comp-ph↗

PatternListener: Cracking Android Pattern Lock Using Acoustic Signals

Pattern lock has been widely used for authentication to protect user privacy on mobile devices (e.g., smartphones and tablets). Given its pervasive usage, the compromise of pattern lock could lead to serious consequences. Several attacks have been constructed to crack the lock. However, these approaches require the attackers to either be physically close to the target device or be able to manipulate the network facilities (e.g., WiFi hotspots) used by the victims. Therefore, the effectiveness of the attacks is significantly impacted by the environment of mobile devices. Also, these attacks are not scalable since they cannot easily infer unlock patterns of a large number of devices. Motivated by an observation that fingertip motions on the screen of a mobile device can be captured by analyzing surrounding acoustic signals on it, we propose PatternListener, a novel acoustic attack that cracks pattern lock by analyzing imperceptible acoustic signals reflected by the fingertip. It leverages speakers and microphones of the victim's device to play imperceptible audio and record the acoustic signals reflected by the fingertip. In particular, it infers each unlock pattern by analyzing individual lines that compose the pattern and are the trajectories of the fingertip. We propose several algorithms to construct signal segments according to the captured signals for each line and infer possible candidates of each individual line according to the signal segments. Finally, we map all line candidates into grid patterns and thereby obtain the candidates of the entire unlock pattern. We implement a PatternListener prototype by using off-the-shelf smartphones and thoroughly evaluate it using 130 unique patterns. The real experimental results demonstrate that PatternListener can successfully exploit over 90% patterns within five attempts.

eess.SP↗

Coupled THINC and level set method: a conservative interface capturing scheme with arbitrary-order surface representations

In this paper, we propose a simple and accurate numerical method for capturing moving interfaces on fixed Eulerian grids by coupling the Tangent of Hyperbola Interface Capturing (THINC) method and Level Set (LS) method. The innovative and practically-significant aspects of the proposed method, so-called THINC/LS method, lie in (1) representing the interface with polynomial of arbitrary-order rather than the plane representation commonly used in the Piecewise Linear Interface Calculation (PLIC) Volume of fluid (VOF) methods, (2) conserving rigorously the mass of the transported VOF field, and (3) providing a straightforward and easy-to-code algorithm for implementation. We verified the proposed scheme with the widely used benchmark tests. Numerical results show that this new method can obtain arbitrary-order accuracy for interface reconstruction and can produce more accurate results than the classical VOF methods.

physics.comp-ph↗

Robustness Analysis of Asynchronous Sampled-Data Multi-Agent Networks With Time-Varying Delays

In this paper, we study the simultaneous stability problem of a finite number of locally inter-connected linear subsystems under practical constraints, including asynchronous and aperiodic sampling, time-varying delays, and measurement errors. We establish a new Lyapunov-based stability result for such a decentralized system. This system has a particular simple structure of interconnections, but it captures some key characteristics of a large class of intermediate models derived from the consensus analysis of multi-agent systems. The stability result is applicable to the estimation of the maximum allowable inter-sampling periods and time delays based on individual dynamics and coupling structures in the scenarios of consensus control via asynchronous sampling of relative states and asynchronous broadcasting of self-sampled states respectively. The asynchrony of aperiodic sampling and the existence of measurement errors allow the utilization of some kinds of quantizing devices, such as Logarithmic quantizers, in the process of data sampling, and allow the introduction of a period of dwell time after each update of state measurement to eliminate the Zeno behavior of events in event-based control. The extension in the case with input saturations and input delays is also discussed.

math.OC↗

A Deep Learning Model for Traffic Flow State Classification Based on Smart Phone Sensor Data

This study proposes a Deep Belief Network model to classify traffic flow states. The model is capable of processing massive, high-density, and noise-contaminated data sets generated from smartphone sensors. The statistical features of Vehicle acceleration, angular acceleration, and GPS speed data, recorded by smartphone software, are analyzed, and then used as input for traffic flow state classification. Data from a five-day experiment is used to train and test the proposed model. A total of 747,856 sets of data are generated and used for both traffic flow states classification and sensitivity analysis of input variables. The result shows that the proposed Deep Belief Network model is superior to traditional machine learning methods in both classification performance and computational efficiency.

cs.LG↗

A new shock-capturing scheme for stiff detonation waves problems

A new approach to prevent spurious behavior caused by conventional shock-capturing schemes when solving stiff detonation waves problems is introduced in the present work. Due to smearing of discontinuous solution by the excessive numerical dissipation, conventional shock-capturing schemes have difficulties to obtain the correct location of detonation front without enough grids resolution. To overcome the excessive numerical errors around discontinuities by traditional discretized schemes used in non-reacting high speed compressible flow, we introduce a new shock-capturing scheme in which besides linear function constructed by MUSCL (Monotone Upstream-centered Schemes for Conservation Law) scheme, a step like THINC (Tangent of Hyperbola for INterface Capturing) function is also employed as another candidate in the reconstruction process. The final reconstruction function is determined by boundary variation diminishing (BVD) algorithm by which numerical dissipation around discontinuities can be reduced significantly. The new resulted shock-capturing scheme is named MUSCL-THINC-BVD. One- and two-dimensional comparative numerical tests about stiff detonation waves problems are conducted with the 5th order WENO (Weighted Essentially Non-Oscillatory) and MUSCL-THINC-BVD scheme respectively, which show MUSCL-THINC-BVD scheme can capture the correct position of detonation waves with improved resolution while WENO scheme, in spite of higher order, produces spurious waves. Compared with other existing methods which involves extra treatments by accepting the smeared out discontinuities profiles, the current method obtain the correct but also sharp detonation front by fundamentally reducing numerical dissipation errors from shock-capturing schemes. Thus the proposed approach is an effective but simple method to solve stiff detonation problems.

physics.comp-ph↗

Some practical versions of boundary variation diminishing (BVD) algorithm

This short note presents some variant schemes of boundary variation diminishing (BVD) algorithm in one dimension with the results of numerical tests for linear advection equation to facilitate practical use. In spite of being presented in 1D fashion, all the schemes are simple and easy to implement in multi-dimensions on structured and unstructured grids for nonlinear and system equations.

math.NA↗

Implementation of BVD (boundary variation diminishing) algorithm in simulations of compressible multiphase flows

We present in this work a new reconstruction scheme, so-called MUSCL-THINC-BVD scheme, to solve the five-equation model for interfacial two phase flows. This scheme employs the traditional shock capturing MUSCL (Monotone Upstream-centered Schemes for Conservation Law) scheme as well as the interface sharpening THINC (Tangent of Hyperbola for INterface Capturing) scheme as two building-blocks of spatial reconstruction using the BVD (boundary variation diminishing) principle that minimizes the variations (jumps) of the reconstructed variables at cell boundaries, and thus effectively reduces the numerical dissipations in numerical solutions. The MUSCL-THINC-BVD scheme is implemented to all state variables and volume fraction, which realizes the consistency among volume fraction and other physical variables. Benchmark tests are carried out to verify the capability of the present method in capturing the material interface as a well-defined sharp jump in volume fraction, as well as significant improvement in solution quality. The proposed scheme is a simple and effective method of practical significance for simulating compressible interfacial multiphase flows.

physics.comp-ph↗

CHAOS: an SDN-based Moving Target Defense System

The static nature of current cyber systems has made them easy to be attacked and compromised. By constantly changing a system, Moving Target Defense (MTD) has provided a promising way to reduce or move the attack surface that is available for exploitation by an adversary. However, the current network- based MTD obfuscates networks indiscriminately that makes some networks key services, such as web and DNS services, unavailable, because many information of these services has to be opened to the outside and remain real without compromising their usability. Moreover, the indiscriminate obfuscation also severely reduces the performance of networks. In this paper, we propose CHAOS, an SDN (Software-defined networking)-based MTD system, which discriminately obfuscates hosts with different security levels in a network. In CHAOS, we introduce a Chaos Tower Obfuscation (CTO) method, which uses a Chaos Tower Structure (CTS) to depict the hierarchy of all the hosts in an intranet and provides a more unpredictable and flexible obfuscation method. We also present the design of CHAOS, which leverages SDN features to obfuscate the attack surface including IP obfuscation, ports obfuscation, and fingerprint obfuscation thereby enhancing the unpredictability of the networking environment. We develop fast CTO algorithms to achieve a different degree of obfuscation for the hosts in each layer. Our experimental results show that a network protected by CHAOS is capable of decreasing the percentage of information disclosure effectively to guarantee the normal flow of traffic.

cs.NI↗

A note on implementation of boundary variation diminishing algorithm to high-order local polynomial-based schemes

A novel approach for selecting appropriate reconstructions is implemented to the hyperbolic conservation laws in the high-order local polynomial-based framework, e.g., the discontinuous Galerkin (DG) and flux reconstruction (FR) schemes. The high-order polynomial approximation generally fails to correctly capture a strong discontinuity inside a cell due to the Runge phenomenon, which is replaced by more stable approximation on the basis of a troubled-cell indicator such as that used in the total variation bounded (TVB) limiter. This paper examines the applicability of a new algorithm, so-called boundary variation diminishing (BVD) reconstruction, to the weighted essentially non-oscillatory (WENO) methodology in the FR framework including the nodal type DG method. The BVD reconstruction adaptively chooses a proper approximation for the solution function so as to minimize the jump between values at the left- and right-side of cell boundaries without any ad hoc constant such as the TVB parameter. Several numerical tests are conducted for a linear advection equation as well as the selection of an appropriate reconstruction, where the results of the BVD algorithm are comparable to those using the conventional TVB limiter. Note that the present work is limited to third or lower order polynomials, leaving the implementations for higher-order schemes a future work.

math.NA↗

Boundary Variation Diminishing (BVD) reconstruction: a new approach to improve Godunov scheme

This paper presents a new approach, so-called boundary variation diminishing (BVD), for reconstructions that minimize the discontinuities (jumps) at cell interfaces in Godunov type schemes. It is motivated by the observation that diminishing the jump at the cell boundary might effectively reduce the dissipation in numerical flux. Different from the existing practices which seek high-order polynomials within mesh cells while assuming discontinuities being always at the cell interfaces, we proposed a new strategy that combines a high-order polynomial-based interpolation and a jump-like reconstruction that allows a discontinuity being partly represented within the mesh cell rather than at the interface. It is shown that new schemes of high fidelity for both continuous and discontinuous solutions can be devised by the BVD guideline with properly-chosen candidate reconstruction schemes. Excellent numerical results have been obtained for both scalar and Euler conservation laws with substantially improved solution quality in comparison with the existing methods. This work provides a simple and accurate alternative of great practical significance to the current Godunov paradigm which overly pursues the smoothness within mesh cell under the questionable premiss that discontinuities only appear at cell interfaces.

physics.comp-ph↗

CIP/multi-moment finite volume method with arbitrary order of accuracy

This paper presents a general formulation of the CIP/multi-moment finite volume method (CIP/MM FVM) for arbitrary order of accuracy. Reconstruction up to arbitrary order can be built on single cell by adding extra derivative moments at the cell boundary. The volume integrated average (VIA) is updated via a flux-form finite volume formulation, whereas the point-based derivative moments are computed as local derivative Riemann problems by either direct interpolation or approximate Riemann solvers.

physics.comp-ph↗