基于复杂网络的软件体系结构复杂性度量方法

介绍了复杂网络理论及软件体系结构复杂性度量思想,提出借助复杂网络理论来进行软件体系结构复杂性度量,给出了具体度量过程和算法,最后对提出的度量算法通过实例进行验证.     

基于复杂网络的软件复杂性度量研究

软件开发者对于日趋复杂的软件系统的理解和控制越来越困难，传统软件工程正接近其复杂性和可扩展性的极限．复杂性使软件开发困难，质量难以保证．复杂网络理论的最新研究成果，为软件复杂性度量提供了新的数学基础．讨论了软件复杂性的形成原因和度量方法，介绍了目前复杂网络与软件复杂性结合的研究工作．探讨了基于复杂网络的软件结构复杂性度量方法，提出一种结合复杂网络和演化算法的软件演化复杂性度量模型．     

基于复杂网络的JDK代码结构演化研究

软件系统日趋大型化和复杂化使得软件系统的结构可以用复杂网络来表示,研究表明,大规模软件系统结构表现出复杂网络的各项特征如小世界效应和无标度特性等,复杂网络成为理解软件系统结构和演化的重要方法之一.本文定义了一种针对Java程序的网络拓扑图,为JDK构造复杂网络,并统计其度分布标度指数、平均距离、平均簇系数等网络特征.同时研究这些特征随JDK版本的变化,提出了一个基于模块的演化模型,并对JDK的版本演化进行模拟.实验结果表明JDK具有复杂网络的各项特征,是一个复杂网络,并且与一般复杂网络的演化模型不同,其演化模型具有软件系统的特征--模块化,能与软件系统演化的实际相符合.     

COSMIC-FFP模型对大型软件的规模评估

阐述了一种基于传统的IFPUG-FPA方法的演进规模估计模型--COMSIC-FFP模型。分别详细分析了它的软件度量过程模型原理和度量方法:将软件系统转换成为软件功能模型,进而使用度量系统将软件的功能点量化,最终得到表示软件大小的数值表示。这个模型可以使得软件功能点划分的标准更加灵活,对软件内部的结构和实现依赖更小,使得功能过程定义更加细致,其中包含的功能点也更加具体和单一。能够极大提高对复杂大型软件系统规模估计的准确度。     

软件体系结构的复杂网络社团特性研究

作为系统设计的高层抽象和系统实现的蓝图,SA体现了系统的基本思想和系统开发的早期决策.对所开发系统的SA结构的复杂网络社团特性研究,是了解整个系统的网络结构和功能特征的重要途径.介绍了复杂网络及复杂网络社团理论和方法,提出借助复杂网络社团思想进行SA复杂网络社团特性度量.将SA结构转化为复杂网络模型,并通过SA的模块度、SA的层次性及SA的重叠性等来进行SA结构的复杂网络社团特性研究.最后,通过实例对所提出的研究思路进行验证.实践表明,此方法能较好地对所开发系统的SA结构的复杂网络社团特性进行评估及度量,为系统后续开发等工作提供依据.     

基于多粒度软件网络模型的软件系统演化分析

软件系统是一类典型的人工参与的复杂系统,理解软件系统的演化规律有助于更好地指导软件工程实践.本文从包、类和特征三个粒度上构建软件系统的网络模型,利用复杂网络理论依次从网络规模、质量、结构控制三方面定量分析软件系统演化规律.以经典的Lehman演化定律为基准,对比软件系统在不同粒度下的演化差异.研究结果表明：（1）不同粒度下软件系统表现出的演化特性有所不同,其中在类粒度下效果更好;（2）持续增长、持续变化、自我调节和主体维持四项定律表现出与构建软件网络的粒度无关;（3）包粒度下系统演化对软件质量影响不大,而反馈系统定律仅在类粒度下成立.     

基于UML的卫星通信对抗训练系统导控软件设计

提出一种基于UML的卫星通信对抗训练系统导控软件设计方法,分析了软件系统的功能需求,给出了软件系统的用例图、类图、活动图和时序图。实践证明:基于UML的软件设计方法能够降低系统开发难度、提高开发效率。     

财务核算软件系统设计用例的构建研究

本文通过对财务核算软件系统的设计用例进行分析,包括系统各模块详细用例图的介绍和设计,并详细列出了各个模块的用例图,明确的展示出了财务核算软件系统用例的构建形成,为构建财务核算软件系统实现了系统的用例分析和设计,确保软件的构建可行。     

相似网络构建与表征的水下声信号检测

水下声信号检测在海洋防御系统中扮演着不可或缺的角色,同时也广泛应用于民用领域。然而,在没有目标信号先验信息的情况下,目前仍缺乏行之有效的水下声信号检测方法。为此,该文提出了一种新的算法—相似网络,以解决在复杂海洋背景下水下目标检测的难题。该方法结合了信息几何和复杂网络理论,通过将节点相似度度量问题转化为矩阵流形上的几何问题,测量不同时间尺度上数据之间的相似性,并构建时间序列数据的网络表示。同时还引入了图信号处理理论,以提取目标信号内部隐藏的动力学特性,从而实现无目标先验信息下的水下声信号检测。通过对仿真和实测数据的研究验证,证明了该方法的有效性。结果表明,相似网络方法优于现有的网络构建和目标信号被动检测方法,能够更有效地检测水下声信号,实现无目标先验信息下的水下声信号检测。     

基于复杂网络的天基预警系统模型映射及抗毁性分析

作为国家军事防御体系的一个重要组成部分,天基预警系统能够在维护国家安全和获取潜在目标威胁等方面发挥重要作用。因此,对天基预警系统的系统网络进行建模和分析成为认识系统网络和衡量系统性能的重要方法。基于此,文章提出了基于复杂网络理论的天基预警系统抽象映射和抗毁性分析方法,以完成对网络拓扑图的构建,获取系统网络的特征信息以及不同攻击模式下抗毁性变化情况等。     

软件定义传感器网络重配置算法研究

为了提高无线传感器网络的性能及其适应性,提出一种软件定义传感器网络的架构并重点研究其网络重配置算法。算法首先运用Voronoi图理论,寻求SDSN全覆盖问题中保证网络能量均衡的最优感知半径分配,以达到目标区域的K重覆盖;其次基于单纯复形理论,提出一种基于边缘链群最小生成元和节点度的集中控制方法,以最简练的网络拓扑结构为目标,同时保证整个系统的连通性以及突发区域的顽健性;考虑SDSN中路由协议在动态环境的自适应性,提出一种基于多业务QoS的SDSN路由优化算法并进行了仿真,结果表明所提路由算法能够有效分配资源,满足多业务QoS需求并延长网络的生命周期。     

Data network structural vulnerability analysis method

Existing data network risk assessment methodology concerned about the safety analysis of the data network components lack of analysis of the overall network security features. With the maturing of the complex network theory to study, more and more researchers will combine theory with reality system to describe the analysis of complex data networks. The complex network theory is applied to the field of complex structured risk analysis of the data network, data network connectivity and efficacy of two aspects of the analysis, and the vulnerability of the network structure of the complex data analysis. The methods adopted to study the unique characteristics of the network traffic on the data network to make up for the one-sidedness of the general complex network theory to evaluate the efficacy of the data network, and at the same time to make up for the blank data network structure overall vulnerability analysis.     

PFARS: Enhancing throughput and lifetime of heterogeneous WSNs through power‐aware fusion,aggregation, and routing scheme

Heterogeneous wireless sensor networks (WSNs) consist of resource‐starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, congestion control, and energy efficiency. In these networks, data fusion algorithms process the raw data generated by a sensor node in an energy‐efficient manner to reduce redundancy, improve accuracy, and enhance the network lifetime. In literature, these issues are addressed individually, and most of the proposed solutions are either application‐specific or too complex that make their implementation unrealistic, specifically, in a resource‐constrained environment. In this paper, we propose a novel node‐level data fusion algorithm for heterogeneous WSNs to detect noisy data and replace them with highly refined data. To minimize the amount of transmitted data, a hybrid data aggregation algorithm is proposed that performs in‐network processing while preserving the reliability of gathered data. This combination of data fusion and data aggregation algorithms effectively handle the aforementioned issues by ensuring an efficient utilization of the available resources. Apart from fusion and aggregation, a biased traffic distribution algorithm is introduced that considerably increases the overall lifetime of heterogeneous WSNs. The proposed algorithm performs the tedious task of traffic distribution according to the network's statistics, ie, the residual energy of neighboring nodes and their importance from a network's connectivity perspective. All our proposed algorithms were tested on a real‐time dataset obtained through our deployed heterogeneous WSN in an orange orchard and also on publicly available benchmark datasets. Experimental results verify that our proposed algorithms outperform the existing approaches in terms of various performance metrics such as throughput, lifetime, data accuracy, computational time, and delay.     

Stability‐aware multi‐metric clustering in mobile ad hoc networks with group mobility

Clustering can help aggregate the topology information and reduce the size of routing tables in a mobile ad hoc network (MANET). The maintenance of the cluster structure should be as stable as possible to reduce overhead and make the network topology less dynamic. Hence, stability measures the goodness of clustering. However, for a complex system like MANET, one clustering metric is far from reflecting the network dynamics. Some prior works have considered multiple metrics by combining them into one weighted sum, which suffers from intrinsic drawbacks as a scalar objective function to provide solution for multi‐objective optimization. In this paper, we propose a stability‐aware multi‐metric clustering algorithm, which can (1) achieve stable cluster structure by exploiting group mobility and (2) optimize multiple metrics with the help of a multi‐objective evolutionary algorithm (MOEA). Performance evaluation shows that our algorithm can generate a stable clustered topology and also achieve optimal solutions in small‐scale networks. For large‐scale networks, it outperforms the well‐known weighted clustering algorithm (WCA) that uses a weighted sum of multiple metrics. Copyright © 2008 John Wiley & Sons, Ltd.     

Survey on network system security metrics

With the improvement for comprehensive and objective understanding of the network system,the research and application of network system security metrics (NSSM) are noticed more.The quantitative evaluation of network system security is developing towards precision and objectification.NSSM can provide the objective and scientific basis for the confrontation of attack-defense and decision of emergency response.The global metrics of network system security is a crucial point in the field of security metrics.From the perspective of global metrics,the status and role of global metrics in security evaluation were pointed out.Three development stages of metrics (perceiving,cognizing and deepening) and their characteristics were analyzed and summarized.The process of global metrics was described.The metrics models,metrics systems and metrics tools were analyzed,and their functions,interrelations,and features in security metrics were pointed out.Then the technical challenges of global metrics of network systems were explained in detail,and ten opportunities and challenges were summarized in tabular form.Finally,the next direction and development trend of network system security metrics research were forecasted.The survey shows that NSSM has a good application prospect in network security.     

A network‐centric approach for access and interface selection in heterogeneous wireless environments

In this paper, we introduce a network‐based approach for access and interface selection (AIS) in the context of resource management in heterogeneous wireless environments (UMTS, WLAN and DVB‐T). We focus on the optimization of resource utilization, while ensuring acceptable quality of service (QoS) provision to the end users. Our objective is to optimally manage the overall system resources and minimize the possibility of QoS handovers (non‐mobility handovers). The adopted architecture applies to typical heterogeneous environments and network entities (Access Routers) are enhanced with extra functionalities. We propose an AIS algorithm that exploits the multihoming concept and globally manages network resources at both radio access and IP backbone networks. The algorithm can estimate near‐optimal solutions in real time and we also introduce a novel triggering policy. We present simulation results of typical scenarios that demonstrate the advantages of our approach. System performance metrics, derived from the simulations, show minimum degradations in high load and congestion situations. Copyright © 2007 John Wiley & Sons, Ltd.     

Routing characteristics of ad hoc networks with unidirectional links

Unidirectional links in an ad hoc network can result from factors such as heterogeneity of receiver and transmitter hardware, power control or topology control algorithms, or differing sources of interference or jamming. Previously proposed metrics for evaluating the difficulty of a unidirectional scenario are limited in scope and are frequently misleading. To be able to analyze ad hoc network routing protocol behavior in a complex networking environment, it is not sufficient to merely assign a single level of difficulty to a unidirectional network scenario; the many interrelated routing characteristics of these scenarios must be understood. In this paper, we develop a set of metrics for describing these characteristics, for example for characterizing routing scenarios in simulations, analysis, and testbed implementations. Based on these metrics, we perform a detailed simulation analysis of the routing characteristics of the three most common simulation models for generating unidirectional links in ad hoc networks: the random-power model, the two-power model, and the three-power model. Our findings enable protocol designers to better choose a set of network scenarios and parameters that truly explore a wide range of a routing protocol’s behaviors in the presence of unidirectional links, and to better understand the complex interplay between routing mechanisms and network conditions.     

QoS‐aware LTE‐A downlink scheduling algorithm: A case study on edge users

4G/LTE‐A (Long‐Term Evolution—Advanced) is the state of the art wireless mobile broadband technology. It allows users to take advantage of high Internet speeds. It makes use of the OFDM technology to offer high speed and provides the system resources both in time and frequency domain. A scheduling algorithm running on the base station holds the allocation of these resources. In this paper, we investigate the performance of existing downlink scheduling algorithms in two ways. First, we look at the performance of the algorithms in terms of throughput and fairness metrics. Second, we suggest a new QoS‐aware fairness criterion, which accepts that the system is fair if it can provide the users with the network traffic speeds that they demand and evaluate the performance of the algorithms according to this metric. We also propose a new QoS‐aware downlink scheduling algorithm (QuAS) according to these two metrics, which increases the QoS‐fairness and overall throughput of the edge users without causing a significant degradation in overall system throughput when compared with other schedulers in the literature.     

Chaos Synchronization of Complex Network Based on Signal Superposition of Single Variable

Chaos synchronization of complex network with uncertain topological structure and coupling coefficient is used to study. By designing appropriate kinetic equation of network node, the chaos synchronization of the complex network is achieved. The unknown parameters and transported values of all the kinetic equations are identified simultaneously in the process of synchronization. When sets the parameter C^T for a specific value, the transported values of complex network node is the superposition of specific parameter of passed node. Lorenz system is taken for example to demonstrate the effectiveness of the presented method for a complex network of arbitrary topological type, and the dynamics analysis of the Lorenz chaotic system is given, the results we get including the Lyapunov exponents spectrum and its corresponding bifurcation diagram, and its corresponding analysis of SE complexity algorithm and C0 complexity algorithm are analysis briefly. In this paper, 0–1 test is given respectively. Discusses the influence of parameters on the synchronization performance. It is found that the synchronization performance of the complex network is very stable.