共查询到20条相似文献,搜索用时 15 毫秒
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The vehicular cloud computing is an emerging technology that changes vehicle communication and underlying traffic management applications. However, cloud computing has disadvantages such as high delay, low privacy and high communication cost, which can not meet the needs of real-time interactive information of Internet of vehicles. Ensuring security and privacy in Internet of Vehicles is also regarded as one of its most important challenges. Therefore, in order to ensure the user information security and improve the real-time of vehicle information interaction, this paper proposes an anonymous authentication scheme based on edge computing. In this scheme, the concept of edge computing is introduced into the Internet of vehicles, which makes full use of the redundant computing power and storage capacity of idle edge equipment. The edge vehicle nodes are determined by simple algorithm of defining distance and resources, and the improved RSA encryption algorithm is used to encrypt the user information. The improved RSA algorithm encrypts the user information by reencrypting the encryption parameters . Compared with the traditional RSA algorithm, it can resist more attacks, so it is used to ensure the security of user information. It can not only protect the privacy of vehicles, but also avoid anonymous abuse. Simulation results show that the proposed scheme has lower computational complexity and communication overhead than the traditional anonymous scheme. 相似文献
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One of the most ambitious technological goals is the development of devices working under the laws of quantum mechanics. Among others, an important challenge to be resolved on the way to such breakthrough technology concerns the scalability of the available Hilbert space. Recently, proof‐of‐principle experiments were reported, in which the implementation of quantum algorithms (the Grover's search algorithm, iSWAP‐gate, etc.) in a single‐molecule nuclear spin qudit (with d = 4) known as 159TbPc2 was described, where the nuclear spins of lanthanides are used as a quantum register to execute simple quantum algorithms. In this progress report, the goal of linear and exponential up‐scalability of the available Hilbert space expressed by the qudit‐dimension “d” is addressed by synthesizing lanthanide metal complexes as quantum computing hardware. The synthesis of multinuclear large‐Hilbert‐space complexes has to be carried out under strict control of the nuclear spin degree of freedom leading to isotopologues, whereby electronic coupling between several nuclear spin units will exponentially extend the Hilbert space available for quantum information processing. Thus, improved multilevel spin qudits can be achieved that exhibit an exponentially scalable Hilbert space to enable high‐performance quantum computing and information storage. 相似文献
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针对正交频分复用(Orthogonal Frequency Division Multiplexing, OFDM)水声通信中常用的相干和非相干通信分别面临的对多普勒敏感和频谱效率低的问题,提出一种高阶幅度键控调制的半相干通信技术,将OFDM符号时频帧结构中全部频点采用高阶幅度键控调制方式,并利用信号幅度信息完成半相干信道估计。通过两种基于深度学习的算法优化半相干信道估计这一非线性过程,较非相干通信有效提高了频谱效率,较一定信噪比下的相干通信提高了鲁棒性,降低了误比特率和系统复杂度,并利用元学习算法降低深度学习算法对训练数据的依赖。最后,提取海试信道数据,完成OFDM半相干水声通信系统仿真,验证了所提方法在频谱效率和系统误比特率性能方面较非相干和相干通信的优势,当信道长度改变时,基于元学习的算法依然可以获得较好的性能。 相似文献
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We propose a statistical phase-shifting estimation algorithm for temporal phase-shifting interferometry (PSI) based on the continuous wavelet transform (CWT). The proposed algorithm explores spatial information redundancy in the intraframe interferogram dataset using the phase recovery property on the power ridge of the CWT. Despite the errors introduced by the noise of the interferogram, the statistical part of the algorithm is utilized to give a sound estimation of the phase-shifting step. It also introduces the usage of directional statistics as the statistical model, which was validated, so as to offer a better estimation compared with other statistical models. The algorithm is implemented in computer codes, and the validations of the algorithm were performed on numerical simulated signals and actual phase-shifted moiré interferograms. The major advantage of the proposed algorithm is that it imposes weaker conditions on the presumptions in the temporal PSI, which, under most circumstances, requires uniform and precalibrated phase-shifting steps. Compared with other existing deterministic estimation algorithms, the proposed algorithm estimates the phase-shifting step statistically. The proposed algorithm allows the temporal PSI to operate under dynamic loading conditions and arbitrary phase steps and also without precalibration of the phase shifter. The proposed method can serve as a benchmark method for comparing the accuracy of the different phase-step estimation methods. 相似文献
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The authors evaluate the improved energy and spectral efficiency by pilot overhead reduction of turbo coded orthogonal frequency division multiplexing (OFDM) systems employing an iterative phase estimation algorithm. Developed from the recently proposed iterative phase estimation schemes, the phase estimation and compensation process is embedded into the basic iterative turbo decoding process for the application to OFDM systems with just a slight complexity overhead. At each decoding iteration, sub-carrier phase rotations are estimated from the extrinsic information arranged in each sub-carrier and are compensated for the next decoding iteration. This enables the iterative phase estimation algorithm to successfully work under very low signal-to-noise ratios even without pilot symbols. The pilot symbols are just very rarely inserted only for breaking the erroneous phase estimation propagation frame to frame in case of large residual phase offset beyond reliable decoding range. Simulation results show that the iterative phase estimation algorithm drastically reduces the pilot insertion overhead and thus, it achieves improved spectral efficiency as well as bit error rate (BER) performance by saving pilot energy compared to the conventional method. 相似文献
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Iftikhar Ahmad Ambreen Shahnaz Muhammad Asfand-e-Yar Wajeeha Khalil Yasmin Bano 《计算机、材料和连续体(英文)》2023,74(1):279-293
The demand for cloud computing has increased manifold in the recent past. More specifically, on-demand computing has seen a rapid rise as organizations rely mostly on cloud service providers for their day-to-day computing needs. The cloud service provider fulfills different user requirements using virtualization - where a single physical machine can host multiple Virtual Machines. Each virtual machine potentially represents a different user environment such as operating system, programming environment, and applications. However, these cloud services use a large amount of electrical energy and produce greenhouse gases. To reduce the electricity cost and greenhouse gases, energy efficient algorithms must be designed. One specific area where energy efficient algorithms are required is virtual machine consolidation. With virtual machine consolidation, the objective is to utilize the minimum possible number of hosts to accommodate the required virtual machines, keeping in mind the service level agreement requirements. This research work formulates the virtual machine migration as an online problem and develops optimal offline and online algorithms for the single host virtual machine migration problem under a service level agreement constraint for an over-utilized host. The online algorithm is analyzed using a competitive analysis approach. In addition, an experimental analysis of the proposed algorithm on real-world data is conducted to showcase the improved performance of the proposed algorithm against the benchmark algorithms. Our proposed online algorithm consumed 25% less energy and performed 43% fewer migrations than the benchmark algorithms. 相似文献
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在多波束测深声呐的工作环境中,若海底反向散射信号不满足点源假设,方位估计精度将严重下降,而基于分布源模型的方位估计算法可以适应这种环境。目前,大多数分布源算法要求分布源之间不相干,有人提出采用Toeplitz方法估计相干分布源,但该方法精度不高并且忽略了角度扩展参数。为解决多波束测深声呐相干分布源的方位估计问题,提出了基于空间平滑的广义MUSIC方法,公式推导证明了算法的有效性,通过计算机仿真给出算法方位估计的精度以及不同信噪比条件下的性能,最后采用多波束测深系统的实验数据对算法进行了验证。 相似文献
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As an important branch of machine learning, clustering analysis is widely used
in some fields, e.g., image pattern recognition, social network analysis, information
security, and so on. In this paper, we consider the designing of clustering algorithm in
quantum scenario, and propose a quantum hierarchical agglomerative clustering
algorithm, which is based on one dimension discrete quantum walk with single-point
phase defects. In the proposed algorithm, two nonclassical characters of this kind of
quantum walk, localization and ballistic effects, are exploited. At first, each data point is
viewed as a particle and performed this kind of quantum walk with a parameter, which is
determined by its neighbors. After that, the particles are measured in a calculation basis.
In terms of the measurement result, every attribute value of the corresponding data point
is modified appropriately. In this way, each data point interacts with its neighbors and
moves toward a certain center point. At last, this process is repeated several times until
similar data points cluster together and form distinct classes. Simulation experiments on
the synthetic and real world data demonstrate the effectiveness of the presented algorithm.
Compared with some classical algorithms, the proposed algorithm achieves better
clustering results. Moreover, combining quantum cluster assignment method, the
presented algorithm can speed up the calculating velocity. 相似文献
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Cloud computing is currently dominated within the space of high-performance distributed computing and it provides resource polling and on-demand services through the web. So, task scheduling problem becomes a very important analysis space within the field of a cloud computing environment as a result of user's services demand modification dynamically. The main purpose of task scheduling is to assign tasks to available processors to produce minimum schedule length without violating precedence restrictions. In heterogeneous multiprocessor systems, task assignments and schedules have a significant impact on system operation. Within the heuristic-based task scheduling algorithm, the different processes will lead to a different task execution time (makespan) on a heterogeneous computing system. Thus, a good scheduling algorithm should be able to set precedence efficiently for every subtask depending on the resources required to reduce (makespan). In this paper, we propose a new efficient task scheduling algorithm in cloud computing systems based on RAO algorithm to solve an important task and schedule a heterogeneous multiple processing problem. The basic idea of this process is to exploit the advantages of heuristic-based algorithms to reduce space search and time to get the best solution. We evaluate our algorithm's performance by applying it to three examples with a different number of tasks and processors. The experimental results show that the proposed approach significantly succeeded in finding the optimal solutions than others in terms of the time of task implementation. 相似文献
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快速傅里叶变换(Fast Fourier Transform,FFT)常用于信号频率估计,采用填零的方法可降低幅度谱频率搜索间隔的量化误差,但是会使频率估计的计算量成倍增加。本文提出了一种FFT幅相联合的快速高精度频率估计算法,首先利用信号采样的频谱序列和尾首样本差确定幅度谱及峰值位置,然后由频谱序列在幅度谱峰值位置和信号采样的尾首样本差来确定频率搜索间隔的量化误差校正值。因此,所提方法同时利用了幅度谱峰值的位置信息与相位信息。分析结果表明,与仅基于幅度谱搜索的FFT算法相比,所提方法的计算复杂度更低,且定位精度更高。 相似文献
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After Google reported its realization of quantum supremacy, Solving the classical problems with quantum computing is becoming a valuable research topic. Switching function minimization is an important problem in Electronic Design Automation (EDA) and logic synthesis, most of the solutions are based on heuristic algorithms with a classical computer, it is a good practice to solve this problem with a quantum processer. In this paper, we introduce a new hybrid classic quantum algorithm using Grover’s algorithm and symmetric functions to minimize small Disjoint Sum of Product (DSOP) and Sum of Product (SOP) for Boolean switching functions. Our method is based on graph partitions for arbitrary graphs to regular graphs, which can be solved by a Grover-based quantum searching algorithm we proposed. The Oracle for this quantum algorithm is built from Boolean symmetric functions and implemented with Lattice diagrams. It is shown analytically and verified by simulations on a quantum simulator that our methods can find all solutions to these problems. 相似文献
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基于模糊支持度的分布式多传感器加权融合算法 总被引:1,自引:0,他引:1
针对目前分布式多传感器数据融合算法中鲁棒性和实时性问题,基于充分利用多传感器测量数据中互补和冗余信息的思想,通过局部状态估计精度间支持度函数的建立和支持度矩阵的求解,合理地分配各局部航迹估计在融合中心的权重,进而提出了一种基于模糊支持度的分布式多传感器加权融合算法.最后,通过蒙特卡罗仿真验证了该算法的有效性. 相似文献
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在《与荷载同步变化的时间步自动调整方法》中提出的时间步自动调整方法(apriori time adaptive method,ATAM)是先验式误差评估研究领域的一次有益尝试。在ATAM使用过程中,由于一般情况下难以获得解析解,所以对数值计算程序应用ATAM自动调整时间步长后,相比时间步调整前,无法评估计算效率具体提高了多少。为了解决这个问题,提出了解决方法并对其进行了验证。在此基础上,进一步提出了一种简易评估算法,并推导出评估计算效率提高程度的计算公式。根据此计算公式,不需要采用最小时间步长代入到原数值程序中进行计算,可直接获得计算效率的提高程度,节省了大量计算成本。同时,对简易评估算法进行了验证,结果证实所提算法实用有效。 相似文献
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一种低计算复杂度的无线传感器网络分簇定位算法 总被引:1,自引:0,他引:1
针对已有的集中式定位算法定位精度低,而分布式定位算法计算复杂度高、通信量大的问题,提出了一种适用于无线传感器网络的计算复杂度低的节点分簇定位算法.首先,提出满足最大连通度的多边界节点分簇算法,采用此算法把网络划分为若干个簇,各簇分别进行簇内节点定位;其次,各簇进行融合,最终实现全网节点的定位.仿真结果表明,这种分簇定位算法比分布式定位算法计算复杂度低、通信量小、定位精度相当或略差,比集中式定位算法计算复杂度低、通信量小、定位精度高.采用该算法可以降低传感器网络节点定位过程中的能耗,提高计算效率,延长网络寿命. 相似文献
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Host cardinality estimation is an important research field in network
management and network security. The host cardinality estimation algorithm based on
the linear estimator array is a common method. Existing algorithms do not take memory
footprint into account when selecting the number of estimators used by each host. This
paper analyzes the relationship between memory occupancy and estimation accuracy and
compares the effects of different parameters on algorithm accuracy. The cardinality
estimating algorithm is a kind of random algorithm, and there is a deviation between the
estimated results and the actual cardinalities. The deviation is affected by some
systematical factors, such as the random parameters inherent in linear estimator and the
random functions used to map a host to different linear estimators. These random factors
cannot be reduced by merging multiple estimators, and existing algorithms cannot
remove the deviation caused by such factors. In this paper, we regard the estimation
deviation as a random variable and proposed a sampling method, recorded as the linear
estimator array step sampling algorithm (L2S), to reduce the influence of the random
deviation. L2S improves the accuracy of the estimated cardinalities by evaluating and
remove the expected value of random deviation. The cardinality estimation algorithm
based on the estimator array is a computationally intensive algorithm, which takes a lot of
time when processing high-speed network data in a serial environment. To solve this
problem, a method is proposed to port the cardinality estimating algorithm based on the
estimator array to the Graphics Processing Unit (GPU). Experiments on real-world highspeed network traffic show that L2S can reduce the absolute bias by more than 22% on
average, and the extra time is less than 61 milliseconds on average. 相似文献