容错光网中带宽分配算法的设计与实现

在光网络带宽分配问题中,如何根据既定的网络拓扑和业务量规划各链路带宽及其可靠性成为一个难题。该文在分析网络带宽分配算法并综合考虑成本和可靠性的基础上,提出了带宽分配遗传算法,将带宽分解为相对尺度和绝对尺度,解决了编码经各种遗传运算仍为可行解的问题。对实验结果进行了分析,并提出了改进方法。     

基于多描述编码的视频组播网络带宽优化分配算法

为了最大限度的满足各种类型视频应用的带宽要求,提高不同类型视频用户的满意度,解决不同类型应用的视频流对网络带宽的需求差异很大的问题,该文提出了一个基于多描述编码的带宽分配模拟退火算法;实验表明,该算法比其他带宽分配算法更能充分利用带宽资源且能有效提高网络视频用户的整体满意度。     

带宽分配中效率与公平性问题研究

本文提出了新的衡量网络带宽分配算法的公平性和效率的定义。基于这个定义对不同的网络带宽公平性分配算法之间的公平性和效率进行了比较。带宽分配问题可以看作是求解一个最大化效用函数的问题,给出了一个新的效用函数,对它在具体网络中的分配和其他公平性分配算法进行比较,建立了它们之间的一种对应关系。     

多重链路时延优化动态可用带宽分配算法

为了优化多重链路多业务环境下的时延,首先分析了带宽分配及链路中数据传输时延计算方法,提出一种时延优化的动态可用带宽分配算法(DODBA)。该算法基于不同优先级业务的时延比较实现了剩余可用带宽的重新分配。仿真实验证明了DODBA的有效性,能控制各链路不同业务的时延,并提高了系统带宽资源的利用率。DODBA可用于解决大型宽带网络接入控制中的实际问题。     

基于效用的超宽带系统带宽分配

把超宽带系统的带宽优化调度表示为一个效用最大化的问题。对于系统的带宽分配,效用函数是服务质量的有效度量,它反映了用户对所分配的资源的满意程度。针对超宽带无线网络带宽分配中链路和用户的集中式算法的复杂性,用分布式方案解决这种问题,以自适应变化的无线网络环境。对系统带宽进行基于效用的分配,满足超宽带系统高速率传输的需要。     

基于定价机制的无线网络带宽分配的研究

基于已有的市场模型下的带宽分配算法,从系统收益和用户平均满意度出发,提出一种改进后的墨于定价机制的带宽分配算法.该算法根据用户的需求和网络系统带宽的使用状况,计算出网络带宽的价格,并采用集中竞拍的方式,通过用户的价格参数进行带宽资源的协商与分配.仿真分析表明,该方法可以达到提高用户满意度和优化系统效益的目标.     

一种改进的OPBM快速算法

在对大规模通信网络中的最优带宽分配算法(OPBM)的实现及其性能的研究过程中发现影响呼叫阻塞概率(CBP)的因素包括两部分预留带宽的影响和非预留带宽的影响,而预留带宽对CBP的影响要大过非预留带宽的影响。基于此发现,该文在OPBM方法的基础上,提出了一种改进式的OPBM算法,与原算法进行了对比,改进OPBM算法的误差很小并且运算速度加快。     

数字校园数据中心传输的滑动带宽分配设计

数据中心是数字化校园各项应用服务访问的核心,其网络带宽的有效利用则是一个重要方面;在一个实际校园网数据中心的网络带宽及流量分析的基础上,提出了基于静态带宽分配改进的滑动带宽分配的机制,给出了滑动带宽的带宽分配模型和调度算法,提高了数据中心带宽的有效利用率.     

基于萤火虫算法的移动边缘计算网络带宽资源优化策略

由于移动边缘计算网络在边缘位置部署,在多用户并发的情况下带宽资源优化策略容易出现高计算负荷,降低带宽资源优化的效果。为了解决这一问题,提出基于萤火虫算法的移动边缘计算网络带宽资源优化策略。在服务器之间数据连续传输的情况下,确定网络内用户分布情况,计算网络运行需要消耗的能量,利用萤火虫算法建立以带宽资源为中心的数学模型,以移动边缘计算网络的各项参数作为依据,对数学模型求解,得到最优解后,以用户最大收益为目标部署优化策略。实验结果表明:提出的基于萤火虫算法的带宽资源优化策略计算延迟小,网络带宽资源优化效能高,整体计算性能得到了明显提升。     

第k条最大可用带宽路径算法

该文提出了无环路的第k条最大可用带宽路径算法．由于具有凹性的带宽和具有加性的代价存在本质区别，第k条最大可用带宽路径算法不能通过简单修改第k条最短路径算法得到．该文结合两个新定义的路径操作和修改的二重扫除算法完成第k条最大可用带宽路径算法，并证明其正确性、无环性和具有多项式复杂性，最后给出实例并讨论算法实际应用．该文解决了基于带宽度量的路由算法中一类很基本的问题；因算法采用能反映网络实时特性的可用带宽作为路由度量，能直接保证网络带宽资源的最优利用．     

采用分级策略和控制消息的一种动态带宽分配

通过对以太无源光网络接入技术和现有各种带宽分配算法存在不足的分析,基于数据服务优先级划分和ONU队列管理机制,提出了一种新的动态带宽分配算法。它基于服务分级策略和控制消息格式来处理一个EPONs多点控制协议中的不同优先级带宽。仿真表明,提出的动态带宽分配算法不仅有较高的链接效率和带宽利用率,而且在资源分配方面效率更高。     

多约束QoS多播路由选择优化算法研究

研究了一类通信网络中源节点到目的节点的多约束QoS多播路由选择问题,提出了一种解决此类问题的算法.该算法将带宽、时延、丢失率等QoS参数作为约束条件,用基于最短路径算法构造路径选择函数,并依照该函数修正被选路径,使其满足多约束条件.仿真结果表明该算法有较好的性能和较小的时间复杂度,可以方便地推广到多个QoS参数的情况.     

一类标准矩形网络节点间最短路径的求解方法

针对常见的交通道路最短路径问题, 提出标准矩形网络的概念, 分析其节点间最短路径的性质, 并在此基础上给出一种新颖的最短路径求解算法. 该算法利用标准矩形网络的几何性质, 简化了搜索方向和步长的判断, 同时指出常见的交通道路网络一般均可以整体或部分化为标准矩形网络. 与常见的求取最短路径的Dijkstra、Floyd、ACO、A* 等算法进行仿真实验比较, 实验结果表明, 对于大规模标准矩形道路网络, 所提出算法具有更好的寻优精度、稳定性和寻优速度.

     

Fair resource allocation and stability for communication networks with multipath routing

Multipath networks allow that each source-destination pair can have several different paths for data transmission, thus they improve the performance of increasingly bandwidth-hungry applications and well cater for traffic load balancing and bandwidth usage efficiency. This paper investigates fair resource allocation for users in multipath networks and formulates it as a multipath network utility maximisation problem with several fairness concepts. By applying the Lagrangian method, sub-problems for users and paths are derived from the resource allocation model and interpreted from an economic point of view. In order to solve the model, a novel rate-based flow control algorithm is proposed for achieving optimal resource allocation, which depends only on local information. In the presence of round-trip delays, sufficient conditions are obtained for local stability of the delayed algorithm. As for the end-to-end implementation in Internet, a window-based flow control mechanism is presented since it is more convenient to implement than rate-based flow control.     

An ant colony optimization algorithm for the bi-objective shortest path problem

Multi-objective shortest path problem (MOSP) is an extension of a traditional single objective shortest path problem that seeks for the efficient paths satisfying several conflicting objectives between two nodes of a network. MOSP is one of the most important problems in network optimization with wide applications in telecommunication industries, transportation and project management. This research presents an algorithm based on multi-objective ant colony optimization (ACO) to solve the bi-objective shortest path problem. To analyze the efficiency of the algorithm and check for the quality of solutions, experimental analyses are conducted. Two sets of small and large sized problems that generated randomly are solved. Results on the set problems are compared with those of label correcting solutions that is the most known efficient algorithm for solving MOSP. To compare the Pareto optimal frontiers produced by the suggested ACO algorithm and the label correcting algorithm, some performance measures are employed that consider and compare the distance, uniformity distribution and extension of the Pareto frontiers. The results on the set of instance problems show that the suggested algorithm produces good quality non-dominated solutions and time saving in computation of large-scale bi-objective shortest path problems.     

基于干扰模式的无线传感器网络链路调度算法

传感器网络把各种各样的微型传感器设备通过Ad Hoc网络连接起来,以便完成某些特定任务。但是,由于Ad Hoc无线网需要通过共享信道来实现节点间的通信,所以本文基于节点之间可能存在的信道干扰研究了：给定一个源和目的节点对的集合{（si,ti）},怎样在链路层上对从源到目的的数据流进行调度,以使带宽资源得到充分的利用,并设 计了链路的调度算法。     

Joint routing, scheduling, and power control for multichannel wireless sensor networks with physical interference

Reliability and real-time requirements bring new challenges to the energy-constrained wireless sensor networks, especially to the industrial wireless sensor networks. Meanwhile, the capacity of wireless sensor networks can be substantially increased by operating on multiple nonoverlapping channels. In this context, new routing, scheduling, and power control algorithms are required to achieve reliable and real-time communications and to fully utilize the increased bandwidth in multichannel wireless sensor networks. In this paper, we develop a distributed and online algorithm that jointly solves multipath routing, link scheduling, and power control problem, which can adapt automatically to the changes in the network topology and offered load. We particularly focus on finding the resource allocation that realizes trade-off among energy consumption, end-to-end delay, and network throughput for multichannel networks with physical interference model. Our algorithm jointly considers 1) delay and energy-aware power control for optimal transmission radius and rate with physical interference model, 2) throughput efficient multipath routing based on the given optimal transmission rate between the given source-destination pairs, and 3) reliable-aware and throughput efficient multichannel maximal link scheduling for time slots and channels based on the designated paths, and the new physical interference model that is updated by the optimal transmission radius. By proving and simulation, we show that our algorithm is provably efficient compared with the optimal centralized and offline algorithm and other comparable algorithms.     

基于比例积分控制器的分布式动态带宽分配算法

针对公平、有效分配地理上呈分布式的控制系统带宽的问题,提出了一种分布式的动态带宽分配算法。首先把这种带宽分配问题构建为一个凸优化问题,使全部控制系统的效用最大化;再采用分布式带宽分配算法思想,使得控制系统基于网络反馈的拥塞信息改变其采样周期,得到可利用的最大采样速率或最大传输速率;然后把控制系统和链路之间的相互作用建模为一个时延动态系统,并采用比例积分(PI)控制器作为链路队列控制器来实现算法。仿真结果表明,所提带宽分配算法不仅能够使全部设备的传输速率在10 s内收敛到全部设备均等共享的链路带宽值;同时对于PI控制器来说,其队列稳定在期望设置点50个数据包左右,而且能够准确、稳定地跟踪输入信号,使全部控制系统的性能最大化。     

A lexicographically fair allocation of discrete bandwidth for multirate multicast traffics

Fair bandwidth allocation is an important issue in the multicast network to serve each multicast traffic at a fair rate commensurate with the receiver's capabilities and the capacity of the path of the traffic. Lexicographically fair bandwidth layer allocation problem is considered and formulated as a nonlinear integer programming problem. A nonincreasing convex function of the bandwidth layers of the virtual sessions is employed to maximize the bandwidth of each virtual session from the smallest.To solve the fairness problem a genetic algorithm (GA) is developed based on the fitness function, ranking selection and the shift crossover. Outstanding performance is obtained by the proposed GA in various multicast networks. The effectiveness of the GA becomes more powerful as the network size increases.     

Media Flow Rate Allocation in Multipath Networks

We address the problem of joint path selection and source rate allocation in order to optimize the media specific quality of service in streaming of stored video sequences on multipath networks. An optimization problem is proposed in order to minimize the end-to-end distortion, which depends on video sequence dependent parameters, and network properties. An in-depth analysis of the media distortion characteristics allows us to define a low complexity algorithm for an optimal flow rate allocation in multipath network scenarios. In particular, we show that a greedy allocation of rate along paths with increasing error probability leads to an optimal solution. We argue that a network path shall not be chosen for transmission, unless all other available paths with lower error probability have been chosen. Moreover, the chosen paths should be used at their maximum available end-to-end bandwidth. Simulation results show that the optimal flow rate allocation carefully adapts the total streaming rate and the number of chosen paths, to the end-to-end transmission error probability. In many scenarios, the optimal rate allocation provides more than 20% improvement in received video quality, compared to heuristic-based algorithms. This motivates its use in multipath networks, where it optimizes media specific quality of service, and simultaneously saves network resources at the price of a very low computational complexity.