基于参数估计的随机早期探测改进算法

流量控制是互联网有效运行的必要条件.随机早期探测RED(Random Early Detection)是一种基于整条链路的积极队列管理技术,它能显著地提高网络的利用率、稳定性和公平性,是IETF倡导使用的流量控制技术.它由Hashem首先提出雏型,Floyd对之作出了重大改进,形成了较为完善、实用的RED技术,为了在应用中增大RED的适应范围,Fang又提出基于参数自适应的RED.由于现有方法未能稳定、准确地刻画网络流量特征,在流量特性差异较大时,以上方法均难以有效控制网络流量.在本文中,作者首先给出了估计流量特性的解析方法,该方法较参数自适应具有更好的稳定性和准确性;并据此提出了一种RED改进算法,最后通过动态仿真,证明该改进算法提高了RED的适应性,降低了网络时延,减小了时延抖动.     

基于消息优先级的 OppIoV拥塞控制策略

针对机会车联网的网络拥塞问题,提出了一种基于所传输消息优先级的车辆节点拥塞控制策略。当车辆节点存储空间不足而又需要存储新的消息时,该车辆节点内的所有消息按照其优先级由高到低排列,丢弃优先级最低的消息,直至有存储空间来接收新的消息。通过大量的仿真实验与传统的丢弃策略对比,该拥塞控制策略能显著提高消息的递交率,减小开销,并对网络拥塞状况有更好的自适应能力。     

QoS区分的无线通信仿生建模

为了实现动态网络环境下的自适应QoS区分服务,提出了QoS区分的无线通信仿生竞争模型,模型借用LV(Lotka-Volterra)生物竞争模型的思想,建立生态系统与无线网络之间的映射关系,同时结合IEEE 802.11e协议设置不同优先级,并将模型瞬时输出值和稳态输出值作为各数据流的发送速率.与传统的QoS区分服务机制EDCA相比,显著提高了网络系统自适应性和快速收敛性,对突发数据流具有很强的抗扰动性,同时有效改善了数据传输友好性,避免了网络拥塞.     

Proactive multipath routing with a predictive mechanism in software‐defined networks

With the growth of network traffic volume, link congestion cannot be avoided efficiently with conventional routing protocols. By utilizing the single shortest‐path routing algorithm from link state advertisement information, standard routing protocols lack of global awareness and are difficult to be modified in a traditional network environment. Recently, software‐defined network (SDN) provided innovative architecture for researchers to program their own network protocols. With SDN, we can divert heavy traffic to multiple paths in order to resolve link congestion. Furthermore, certain network traffics come in periodic fashion such as peak hours at working days so that we can leverage forecasting for resource management to improve its performance. In this paper, we propose a proactive multipath routing with a predictive mechanism (PMRP) to achieve high‐performance congestion resolution. PMRP has two main concepts: (a) a proactive mechanism where PMRP deploys M/M/1 queue and traffic statistics to simulate weighted delay for possible combinations of multipaths placement of all subnet pairs, and leverage genetic algorithm for accelerating selection of optimized solution, and (b) a predictive mechanism whereby PMRP uses exponential smoothing for demand traffic volumes and variance predictions. Experimental results show a 49% reduction in average delay as compared with single shortest routing, and a 16% reduction in average delay compared with utilization & topology‐aware multipath routing (UTAMP). With the predictive mechanism, PMRP can decrease an additional 20% average delay. Furthermore, PMRP reduces 93% of flow table usage on average as compared with UTAMP.     

主动队列管理算法的分类器实现

作为端到端拥塞控制的增强机制,主动队列管理(AQM)通过在网络中间节点有目的地丢弃分组来维持较小的队列长度和较高的链路利用率.已有的大多数主动队列管理算法沿用了随机早期探测(RED)算法首创的概率丢弃机制.本质上,判决是否丢弃分组的过程是一个依赖于网络拥塞状态的决策过程,因此,概率决策不应该是唯一的方法.在本文的研究中,我们首先归纳了理想AQM算法所应具备的品质,然后应用模式识别中分类器的设计思想提出了一种新颖简洁的主动队列管理策略实现框架,并基于Fisher线性判别方法为AQM设计了一个两维两类分类器(TCC).仿真试验表明TCC有效、敏捷、鲁棒,扩展性好,同时实现简单,计算开销小,有利于高速路由器的性能优化.     

随机回退的TCP拥塞控制算法

 面对目前大量使用弃尾队列管理的网络中间节点,提出了一种随机回退的TCP拥塞控制算法TCP Njust,拥塞时在一定范围内随机减少拥塞窗口,拥塞避免时其拥塞窗口在一定范围内随机增加,以减缓TCP全局同步.该算法在Newreno基础上增加了一个随机函数,仿真表明该算法的性能优于Newreno,在网络突发数据流较多时,其性能优于Vegas,适合在Internet上使用.     

基于拥挤度因子的动态信息素更新策略蚁群算法

针对蚁群算法易陷入局部最优、收敛速度慢的问题,文中提出了一种基于拥挤度因子的动态信息素更新策略的蚁群算法(CFACS)。引入鱼群算法中拥挤度的思想,扩大种群中蚂蚁分布范围,使其探索更大的解空间,提高算法全局搜索能力;采用动态信息素更新策略,在每一次迭代中,自适应调整当前最优路径所释放的信息素浓度,保证蚁群前期的多样性,同时保证算法在后期的收敛性。求解TSP问题的仿真实验表明,改进算法求得解的质量和求解的收敛速度都明显优于传统蚁群算法,较好地平衡了种群多样性与收敛速度之间的矛盾。     

Distributed congestion control strategy using network utility maximization theory in VANET

Cooperative vehicle safety system (CVSS) rely on periodical beacons to track neighboring vehicles.High traffic density often causes channel congestion,seriously damaging the performance of CVSS.Existing congestion control strategies aim to ensure the performance in network layer,without considering the service requirements of vehicles in different driving contexts.To solve the problem,a distributed congestion control strategy using network utility maximization (NUM) theory was proposed.First of all,the NUM model for channel resource allocation was introduced.A utility function reflecting vehicle’s safety requirements was proposed in the model.Then under the condition of fixed transmit powers,a optimization problem of channel resource allocation was proposed.Lastly,to solve the optimization problem,a distributed congestion control algorithm named utility-based rate congestion control (UBRCC) algorithm was designed,the algorithm worked out the optimal beaconing rate by updating vehicle’s congestion price,realizing the resource allocation according to vehicle’s safety requirements.Simulation results validate that UBRCC algorithm can efficiently control channel congestion,reduce transmission delay,ensure reliable data transmission and satisfies the requirements of safety applications.     

Location of Multiple-Server Congestible Facilities for Maximizing Expected Demand, when Services are Non-Essential

We formulate a model for locating multiple-server, congestible facilities. Locations of these facilities maximize total expected demand attended over the region. The effective demand at each node is elastic to the travel time to the facility, and to the congestion at that facility. The facilities to be located are fixed, so customers travel to them in order to receive service or goods, and the demand curves at each demand node (which depend on the travel time and the queue length at the facility), are known. We propose a heuristic for the resulting integer, nonlinear formulation, and provide computational experience.     

Up- and Downlink Admission/Congestion Control and Maximal Load in Large Homogeneous CDMA Networks

This paper proposes scalable admission and congestion control schemes that allow each base station to decide independently of the others what set of voice users to serve and/or what bit rates to offer to elastic traffic users competing for bandwidth. These algorithms are primarily meant for large CDMA networks with a random but homogeneous user distribution. They take into account in an exact way the influence of geometry on the combination of inter-cell and intra-cell interferences as well as the existence of maximal power constraints of the base stations and users. We also study the load allowed by these schemes when the size of the network tends to infinity and the mean bit rate offered to elastic traffic users. By load, we mean here the number of voice users that each base station can serve.