MABP: an optimal resource allocation approach in data center networks

In data center networks, resource allocation based on workload is an effective way to allocate the infrastructure resources to diverse cloud applications and satisfy the quality of service for the users, which refers to mapping a large number of workloads provided by cloud users/tenants to substrate network provided by cloud providers. Although the existing heuristic approaches are able to find a feasible solution, the quality of the solution is not guaranteed. Concerning this issue, based on the minimum mapping cost, this paper solves the resource allocation problem by modeling it as a distributed constraint optimization problem. Then an efficient approach is proposed to solve the resource allocation problem, aiming to find a feasible solution and ensuring the optimality of the solution. Finally, theoretical analysis and extensive experiments have demonstrated the effectiveness and efficiency of our proposed approach.     

关于可信软件开发的若干问题思考

在信息科学时代,现代社会的发展日益依赖软件,实现可信软件的开发在一定程度上契合现代社会的需求,也是自身发展的内部需求。但是,可信软件的开发是一个系统而复杂的过程,强调可信软件开发中各方工作的有效落实。本文分析了可信软件的研究现状,阐述了软件架构与开发,并基于此,论述了强化软件架构,开发可信软件的若干建议。本文旨在强化对可信软件的认识,并为今后相关领域的研究提供一定的参考资料。     

Adaptive neural network control for a class of continuous stirred tank reactor systems

In this paper, the control problem of continuous stirred tank reactors （CSTR） is studied. The considered CSTR are required to contain unknown functions and unknown dead zone input. An adaptive controller that uses the neural networks （NNs） is provided to solve the unknown terms. The proposed approach overcomes the effect of the dead zone input. The dead zone input in the systems is compensated for by introducing a new Lyapunov form and Young＇s inequality. The backstepping procedure is exploited to implement controller design with adaptation laws. The stability is analyzed using Lyapunov method. The performance is examined for CSTR to confirm the effectiveness of the proposed approach based on computer simulation.     

Variable partial-update NLMS algorithms with data-selective updating

We note that some existing algorithms are based on the normalized least-mean square （NLMS） algorithm and aim to reduce the computational complexity of NLMS all inherited from the solution of the same optimization problem, but with different constraints. A new constraint is analyzed to substitute an extra searching technique in the set-membership partial-update NLMS algorithm （SM-PU-NLMS） which aims to get a variable number of updating coefficients for a further reduction of computational complexity. We get a closed form expression of the new constraint without extra searching technique to generate a novel set-membership variable-partial-update NLMS （SM-VPU-NLMS） algorithm. Note that tile SM-VPU-NLMS algorithm obtains a faster convergence and a smaller mean-squared error （MSE） than the existing SM-PU-NLMS. It is pointed out that the closed form expression can also be applied to the conventional variable-step-size partial-update NLMS （VSS-PU-NLMS） algorithm. The novel variable-step-size variable-partial-update NLMS （VSS-VPU-NLMS） algorithm is also verified to get a further computational complexity reduction. Simulation results verify that our analysis is reasonable and effective.     

Joint optimal sensing time and power allocation for multi-channel cognitive radio networks considering sensing-channel selection

In this paper,we consider a multi-channel cognitive radio network(CRN)where each secondary user(SU)can only choose to sense a subset of channels.We formulate a joint optimization problem of sensingchannel selection,sensing time and power allocation under the constraints of average transmit power budget and average interference power budget,which maximizes the CRN’s total throughput.We propose a greedy algorithm to solve the joint optimization problem,which has much less computational complexity.Moreover,it is shown that the search space of the greedy algorithm can be further pruned.Finally,numerical results demonstrate that the greedy algorithm has comparable performance to the exhaustive search algorithm.     

有关网银系统的信息安全问题与措施探索

近年来,我国网上银行的业务量增长迅速,越来越多的商务交易通过网银来实现,由于网络存在缺陷,进而导致针对网银的犯罪情态日益严重,网银的安全问题十分突出,这给网络银行的正常运行造成了一定程度的影响,严重损害了网银的根本利益,阻碍了网上银行的稳定、健康发展。本文主要针对我国网银安全问题进行探讨,阐述了我国网银发展的现状,并提出了几点措施,以有效加固网银安全,降低网银的风险,不断推动网上银行的健康发展。     

基于AJAX和X3D的虚拟场景交互架构研究

针对X3D的web应用中用户与三维物体的交互仅局限于浏览器端的三维场景之中不能操作存在于服务器端的特定三维物体,结合AJAX技术,提出一个AJAX和X3D结合的场景交互架构,通过一个应用实例给出了AJAX和X3D结合的场景交互实现方法.该场景交互架构很好地解决了三维场景与服务器端的通信问题.     

基于FPGA的串口控制器设计与实现

为了解决只带有串口的设备不易组网的问题,提出了一种基于FPGA的通用型串口控制器的设计方法,给出了串口控制器总体设计.该设计能方便地独立修改各个串口的结构和参数,满足不同设备通过串口组网的要求.     

基于参数测量法的液压故障诊断系统

针对液压系统的战场抢修问题,提出了通过关键点测量系统压力,流量及油液污染度来诊断液压系统故障的方法,给出了系统组成及测试方法,并结合实例进行了故障诊断分析.     

自适应递归神经网络混合控制裹包同步机伺服系统

根据裹包机的驱动系统控制精度较差的问题,提出采用自适应递归神经网络混合控制线性同步电动器驱动机系统。仿真结果表明,该控制系统克服了上述缺点。