Region based Image Steganalysis using Artificial Bee Colony

Steganalysis is the art and skill of discriminating stego images from cover images. Image steganalysis algorithms can be divided into two broad categories, specific and universal. In this paper, a novel universal image steganalysis algorithm is proposed which is called RISAB, Region based Image Steganalysis using Artificial Bee colony. The goal of the proposed method is to realize a sub-image from stego and cover images through ABC with respect to density according to the cover, stego and difference images. In our method, we look for the best sub-image, which contains the highest density with respect to the changed embedding pixels. Furthermore, after selecting the best sub-image, we extract the features, which have been selected by IFAB, Image steganalysis based on Feature selection using Artificial Bee colony. At the end, both selected features by IFAB and extracted features by RISAB are combined. As a result, a feature vector is generated which improves accuracy of steganalysis. Experimental results show that our proposed method outperforms other approaches.     

基于混合人工蜂群策略的改进DV-Hop定位算法

为了减小DV-Hop算法在无线传感器网络节点定位中的误差,提出了一种基于混合人工蜂群算法的改进算法。该算法结合了粒子群算法收敛速度快和蜂群算法搜索能力强的特性,首先通过DV-Hop算法估计锚节点与未知节点之间的距离,然后采用粒子群算法计算未知节点的初始位置,最后利用蜂群算法进行迭代求精,从而实现基于不同距离测量方法的总体优化。仿真结果表明,改进算法的定位精度较DV-Hop算法和基于粒子群的定位算法有明显改善。     

基于人工蜂群算法的中继卫星任务调度研究

研究中继卫星任务调度问题可以为跟踪与数据中继卫星系统(TDRSS)的任务计划编排提供科学合理的决策方法,任务调度模型的建立与调度算法的设计是中继卫星任务调度的两个关键问题。该文针对中继卫星任务调度问题特点,综合考虑中继卫星与用户航天器之间具有可见时间窗、用户提交的任务属性、中继卫星前向资源受限等约束条件,建立了中继卫星任务调度约束规划模型并提出基于人工蜂群(ABC)算法的中继卫星任务调度算法。最后,通过仿真数据分析,表明基于人工蜂群算法的中继卫星任务调度算法是一种有效的、合理的调度方法。     

A unified enhanced particle swarm optimization‐based virtual network embedding algorithm

Virtual network (VN) embedding is a major challenge in network virtualization. In this paper, we aim to increase the acceptance ratio of VNs and the revenue of infrastructure providers by optimizing VN embedding costs. We first establish two models for VN embedding: an integer linear programming model for a substrate network that does not support path splitting and a mixed integer programming model when path splitting is supported. Then we propose a unified enhanced particle swarm optimization‐based VN embedding algorithm, called VNE‐UEPSO, to solve these two models irrespective of the support for path splitting. In VNE‐UEPSO, the parameters and operations of the particles are well redefined according to the VN embedding context. To reduce the time complexity of the link mapping stage, we use shortest path algorithm for link mapping when path splitting is unsupported and propose greedy k‐shortest paths algorithm for the other case. Furthermore, a large to large and small to small preferred node mapping strategy is proposed to achieve better convergence and load balance of the substrate network. The simulation results show that our algorithm significantly outperforms previous approaches in terms of the VN acceptance ratio and long‐term average revenue. Copyright © 2012 John Wiley & Sons, Ltd.     

时间和能量感知的贝叶斯虚拟网映射

针对虚拟网的节能映射问题,建立了结合时间和能量感知的虚拟网映射算法。在对节点和路径的评价标准中加入了时间因素,综合考虑了物理资源的运行时间等因素,用概率理论辅助分析了每个虚拟节点的多个可用物理节点被选中的概率。在节点选择阶段,综合考虑底层节点的剩余资源量、CPU资源利用率增量、节点开启情况和是否延长使用时间等因素,并使用条件概率理论辅助分析得到各可用节点的重要性;在链路选择阶段,综合考虑链路开启情况、延长使用时间和链路长度等因素。不仅使虚拟网请求映射在当前较小的节点和链路集合中,而且映射到了延长时间较短的设备上。实验结果表明,与未考虑时间因素的方法相比,该方法能带来更好的性能和更低的能耗。     

Energy efficient virtual network embedding for federated software‐defined networks

In this paper, we focus on energy efficient virtual network embedding in federated (multidomain) software‐defined networks (SDNs). We first formulate an optimization problem as an integer linear program (ILP) that minimizes the energy consumption of the network links, while at the same time adhering to the bandwidth and CPU requirements of the virtual network requests. We then propose a polynomial‐time heuristic algorithm, which consists of three stages. In the first stage, the top SDN controller decides on whether to partition the virtual network request into smaller subrequests and give subrequests to multiple domains or give the enitre virtual network request to a single domain, while in the second stage, each SDN controller implements virtual network embedding in its own domain. Finally, in the third stage, the algorithm performs interdomain routing if partitioning decision had been made in the first stage. Our simulation results demonstrate that our proposed algorithm yields close performance to the solutions obtained by using the optimization software CPLEX that implements our ILP.     

一种强鲁棒性的盲分离混合矩阵估计方法

针对传统盲分离混合矩阵估计鲁棒性差、易受初始值影响、精度不高等问题,该文将人工蜂群算法(ABC)用到盲分离中,结合稀疏信号混合矩阵估计的特点,提出一种基于不同搜索策略和编码方式的两阶段蜂群算法的混合矩阵估计方法,通过新的蜜蜂搜索行为和子蜂群之间的协同作业,明显加快了算法的收敛速度,提高了混合矩阵的估计精度。仿真实验表明,该方法在源个数较多、弱稀疏、低信噪比的情况下仍然可以很好地估计混合矩阵。相比已有方法,该方法不仅具有很强的鲁棒性和很高的估计精度,而且不需要太大的计算量。     

一种光虚拟专用网管理实现方案

光虚拟专用网(OVPN)是自动交换光网络(ASON)的一种新兴的增值业务,ASON控制平面使得OVPN的实现更加灵活。文章对OVPN的管理方案进行分析,提出了一种基于WBEM(Web-based enterprise management)的管理体系结构,并对OVPN 的通用信息模型(Common Information Model)进行了分析设计。     

Synthesis of satellite footprint patterns from rectangular planar array antenna by using swarm‐based optimization algorithms

A pattern synthesis method based on Firefly Algorithm (FA) and Artificial Bee Colony (ABC) optimization has been presented to generate satellite footprint patterns from a rectangular planar array of isotropic antennas by modifying the amplitude, phase, and the state of the array elements. Three cases comprising three different footprints of rectangular, square, and circular boundary are generated from the same array by using two different swarm‐based optimization algorithms FA and ABC. Both the algorithms, following the proposed procedures are able to generate the three different footprint patterns while maintaining a satisfactory lower peak side lobe level and ripple. A comparative analysis has been carried out between FA, ABC, and Genetic Algorithm (GA) for the presented problem in terms of fitness value for the three different cases. The superiority of FA and ABC over GA has been established in terms of finding better solutions for all the three cases of the proposed problem. Copyright © 2013 John Wiley & Sons, Ltd.     

WDM-PON中基于AWG的新型OVPN研究

在波分复用无源光网络(WDM-PON)中,提出了一种基于阵列波导光栅(AWG)的新型光虚拟专用网(OVPN)。OVPN采用环形结构,在不同光网络单元(ONU)之间使用波长通道直接通信,不仅保证了ONU之间通信的安全性,而且提高了网络生存性。分别从光功率损耗和系统误码率(BER)进行了数值分析,结果表明,本文结构不仅增加了通信的安全性,而且仅使用4个波长就能实现16个ONU的相互联接,从而节省了波长资源,且具有很强的抗串扰能力。     

基于显卡的微带天线谐振频率神经网络建模

谐振频率是微带天线(Microstrip Antennas,MSA)设计过程中最重要的一个参数.针对粒子群神经网络(Particle Swarm Optimization-Neural Network,PSO-NN)对矩形MSA谐振频率建模所面临的计算时间过长以及模型精度不高等问题,提出一种基于图形处理单元(Graphic Processing Unit,GPU)技术的并行处理解决方案.该方法使用粒子与线程一一对应的并行策略,通过并行处理各个粒子的计算过程来加快整个粒子群的收敛速度,从而减少NN的训练时间.在统一计算设备架构下对矩形MSA谐振频率进行了PSO-NN建模,数值计算结果表明:相对于CPU端串行PSO-NN,GPU端并行PSO-NN在寻优稳定性一致的前提下取得了超过300倍的计算加速比;在GPU端大幅增加粒子数,能在运行时间增加极为有限的情况下大幅降低建模的网络误差.     

An adaptive network traffic prediction approach for LDoS attacks detection

Low‐rate denial of service (LDoS) attacks reduce throughput and degrade quality of service (QoS) of network services by sending out attack packets with relatively low average rate. LDoS attack flows are difficult to detect from normal traffic since it has the property of low average rate. The research on network traffic analysis and modeling shows that network traffic measurement data are irregular nonlinear time series. To characterize and analyze network traffic between attack and non‐attack situations, the adaptive normal and abnormal ν‐support vector regression (ν‐SVR) prediction models are constructed on the basis of the reconstructed phase space. In this paper, the dimension of reconstructed phase space for ν‐SVR is optimized by Bayesian information criteria method, and the parameter in the radial basis function is adaptively adjusted by minimizing the within‐class distance and maximizing the between‐class distance in the feature space. The nonthreshold decision function is obtained through calculating the prediction error of adaptive normal and abnormal ν‐SVR prediction models, which is adopted to detect LDoS attacks. Experiments in NS‐2 environment show that the adaptive ν‐SVR prediction model can effectively predict the network traffic measurement time series, and the probability distribution of time series generated by the adaptive ν‐SVR prediction model is quite similar to that of the network traffic measurement data. Experiments also clearly demonstrate the superiority of the proposed approach in LDoS attacks detection.     

A new feature extraction and attacking node classification framework using PDCFE‐HPSMM model in cognitive radio networks

The increasing demand of wireless communication introduces a challenge to an effective spectrum utilization. In wireless communication systems, the Cognitive Radio (CR) has emerged as a new key technology to address this issue, which allows an opportunistic access to the spectrum. The CRs form a CRN by extending the radio link features to network layer functions. The existing CR based wireless communication techniques has some drawbacks such as, inability to differentiate interference or noise from primary signals, it does not distinguish the different types of noise, low performance, not effective in spread spectrum detection, long observation time and high computational cost. To overwhelm these disadvantages, a novel method, namely, partial distribution based cyclostationary feature extraction–hidden probability state Markov model (PDCFE‐HPSMM) is proposed in this work. The main intention of this technique is to extract the node features, classify the attacker nodes and predict the licensed and unlicensed bandwidth. At first, the CRN is formed with some set of CR nodes, and the communication links between the nodes are estimated. Then, the node features are extracted by employing the PDCFE technique. After that, the attacking nodes are classified based on those features with the help of a HPSMM classification technique. If the attacker is present in the network, the link between the attacking nodes to other nodes is disconnected; otherwise, the communication link is updated. In this work, the Rayleigh channels are used to predict the licensed and unlicensed bandwidth. Again, the HPSMM model is employed to optimally select the channel, and the scheduling technique is implemented to check the status of the channel for message transmission. If the channel is not busy, the message signals are multiplexed and transmitted to the receiver via the selected channel. The novel concept of this paper is, the proposed PDCFE technique extracts the features of the nodes in CRN; based on these features, the attacker nodes in the network are classified with the help of HPSMM technique. Moreover, the HPSMM is used to select the optimal channel for message transmission. The experimental results evaluate the performance of the proposed system in terms of bit error rate (BER), error rate, relay, false detection rate (FDR) and cumulative distribution function (CDF). Copyright © 2016 John Wiley & Sons, Ltd.     

OCDMA系统中一种新的多倍长光垂直码

提出了一种新的容量大、相关性好的多倍长、多波长二维光正交码（2D MW-OOC），基于多倍长一维光正交码（1DOOC）构造了MW-OOC。对同时使用具有2种码长的MW-OOC的光码分多址（OCD-MA）系统性能分析表明，使用该MW-OOC的系统性能良好，明显好于同样码长下的多倍长1-DOOC；使用短码序列的信号误码率性能好于使用长码序列信号的误码率性能。这些特征能充分发挥OCDMA系统大容量的技术优势，满足将来大容量多媒体OcDMA网络系统对同时传输的不同信号所需传输质量不同的需求。     

A new and efficient approach for estimating the accurate time-domain response of single and capacitive coupled distributed RC interconnects

This paper describes a novel yet highly efficient approach for estimating the time-domain response of capacitive coupled distributed RC interconnects. By using this method, the voltage signal at any particular point in such wires can be accurately and quickly obtained with very low computational cost. The proposed model exhibits a very good agreement with HSPICE simulations with worst-case error less than 3% and can be readily implemented in CAD analysis tools. This paper also presents an efficient model to estimate the capacitive crosstalk in high-speed very large scale integration (VLSI) circuits. Experimental results show that the maximum error of our peak noise predictions is less than 2.5%. In addition, this work presents an efficient artificial neural network (ANN)-based technique for modeling the time-domain response of interconnects and crosstalk noise. While existing fast noise estimation metrics may overestimate or underestimate the coupling noise, the simulation results demonstrate the ability of this approach to successfully predict coupling noise with a very good accuracy as compared to HSPICE in modest CPU times. Thereby, the proposed models and techniques can be used to predict the signal integrity for designing high-speed and high-density VLSI circuits.