软件定义数据中心网络混合路由机制

针对数据中心网络流量大小分布不均匀、传输性能需求不相同的特征,提出了面向传统树型数据中心网络结构的软件定义混合路由机制SHR（software-defined hybrid routing）。SHR通过统计计算将数据流分为大流和小流,为满足其不同的传输性能需求,对大流采用自适应路由算法,对小流采用流量无视路由算法。SHR在OpenFlow机制的基础上,将部分控制权从控制器下放至交换机,以减轻网络的额外负载。在Fat-Tree网络拓扑结构上建立流量模型进行性能分析与仿真实验,结果表明,与传统的等价多路径转发ECMP算法相比,SHR能够提高网络吞吐量,降低数据流丢弃率和分组端到端时延,同时减轻网络的额外负载。     

基于价格调整和流量工程的软件定义数据中心网络传输优化方法

分析数据中心网络动态价格调整拥塞控制和流量工程传输优化方法的研究现状,提出结合拥塞控制、流量调度和负载均衡的网络传输优化方法,设计一种新型数据中心网络资源动态价格调整策略框架,构建一种两层结构的数据中心网络拥塞控制价格设置算法,平衡和调节各发送端的购买力和链路带宽收益之间的关系,根据各价格指标设计具有QoS路由技术与调度算法实现资源优化利用的流量工程方法,扩展OpenFlow协议算法,整合SDN、FAST协议、ECN三种技术,从运行机制方面找到提高数据中心网络传输性能的方法.     

基于软件定义网络的服务器集群负载均衡技术研究

在当前的网络体系结构下,采用硬件系统实现服务器集群负载均衡存在着获取负载节点状态困难、流量导向方式复杂等制约因素,不利于提升服务器集群的伸缩性和服务性能。针对此问题,该文提出一种基于软件定义网络(SDN)的负载均衡机制(SDNLB)。该机制借助SDN具有的集中式控制和流量灵活调度优势,利用SNMP协议和OpenFlow协议对服务器的运行状态和全局网络负载信息进行实时监测,并通过权值计算的方式选择出权重最高的服务器作为流处理的目标服务器,在此基础上,采用最优转发路径算法进行流量调度,从而达到提高服务器集群的利用率与处理性能的目的。搭建了实验平台对SDNLB的性能进行仿真测试,实验结果表明:在相同的网络负载条件下,SDNLB与其他负载均衡算法相比,能够有效地降低服务器集群的负载,并能够显著提高网络吞吐量和带宽利用率,缩短流的完成时间和平均时延。     

基于SDN的数据中心流切片研究

在云计算的背景下,当代数据中心网络链路在业务高峰期经常出现网络流量分布不均匀的情况,源主机到目的主机往往存在多条可用路径。因此如何平衡流量是保证数据中心正常稳定运行的关键。数据中心网络拥塞主要是由于大流造成的,而直接以大流为单位进行调度并不能有效的提高网络传输效率。文章结合Open Flow技术,根据流特征来对流进行切片,再对子流[1]调度实现负载均衡功能,而且尽可能减少数据包重排序概率,在二者间达到一种平衡。     

面向带宽碎片最小化和QoS保障的数据中心网络流量调度算法

随着数据中心网络流量的迅速增长,如何提高数据中心网络性能和服务质量成为了研究热点。然而现有的流量调度算法在网络负载加大时,一方面会导致网络带宽碎片化从而使得网络吞吐量降低,另一方面忽视了流量应用需求导致网络服务质量较差。为此,该文提出一种面向带宽碎片最小化和QoS保障的动态流量调度算法,算法综合考虑了带宽敏感的大流、时延与丢包敏感的小流的不同需求,首先根据待调度流的源地址和目的地址建立最短路径集,其次从中筛选出满足待调度流的带宽需求的所有路径,然后根据路径剩余带宽信息和小流应用需求情况为每条路径建立权重函数,最后根据权重函数值利用轮盘赌算法选择转发路径。实验仿真结果显示,与其它算法相比,所提算法降低了小流的丢包率和时延,同时在网络负载较大时提升了网络吞吐量。     

基于流分类的数据中心网络负载均衡机制

为充分利用数据中心网络的多路径带宽,现有研究多采用基于链路感知的负载均衡算法,在动态获取全局链路拥塞信息后选取最优路径对流量进行转发.然而这些研究未考虑数据中心网络流量大小分布不均匀的特性,难以在选路成本和转发效率上取得平衡.为此,设计一种基于流分类的数据中心网络负载均衡机制(ULFC,Utilization-aware Load balancing based on Flow Classification),在实现拥塞感知的基础上进行流量特征分析,采用不同的策略为大、小流分配路径,实现网络流量特征与选路方法优势的最佳匹配.实验结果表明,相比于现有方案,ULFC的平均流处理效率提高了1.3倍至1.6倍,路由成本降低了50％以上.     

基于粒子群优化算法的数据中心网络流量调度策略

为解决当前数据中心网络存在链路负载不均衡及带宽资源浪费问题,提出了一种基于粒子群优化算法的流量调度策略.该策略结合软件定义网络控制器可获取全局网络拓扑信息的特性,依据当前链路带宽资源状况及网络流量的带宽需求建立目标函数.首先,根据流的源地址和目的地址找出最短路径集,通过定义粒子聚合度判断算法是否有陷入局部最优的趋势;然后,结合约束条件与目标函数,利用优化的粒子群算法从最短路径集中找出网络流量的最佳调度路径.实验结果表明,相比于其他算法,该算法有效地提高了网络平均吞吐量,获取了较低的丢包率,从而减轻了带宽资源的浪费,更好地实现了网络的负载均衡.     

WMN中一种基于干扰感知的负载均衡路由协议

无线信道干扰和负载分布的不均衡严重影响无线Mesh网络吞吐量、端到端延时和资源利用率。在已有基于信噪比和邻居节点个数的干扰模型基础上,进一步研究了无线Mesh网络的链路干扰。在综合考虑了无线Mesh网络流间干扰和和流内干扰的基础上,提出路由判据PIL（Path Interfer-ence Level）。在此基础上,提出一种新的基于干扰感知的负载均衡路由协议IA-DSR（Interference-Aware DSR）。IA-DSR考虑无线网络拥塞并选择受到干扰最小的路径。仿真结果表明,在不显著增加开销的情况下,IA-DSR可以有效地提高网络的整体吞吐量,降低网络端到端时延和丢包率。     

一种基于分布式服务器集群的可扩展负载均衡策略技术

提出了一种基于软件定义网络的分布式数据库负载均衡算法,将数据、控制、应用分离的同时计算服务器集群中单个服务器的实际负载.通过查询流量采样记录来决策最少连接的服务器路径,减少了访问请求的响应时间,提高了系统吞吐量和容错能力,实现了充分利用服务器资源的目的.内网中的分布式数据库实验对通用负载均衡技术和基于软件定义网络的负载均衡技术进行了比较,在不同服务器集群的负载状态下,后者的平均响应时间小于前者,并得到了更好的负载均衡效果.     

一种智慧协同网络多参数的多路径路由算法

多路径路由技术采用多条路径同时传输,作为优化资源配置和负载均衡的重要技术,在路由可靠性、QoS路由、传输效率等多方面比单路径传输具有优势.现有互联网网络资源配置和路由机制相对静态和僵化,导致多路径技术的发展存在发展的局限性.现有多路径技术考虑在路由层面不利于多路径路由选择和计算,难以保证传输性能,降低网络传输效率.智慧协同网络能够动态感知网络需求,灵活适配网络资源,更好的支持路由可扩展性.本文在智慧协同网络架构下提出了一种智慧协同网络多参数的多路径路由算法.该算法制定了智慧协同网络多参数的多路径路由协议,对网络性能参数CPU占用率、往返时延(RTT)、带宽进行加权计算得到路径权重值,根据权重值进行流量分配.采用图论理论对网络流量分配及模型进行了分析.并在Mini-Net平台上进行了开发和实验,结果表明,该算法能够优化网络配置,减小往返时延,提高网络吞吐量,从而提高网络性能,实现负载均衡.     

OpenFIow Based Flow Slice Load Balancing

Today＇s data center networks are designed using densely interconnected hosts in the data center.There are multiple paths between source host and destination server.Therefore,how to balance traffic is key issue with the fast growth of network applications.Although lots of load balancing methods have been proposed,the traditional approaches cannot fully satisfy the requirement of load balancing in data center networks.The main reason is the lack of efficient ways to obtain network traffic statistics from each network device.As a solution,the OpenFlow protocol enables monitoring traffic statistics by a centralized controller.However,existing solutions based on OpenFlow present a difficult dilemma between load balancing and packet reordering.To achieve a balance between load balancing and packet reordering,we propose an OpenFlow based flow slice load balancing algorithm.Through introducing the idea of differentiated service,the scheme classifies Internet flows into two categories：the aggressive and the normal,and applies different splitting granularities to the two classes of flows.This scheme improves the performance of load balancing and also reduces the number of reordering packets.Using the trace-driven simulations,we show that the proposed scheme gains over 50%improvement over previous schemes under the path delay estimation errors,and is a practical and efficient algorithm.     

DServ‐LB: Dynamic server load balancing algorithm

In recent years, web services have been largely accessed by the customer, and it increases the network traffic on the internet. To provide the services for the large number of customer, dynamic clustering concept has been implemented that provides the ability to add or remove the servers on demand. But managing and processing the large set of traffic are very complicated. Load balancing technic helps to resolve the problems of network traffic and give efficient network management. In this paper, we proposed a dynamic server load balancing algorithm (DServ‐LB) using OpenFlow switches in software‐defined networking. The OpenFlow switches support the dynamic programmability. Also, we used the sFlow protocol, which is used to monitor the servers resource information periodically and the controller. Based on the server resource availability, the controller installs forwarding rules in the OpenFlow switches. For implementation, we used Mininet for network emulation, POX controller, and Docker container as Mininet hosts. The result shows that the proposed DServ‐LB improves the overall network performance and efficiently utilizes the server resources if compared with existing load balancing algorithms.     

On the use of the genetic programming for balanced load distribution in software-defined networks

As a new networking paradigm, Software-Defined Networking (SDN)enables us to cope with the limitations of traditional networks. SDN uses a controller that has a global view of the network and switch devices which act as packet forwarding hardware, known as “OpenFlow switches”. Since load balancing service is essential to distribute workload across servers in data centers, we propose an effective load balancing scheme in SDN, using a genetic programming approach, called Genetic Programming based Load Balancing (GPLB). We formulate the problem to find a path: 1) with the best bottleneck switch which has the lowest capacity within bottleneck switches of each path, 2) with the shortest path, and 3) requiring the less possible operations. For the purpose of choosing the real-time least loaded path, GPLB immediately calculates the integrated load of paths based on the information that receives from the SDN controller. Hence, in this design, the controller sends the load information of each path to the load balancing algorithm periodically and then the load balancing algorithm returns a least loaded path to the controller. In this paper, we use the Mininet emulator and the OpenDaylight controller to evaluate the effectiveness of the GPLB. The simulative study of the GPLB shows that there is a big improvement in performance metrics and the latency and the jitter are minimized. The GPLB also has the maximum throughput in comparison with related works and has performed better in the heavy traffic situation. The results show that our model stands smartly while not increasing further overhead.     

民航空地通信中的多链路数据分配算法

针对民航空地通信数据丢失率高、吞吐量低问题,提出了一种基于丢包感知负载均衡(Packet Loss-Aware Load Balancing)的分配算法。在空地多链路通信中,每条链路的数据损失率随着链路状态与传输环境等情况实时变化。该算法通过控制每次空地通信中数据流的分割比率,动态分配给每条链路不同大小的数据流,使每条链路的传输损失率趋于相近,提高了空地通信系统吞吐量并减少了数据传输损失,以应对空地通信中丢包率高与吞吐量低等问题。仿真结果表明,所提算法在数据传输损失率和吞吐量上都优于现有的多链路子流分配算法。     

一种基于信道阻力的Ad hoc网络多路径路由算法

该文提出了一种基于信道阻力的Ad hoc网络多路径动态源路由算法。算法中定义了信道阻力的概念,并以信道阻力为依据来进行多条路径的流量分配,由于信道阻力计算中综合考虑了链路质量的各个度量参数,因此能够根据各条路径的传输能力合理分配数据流量。NS2环境下的仿真表明,新算法能够有效地平衡网络负载,提高网络的吞吐量。     

Frame-level traffic splitting for link aggregation in data center networks

Ethernet link aggregation, which provides an easy and cost-effective way to increase both bandwidth and link availability between a pair of devices, is well suited for data center networks. However, all the traffic splitting algorithms used in existing Ethernet link aggregation are flow-level which do not work well owing to the traffic characteristics of data centers. Though frame-level traffic splitting can achieve optimal load balance and the maximum benefits from aggregated capacity, it is generally deprecated in most cases because of frame disordering which can disrupt the operation of many Internet protocols, most notably transmission control protocol (TCP). To address this issue, we first investigate the causes of frame disordering in link aggregation and find that all of them either are no longer true or can be prevented in data centers. Then we present a byte-counter frame-level traffic splitting algorithm which achieves optimal performance while causes no frame disordering. The only requirement is that frames in a flow are the same size which can be easily met in data centers. Simulation results show that the proposed frame-level traffic splitting method could achieve higher throughput and optimal load balance. The average completion time of different sized flows is reduced by 24% on average and by up to 46%.     

一种基于游标的多径流量分割算法

 多径传输使用多条连接源节点和目的节点的路径进行传输,在提高资源利用率的同时会引起包乱序问题,并且存在路径之间的负载均衡问题.本文提出了一种基于游标的流量分割算法,游标是当前路径传输延迟与相邻包到达源节点的时间差之间的差值,它作为选取路径的延时基线来保证包到达的有序性,游标会随着路径不同或相邻包到达源节点的时间差不同而动态地滑动,通过动态滑动游标使得尽可能多的路径可用来传输当前包,从而很好地实现负载均衡.仿真结果表明,与已有的保证包有序的算法相比,本算法使负载更加均衡.