最小化路径代价和流量均衡模型及算法

流量均衡是流量工程中为避免网络拥塞经常采用的路由优化目标,如何选择路径以使流量达到均衡分布是流量路由的研究热点和难点.为了最小化网络拥塞,该文在指出网络拥塞决定于流量路由时所选路径的拥塞特征后,建立了流量分布的最小化路径代价和模型.在流量路由选择路径时,提出基于瓶颈链路的最小代价路径路由算法.在实际的网络拓扑和流量矩阵数据基础上对所提模型及算法进行了实验验证,结果显示:在网络负载较大时最大链路利用率相对于已有模型可降低近20%.     

时间敏感网络时隙感知循环排队转发流量整形机制

时间敏感网络是智能工厂内网的核心技术之一。智能工厂内存在多种需求各异的业务流。为保证关键业务流的性能，同时提升网络带宽利用率，该文提出一种时隙感知循环排队转发流量整形机制(TSA-CQF)。TSACQF通过将低优先级流量插入CQF奇偶队列中剩余可用时隙中传输提高带宽利用率。TSA-CQF机制包括低优先级流量的时隙感知插入和全局流量规划两个部分。低优先级流量的时隙感知插入是在CQF队列出队时，通过感知奇偶队列剩余时隙的大小，将低优先级流量插入到奇偶队列的剩余时隙进行传输。将全局流量规划建模为多条件约束目标优化问题，通过模拟退火算法求解，完成全局流量的调度，提高可调度流数目，进一步提高资源利用率。仿真结果表明，在混合流量条件下TSA-CQF比传统CQF机制平均提高了带宽利用率11.29%。与传统的CQF相比，TSA-CQF在牺牲一定调度策略生成时间的前提下，能明显提高带宽利用率并且降低最坏端到端时延。     

主动队列管理算法性能评价：比较研究

对当前的主动队列管理算法进行了分类，然后基于NS2网络仿真器比较了它们在不同流量和网络拓扑条件下的多种性能指标。主要结论包括：ARED综合表现最好；PI和REM的瞬态性能较差，对动态流量响应较慢：REM和没有ECN支持的AVQ可以得到较小的时延，但同时牺牲了链路的带宽利用率并造成大量分组丢失；在多瓶颈网络拓扑中，大部分算法的性能有所提高。     

MANET网络分簇组网协议比较与分析

基于分簇结构的MANET网络不依赖固定基础设施即可以实现动态组网与数据传输,可以通过跨簇节点实现大规模组网。对分簇组网协议与算法进行了分析与介绍,在此基础上基于最大连接度算法提出了一种解决分簇组网中跨簇处理的双信道跨簇策略。最大连接度算法能够在保障网络的稳定性的同时提高跨簇通信的效率,双信道跨簇处理有利于实现网络的分层管理与控制,组成与逻辑关系一致的实体网络,网络之间在保持通联的同时具备较高的独立性,传输效率更高。     

基于价值差异学习的多小区mMTC接入算法

在5G大连接物联网场景下,针对大连接物联网设备（massive machine type communication device,m MTCD）的接入拥塞现象,提出了基于价值差异探索的双重深度Q网络（doubledeepQnetworkwithvalue-difference based exploration,VDBE-DDQN）算法。该算法着重解决了在多小区网络环境下mMTCD接入基站的问题,并将该深度强化算法的状态转移过程建模为马尔可夫决策过程。该算法使用双重深度Q网络来拟合目标状态—动作值函数,并采用基于价值差异的探索策略,可以同时利用当前条件和预期的未来需求来应对环境变化,每个m MTCD根据当前值函数与网络估计的下一时刻值函数的差异来更新探索概率,而不是使用统一的标准,从而为mMTCD选择最佳基站。仿真结果表明,所提算法可有效提高系统的接入成功率。     

支撑向量机回归的简化SMO算法

统计学习理论中提出的支撑向量机回归(SVR)遵循了结构风险最小化原则，从而避免了一味追求经验风险最小化带来的弊端。采用扩展方法使SVR与支撑向量机分类(SVC)具有相似的数学形式，并在此基础上提出了一种用于SVR的简化SMO算法。与SVR现有的SMO算法相比，简化算法的数学形式简洁直观，在不增加算法空间和时间复杂度的前提下避免了大量繁复的判别条件，较大幅度地简化了算法实现，有利于SVR的广泛使用。     

软件定义网络中基于流量管理的分布式防火墙策略

在软件定义网络中将防火墙策略定义为访问控制型规则,并将其分布式地部署在网络中能够提高会话的服务质量。为了减少放置在网络中规则的数量,文中提出多路复用和合并的启发式规则放置算法(HARA)。算法考虑到了商品交换机TCAM存储空间和端点交换机相连链路的流量负载,通过建立以最小化规则放置数量为目标的混合整数线性规划模型,解决不同吞吐量的多路由单播会话的规则放置问题。实验结果表明,与nonRM-CP算法相比,在保证不同会话服务质量的前提下,该算法最多能节省56%的TCAM空间,平均能减少13.1%的带宽资源利用率。     

基于mean-variance的服务集群负载均衡方法

大量并发请求任务进行分配时,负载调度机制是通过最小化响应时间及最大化节点利用率实现网络中节点的负载均衡,在基于遗传算法的负载均衡算法中,适应度函数设计对服务集群负载均衡效率产生重要的影响.对此提出了一种基于mean-variance的服务集群负载均衡方法对适应度函数进行优化,采用投资组合选择模型mean-variance进行最小化响应时间,以得到每个服务器资源利用率的权重,从而获得最优的分配组合,进而提高适应度函数的准确性和有效性.在不同服务环境下与其他模型进行比较,仿真结果表明,本文的负载均衡算法在节点利用率和响应时间方面使服务集群得到了更好的均衡.     

改进型短时对数谱的语音增强算法的DSP实现

通过研究单通道条件下基于语音短时对数谱的最小均方误差（MMSE—LSA）估计的语音增强算法，简化了算法难度，改进了实时性。引入了最佳修正短时对数谱估计，能在信号存在的不确定性下最小化语音信号对数谱的均方误差。试验证明此方法的语音增强效果较好，尤其在较低信噪比时效果更明显。算法用浮点DSP TMS320VC33实现，能有效抑制背景噪声。     

互联网智能路由架构及算法

突发流量在网络中非常普遍,会严重损害用户体验。突发流量往往能在短时间（如毫秒级别）内充满链路,导致网络拥塞和频繁分组丢失,端到端时延增加。传统路由算法要么是流量无关（如 OSPF（open shortest path first,开放式最短路径优先））的,无法对实时流量的变化做出调整;要么是集中式控制的（如线性规划）,面临求解时延过大而无法有效应对突发流量的问题。提出了一种新的智能路由算法解决突发流量的问题。一方面,提出的算法能利用机器学习强大的建模能力,通过对网络历史数据的挖掘来学习“隐式”的路由决策依据。另一方面,提出的算法能借助机器学习的快速推理能力降低决策时延,提高系统对突发流量的响应速度。实验结果表明,在真实流量数据集下,相比较其他路由算法,提出的智能路由算法能降低13%～70%的瓶颈链路利用率。     

A Multi-Objective Optimization Scheme for Multicast Routing: A Multitree Approach

In this paper, we propose a multi-objective traffic engineering scheme using different distribution trees to multicast several flows. The aim is to combine into a single aggregated metric, the following weighting objectives: the maximum link utilization, the hop count, the total bandwidth consumption, and the total end-to-end delay. Moreover, our proposal solves the traffic split ratio for multiple trees. We formulate this multi-objective function as one with Non Linear programming with discontinuous derivatives (DNLP). Results obtained using SNOPT solver show that several weighting objectives are decreased and the maximum link utilization is minimized. The problem is NP-hard, therefore, a novel SPT algorithm is proposed for optimizing the different objectives. The behavior we get using this algorithm is similar to what we get with SNOPT solver. The proposed approach can be applied in MPLS networks by allowing the establishment of explicit routes in multicast events. The main contributions of this paper are the optimization model and the formulation of the multi-objective function; and that the algorithm proposed shows polynomial complexity.     

多QoS约束条件下的多目标网络优化

多约束、多业务、多目标的网络优化是一个复杂且涉及范围广泛的课题。文中在对该课题进行分析的基础上,提出了一种基于遗传算法的多目标网络优化算法(MOPGA)。该算法使用了多约束条件下的路径集预处理,使得每项业务能够获得所需的QoS服务质量,通过对所有业务的路由号进行编码,将问题的解空间转换到遗传算法的搜索空间,达到对全网业务的综合考虑。改进后的适应度函数刻划了网络的费用、链路利用率方差和最大链路利用率、爆破处理以及个体淘汰机制增加了种群多样性,挣脱了未成熟收敛。以求解精度作为算法终止条件,使得算法运行时间减少。仿真实验表明,所提出的算法能高效、快速解决实际多目标网络优化问题,同时在满足多QoS约束条件下可均衡各子目标函数。     

Virtual machine placement optimizing to improve network performance in cloud data centers

With the wide application of virtualization technology in cloud data centers, how to effectively place virtual machine （VM） is becoming a major issue for cloud providers. The existing virtual machine placement （VMP） solutions are mainly to optimize server resources. However, they pay little consideration on network resources optimization, and they do not concern the impact of the network topology and the current network traffic. A multi-resource constraints VMP scheme is proposed. Firstly, the authors attempt to reduce the total communication traffic in the data center network, which is abstracted as a quadratic assignment problem; and then aim at optimizing network maximum link utilization （MLU）. On the condition of slight variation of the total traffic, minimizing MLU can balance network traffic distribution and reduce network congestion hotspots, a classic combinatorial optimization problem as well as NP-hard problem. Ant colony optimization and 2-opt local search are combined to solve the problem. Simulation shows that MLU is decreased by 20%, and the number of hot links is decreased by 37%.     

A simple bandwidth management strategy based on measurements ofinstantaneous virtual path utilization in ATM networks

A new connection admission control method based on actual virtual path traffic measurements is proposed to achieve high bandwidth efficiency for various types of traffic. The proposed method is based on the measurement of instantaneous virtual path utilization, which is defined as the total cell rate of the active virtual channels normalized by the virtual path capacity. A low-pass filter is used to determine the instantaneous virtual path utilization from crude measurements. A smoothing coefficient formula is derived as a function of the peak rate of the virtual channel. The residual bandwidth is derived from the maximum instantaneous utilization observed during a monitoring period. Simulation shows that the proposed method achieves statistical multiplexing gains of up to 80% of the limit possible with optimum control for similar traffic sources. It can be implemented with very simple hardware. The admission decision is simple: the requested bandwidth is compared with the residual bandwidth. This method is therefore well suited for practical asynchronous transfer mode switching systems     

Optimum Power Assignment for Maximum Throughput in CDMA Personal Communication Systems with Integrated Voice/Data Traffic

A CDMA personal communication system with integrated voice/data traffic is considered, in which the link error performance is controlled according to the voice error rate requirement, and the acceptable data traffic error rate is ensured by ARQ. Optimum power assignment (or allocation) between voice and data users is investigated to maximize the total system throughput. A graphical method (the tangent method) is described to obtain this optimum power allocation. The maximum throughput is expressed as a function of other system parameters. The tangent method is further used to measure the impact of transmission quality on the maximum data throughput. Numerical results and a design example are given for a power controlled wideband IS-95 type wireless personal communication system.     

Multipath Cognitive Routing in Integrated Multicast Satellite-HAP System Structures

A new multilayered inter satellite-high altitude platform(HAP)system routing algorithm is proposed,which is mainly based on multipath routing to ensure the network reliability.The proposed multipath routing scheme principally relies on splitting the traffic between different paths to make the best utilization of multiple routes.Linear programming is the main method used for multipath selection.The major constraints to the quality of service(QoS)(delay and link utilization)have been taken into account to meet the criteria of the advanced multimedia applications.Due to the effect of link utilization,the system encounters traffic flow oscillation between paths over time,which affects the system performance.Hence,to fix this issue,we propose a cognitive routing algorithm which reacts to the long-term changes of the traffic loads rather than short-term ones.The performance of the proposed routing techniques has been evaluated using appropriate simulation models and implemented by Matlab.     

Traffic scheduling method based on centralized control in named data networking

In order to address the global optimization problem for traffic scheduling in named data networking,related works were analyzed,a method based on centralized control was proposed.The proposed method took network performance and communication overhead into account.In the proposed scheme,appropriate nodes would be selected as E-NDN nodes,then the controller calculated the corresponding multi-path forwarding policies and sent them to E-NDN nodes according to the in-network cache,the aggregation of Interest packets,and the traffic demands of popular contents to achieve global optimization.The evaluation results indicate that the proposed method can significantly reduce the maximum link utilization and improve network performance.Simultaneously,the proposed method will not cause a large optimization cost,and communication overhead between the controller and nodes will increase slightly.     

The Efficiency of Traffic Engineering with Regard to Link Failure Resilience

IP networks have established as a global telecommunication platform with increasing user population and an extending spectrum of services. The traffic is also steadily increasing, recently driven by peer to peer networking in addition to client server based applications. Network planers and operators have to ensure the scalability of IP platforms in a permanent upgrade process for transmission capacities. At present, Deutsche Telekom and other telecommunication network providers are introducing traffic engineering methods to achieve an optimum resource utilization.In a first step, traffic engineering can be applied to a predefined network topology, but a comprehensive approach has to be coordinated with a process for upgrading the link capacities and has to prepare for relevant failure scenarios. We have evaluated the efficiency of traffic engineering together with simple link upgrade strategies in order to get a maximum throughput. Therefore a predefined traffic matrix T is taken into account. The optimization goal is to scale the traffic matrix by a maximum factor _max such that the traffic demand _max T can still be carried on the available network resources. The influence of the network topology on the evaluation results is shown in examples with regard to single link failures.     

干扰条件下基于NOMA技术的数据链系统性能分析

航空集群作战场景中电磁环境差且需传输业务量大,数据链频谱资源愈发紧张。针对上述问题, 采用NOMA技术提升数据链频谱利用率并分析干扰条件下基于非正交多址接入(NOMA)技术的数据链系统性能。首先针对航空集群作战场景特点,建立了基于NOMA技术的航空数据链系统模型,推导了系统可获得最大速率表达式。其次考虑路径损耗与莱斯衰落的影响, 推导出系统中断概率的闭合表达式,为估算系统性能提供了快速有效的方法。仿真结果验证了理论推导公式的准确性,并进一步分析了信号发射功率、传输距离、敌方干扰以及数据速率等因素对系统性能的影响。      

基于混沌理论的网络流量性能评估

该文基于混沌理论提出了一种使用海量网络流量数据对大规模网络性能进行有效评估的方法。在长期链路利用率数据呈现出明显的周期性行为,和短期链路利用率数据具有混沌特征的前提下,选取最大Lyapunov指数作为一项性能评估参数来评估网络性能。分析结果表明最大Lyapunov指数较常见统计量如数学期望、方差等更能有效反映流量的行为趋势。