基于SDN的混合分段路由概率流调度机制

针对数据中心网络流量路径分配不均匀、易造成大流碰撞,以及控制器流表开销大等问题,提出了一种基于SDN的混合分段路由概率流调度机制SRPFS（segment routing probability flow scheduling）。利用SDN集中控制与全局视图特性,首先采用混合分段路由完成流量初始转发;然后选用粒子群优化算法,重定义粒子群内部寻优过程来对流量进行筛选;最后构造全局节点概率矩阵,设计概率调度算法选举出流量转发最优路径。实验结果表明混合分段路由转发技术在流表开销方面优势较大,并且SRPFS相比于其他较典型的流传输机制,在平均网络吞吐量、链路利用率、标准网络吞吐率等方面有明显优势,能够有效减轻控制器的流表负载,保证了较好的网络性能。     

基于流量特征的流调度策略研究综述

软件定义网络将网络的数据层和控制层相分离,具有可编程性强和全局网络视图的优点,这一优点被越来越多的应用于数据中心网络流调度中。然而,数据中心网络中大象流和老鼠流共存的流量特征是流调度技术的一大挑战。对基于流量特征的流调度策略进行了综述,首先梳理了基于软件定义网络的数据中心网络的理论基础,然后对大象流、老鼠流、大象流与老鼠流三个方面的流调度策略进行了分析和总结,并探讨了相比于传统的流调度技术,在软件定义网络架构下基于流量特征的流调度策略的优势。最后针对目前基于流量特征的流调度技术面临的若干主要问题进行了讨论,指出了下一步的研究方向。     

DAFT:一种OpenFlow大规模流表区分存储与加速查找架构

软件定义网络作为一种数据转发与逻辑控制相解耦的创新网络范式,当采用OpenFlow协议进行大规模部署时,其数据平面的流表规模急剧增大,对OpenFlow交换机的流表存储资源和分组转发性能提出了严峻的挑战.对此,本文构建了一种OpenFlow大规模流表区分存储与加速查找架构DAFT.该架构根据流量分布特性将OpenFlow网络流区分为重要流和次要流,进而采用TCAM和SRAM分别存储其标识字段,并采用DRAM单独存储其内容字段,有效缓解OpenFlow流表存储资源紧张问题.针对重要流/次要流区分问题,在分析传统大象流/老鼠流区分方法的基础上,基于OpenFlow网络流的包成批特性,提出活跃流/空闲流区分方法,以提高TCAM命中率.针对SRAM流表查找性能瓶颈,利用掩码访问不均匀的特点,采用"往前移1"启发法自适应调整掩码顺序,以减少后续数据包的掩码失败探测次数;利用掩码探测多数会失败的特点,借助计数型布鲁姆过滤器预测元组查找失败结果,从而绕过对应的子流表遍历过程.最后,借助骨干网络流量样本,对本文所提DAFT流表架构的查找性能进行实验评估.实验结果表明:DAFT流表架构的TCAM命中率、SRAM平均查找长度和平均流表访问时间均明显优于传统的大象流/老鼠流架构,且稳定性强,有效提升了OpenFlow交换机的分组转发性能.     

Bandwidth-aware energy efficient flow scheduling with SDN in data center networks

Nowadays the energy consumption has become one of the most urgent issues for Data center networks. For general network devices, the power is constant and independent from the actual transfer rate. Therefore the network devices are energy efficient when they are in full workload. The flow scheduling methods based on the exclusive routing can reduce the network energy consumption, as the exclusive routing paths can fully utilize all their links. However, these methods will no longer guarantee the energy efficiency of switches, as they handle flows in priority order by greedily choosing the path of available links instantaneously. In a previous work we proposed an extreme case of flow scheduling based on both link and switch utilization. Herein we consider general scenarios in data center networks and propose a novel energy efficient flow scheduling and routing algorithm in SDN. This method minimizes the overall energy for data center traffic in time dimension, and increases the utilization of switches and meet the flow requirements such as deadline. We did a series of simulation studies in the INET framework of OMNet++. The experiment results show that our algorithm can reduce the overall energy with respect to the traffic volume and reduce the flow completion time on average.     

一种支持DiffServ模型的全分布式调度算法

调度算法设计对于网络路由设备实现区分服务(DiffServ)模型的单跳行为(per hop behavior,简称PHB)至关重要.现有支持DiffServ模型的调度算法普遍基于输出排队(output queued,简称OQ)或是输入排队(input queued,简称IQ)交换结构进行设计,均无法在高速环境下提供高性能的调度.基于联合输入/交叉节点排队(combinedinput-crosspoint-queued,简称CICQ)交换结构提出一种支持DiffServ模型的全分布式调度算法DDSS (distributed DiffServ supporting scheduling),并通过理论分析对其公平性进行了验证.DDSS算法采用基于预约带宽的逐级流量控制机制实现所有预约带宽在快速转发(expedited forwarding,简称EF)业务与确保转发(assured forwarding,简称AF)业务之间的分配,采用优先级调度机制为EF业务提供低延迟服务,算法复杂度为O(log N).仿真结果表明,DDSS算法具有良好的时延性能和公平特性,与现有算法相比,能够更好地支持DiffServ模型.     

On the implications of routing metric staleness in delay tolerant networks

Delay Tolerant Network (DTN) routing addresses challenges of providing end-to-end service where end-to-end data forwarding paths may not exist. The performance of current DTN routing protocols is often limited by routing metric “staleness”, i.e., routing information that becomes out-of-date or inaccurate because of long propagation delays. Our previous work, ParaNets, proposed a new opportunistic network architecture in which the data channel is augmented by a thin end-to-end control channel. The control channel is adequate for the exchange of control traffic, but not data. In this paper we present Cloud Routing, a routing solution for the ParaNets architecture. We motivate the need for such a solution, not only because of stale routing metrics, but also because of congestion that can occur in DTNs. Unable to use up-to-date routing metrics to limit congestion, existing DTN routing solutions suffer from low goodput and long data delivery delays. We show how Cloud Routing avoids congestion by smart use of forwarding opportunities based on up-to-date routing metrics. We evaluate our solution using extensive OPNET simulations. Cloud Routing extends network performance past what is currently possible and motivates a new class of globally cognizant DTN routing solutions.     

TMP-TIE:基于流量迁移预测的域间出口选择算法

出口选择算法是域间路由策略的直接体现,并具备流量工程能力。针对可调域间路由出口选择算法引起的大幅流量迁移问题,以控制与转发分离的网络架构为背景,提出了基于流量迁移预测的出口选择算法TMP-TIE。该算法在TIE算法的基础上加入对流量迁移的预测和判定,避免出口变化引起的大幅流量迁移,降低对域间流量传输的影响。通过模拟实验比较了热土豆、TIE和TMP-TIE的性能,实验结果说明,TMP-TIE具有最小的路由敏感性和流量敏感性,能降低故障条件下的网络代价和网络拥塞的概率,有利于实现域间流量工程。     

数据中心网络中一种半集中式SDN路由策略

在SDN体系架构中把网络控制功能从网络设备（交换机/路由器）里分离出来,集中到中心节点控制器上,交换机只负责数据平面的功能（通过流表进行数据转发）。在大规模的数据中心网络中,路由/流表的计算和分发完全由中心控制器完成,控制器成为网络的性能瓶颈和脆弱点。为了解决上述问题,本文提出半集中式SDN路由技术,其主要思想是每个交换机节点不需要控制器的参与,可以自主构建一个基础流表,基于基础流表,交换机可以完成基本的数据转发工作。而控制器负责更高级的路由选路（故障处理）工作,从而大大减轻控制器的负担。针对控制器的高级路由选路工作,本文通过对现有SDN网络中的故障恢复机制的特性以及限制的分析,在基础流表的基础上设计一套局部迂回故障检测恢复机制。基于该机制,控制器能够及时检测到网络故障,并在极短的时间内进行故障恢复,实现控制器的高级路由选路工作。     

软件定义网络中基于分段路由的多路径调度算法

针对当前软件定义网络(SDN)在应对大量数据流时造成的流表利用率低、转发响应较慢以及当前网络调度算法容易造成网络局部拥塞和负载不均衡等问题,提出一种基于分段路由的多路径调度算法SRMF。首先,SDN控制器根据网络拓扑连接情况下发初始流表;综合考虑网络链路剩余带宽、丢包率和数据流估测带宽需求进行路径权重计算;最后,根据路径权重选择最优路径并构造分段流表下发到边缘交换机。实验结果表明分段路由转发技术在多种网络拓扑下较一般转发技术在流表项开销方面有明显优势,SRMF算法与Hedera、ECMP相比,在业务流端到端时延、端到端时延抖动、网络吞吐率、丢包率等方面有一定的优势。     

基于SDN网络大象流负载均衡算法研究

负载均衡算法是通过对网络中的流量进行调度来提高网络资源利用率,是计算机网络中的一个重要研究方向;针对网络中大象流导致的网络拥塞和老鼠流的排队时延等负载不均衡问题,提出了带宽和时延加权负载均衡(BD-WLB)算法来提高负载均衡性能,综合考虑了大小流之间的流量特征不同,改进了传统算法的路径计算方式;算法通过控制器来获取网络流量和状态信息;然后利用带宽和时延等网络状态参数来为大象流和老鼠流分别计算最优路径;采用P4语言来对数据平面转发流程进行优化处理;实验结果表明,在高负载状态时,BD-WLB算法相比于ECMP算法提高了38.4%的网络吞吐量和41.9%的链路利用率,降低了41.8%的网络时延;使网络资源得到了更好的利用,证明了BD-WLB算法的可行性和有效性。     

Elastic Routing Table with Provable Performance for Congestion Control in DHT Networks

Consistent hashing-based DHT networks have an inherent load balancing problem. The problem becomes more severe in heterogeneous networks with nonuniform and time-varying popular files. Existing DHT load balancing algorithms are mainly focused on the issues caused by node heterogeneity. To deal with skewed lookups, this paper presents an elastic routing table (ERT) mechanism for query load balancing, based on the observation that high-degree nodes tend to receive more traffic load. The mechanism allows each node to have a routing table of variable size corresponding to node capacities. The indegree and outdegree of the routing table can also be adjusted dynamically in response to the change of file popularity and network churn. Theoretical analysis proves that the routing table degree is bounded. The ERT mechanism facilitates locality-aware randomized query forwarding to further improve lookup efficiency. By relating query forwarding to a supermarket customer service model, we prove that a two-way randomized query forwarding policy should lead to an exponential improvement in query processing time over random walking. Simulation results demonstrate the effectiveness of the ERT mechanism and its related query forwarding policy for congestion and query load balancing. In comparison with existing "virtual-server”-based load balancing algorithms and other routing table control approaches, the ERT-based congestion control protocol yields significant improvement in query lookup efficiency.     

一种MPLS流量工程显式路由算法

提出一种基于策略和流分类的MPLS（Multi-Protocol Label Switch）显式路由算法—PTCR（Policy and Traffic Classi-fication Routing）.算法综合考虑网络流量、资源、管理策略等要素,根据网络流量分布特征和网管策略合理配置网络资源.算法能够较好地平衡网络资源的使用,提高网络资源利用率,有效实施MPLS流量工程.     

基于CKSP的分段路由负载均衡技术

针对当前以云计算、大数据为代表的新兴业务需求,现有的MPLS(Multi-Protocol Label Switching)网络存在协议复杂、扩展性差、运维困难等问题。因此文中采用分段路由(Segment Routing,SR)转发技术,根据软件定义网络(Software-Defined Networking,SDN)集中控制、开放编程的特点,提出了一种基于受限K最短路径(Constrained K-Shortest Pathes,CKSP)算法的分段路由负载均衡的技术方案。首先,控制器与各网络节点以OpenFlow协议进行信息交互,对全网拓扑结构和链路速率进行监控;然后,分段路由应用根据北向接口以二级流表、多节点中继的方式实现转发表等初始表项的构建和段列表计算;最后,设计了一种根据链路利用率和跳数进行非均匀加权的CKSP算法。实验结果表明:该技术方案可以增大网络吞吐量,平滑流量分布,降低数据流平均时延和网络总丢包率。     

Termite-hill: Performance optimized swarm intelligence based routing algorithm for wireless sensor networks

A wireless sensor network (WSN) is a large collection of sensor nodes with limited power supply, constrained memory capacity, processing capability, and available bandwidth. The main problem in event gathering in wireless sensor networks is the formation of energy-holes or hot spots near the sink. Due to the restricted communication range and high network density, events forwarding in sensor networks is very challenging, and require multi-hop data forwarding. Improving network lifetime and network reliability are the main factors to consider in the research associated with WSN. In static wireless sensor networks, sensors nodes close to the sink node run out of energy much faster than nodes in other parts of the monitored area. The nodes near the sink are more likely to use up their energy because they have to forward all the traffic generated by the nodes farther away to the sink. The uneven energy consumption results in network partitioning and limit the network lifetime. To this end, we propose an on-demand and multipath routing algorithm that utilizes the behavior of real termites on hill building termed Termite-hill which support sink mobility. The main objective of our proposed algorithm is to efficiently relay all the traffic destined for the sink, and also balance the network energy. The performance of our proposed algorithm was tested on static, dynamic and mobile sink scenarios with varying speed, and compared with other state-of-the-art routing algorithms in WSN. The results of our extensive experiments on Routing Modeling Application Simulation Environment (RMASE) demonstrated that our proposed routing algorithm was able to balance the network traffic load, and prolong the network lifetime.     

基于软件定义网络的边缘控制部署机制

针对软件定义网络（software-defined Networking,SDN）中单一控制器容易发生过载导致较长时延的问题,提出一种基于SDN的边缘控制模型,该模型采取分层部署方式将边缘计算集成到SDN中,每个边缘控制器控制其覆盖范围内部署的所有子边缘控制器和交换机,负责区域内网络设备的通信量。为了方便管理边缘控制器之间的交互,该模型引入一个控制器代理模块,将设备请求转发给父控制器或将路由信息发送给子控制器来协调控制器之间的工作。实验结果表明,与基于SDN的传统网络相比,该方法依托部署在网络设备边缘的计算和存储服务,减轻了SDN主控制器上的负载,降低了转发平面和控制平面之间的延时,显著地改善了总处理延时和带宽使用情况。     

Edge-limited scalable QoS flow set-up

Although the Differentiated Services architecture supports scalable packet forwarding based on aggregate flows, the detailed procedure of Quality of Service (QoS) flow set-up within this architecture has not been well established. In this paper we explore the possibility of a scalable QoS flow set-up using a sink-tree paradigm. The paradigm initially constructs a sink tree at each egress edge router using network topology and bandwidth information provided by a QoS extended version of Open Shortest Path First (OSPF), which is a widely used link-state routing protocol. Our sink-tree paradigm dynamically reallocates network bandwidths online according to traffic demands. As a consequence, our paradigm easily supports QoS routing, resource allocation, and admission control at ingress edge routers without consulting core routers in a way that the QoS flow set-up time and overhead are minimized. Simulation results are very encouraging in that the proposed methodology requires significantly less communication overhead in setting up QoS flows compared to the traditional per-flow signaling-based methodology while still maintaining high resource utilization.     

A novel forwarding and routing mechanism design in SDN-based NDN architecture

Combining named data networking (NDN) and software-defined networking (SDN) has been considered as an important trend and attracted a lot of attention in recent years. Although much work has been carried out on the integration of NDN and SDN, the forwarding mechanism to solve the inherent problems caused by the flooding scheme and discard of interest packets in traditional NDN is not well considered. To fill this gap, by taking advantage of SDN, we design a novel forwarding mechanism in NDN architecture with distributed controllers, where routing decisions are made globally. Then we show how the forwarding mechanism is operated for interest and data packets. In addition, we propose a novel routing algorithm considering quality of service (QoS) applied in the proposed forwarding mechanism and carried out in controllers. We take both resource consumption and network load balancing into consideration and introduce a genetic algorithm (GA) to solve the QoS constrained routing problem using global network information. Simulation results are presented to demonstrate the performance of the proposed routing scheme.     

Beyond Fat--tree: Unidirectional Load--Balanced Multistage Interconnection Network

The fat-tree is one of the most widely-used topologies by interconnection network manufacturers. Recently, it has been demonstrated that a deterministic routing algorithm that optimally balances the network traffic can not only achieve almost the same performance than an adaptive routing algorithm but also outperforms it. On the other hand, fat-trees require a high number of switches with a non-negligible wiring complexity. In this paper, we propose replacing the fat--tree by a unidirectional multistage interconnection network (UMIN) that uses a traffic balancing deterministic routing algorithm. As a consequence, switch hardware is almost reduced to the half, decreasing, in this way, the power consumption, the arbitration complexity, the switch size itself, and the network cost. Preliminary evaluation results show that the UMIN with the load balancing scheme obtains lower latency than fat--tree for low and medium traffic loads. Furthermore, in networks with a high number of stages or with high radix switches, it obtains the same, or even higher, throughput than fat-tree.     

FRoots: A Fault Tolerant and Topology-Flexible Routing Technique

Existing solutions for fault-tolerant routing in interconnection networks either work for only one given regular topology, or require slow and costly network reconfigurations that do not allow full and continuous network access. In this paper, we present FRroots, a routing method for fault tolerance in topology-flexible network technologies. Our method is based on redundant paths, and can handle single dynamic faults without sending control messages other than those that are needed to inform the source nodes of the failing component. Used in a modus with local rerouting, the source nodes need not be informed and no control messages are necessary for the network to stay connected despite of a single fault. In fault-free networks under nonuniform traffic our routing method performs comparable to, or even better than, topology specific routing algorithms in regular networks like meshes and tori. FRoots does not require any other features in the switches or end nodes than a flexible routing table, and a modest number of virtual channels. For that reason, it can be directly applied to several present day technologies like InfiniBand and Advanced Switching.     

Design and performance analysis of an inductive QoS routing algorithm

Routing mechanism is key to the success of large-scale, distributed communication and heterogeneous networks. Consequently, computing constrained shortest paths is fundamental to some important network functions such as QoS routing and traffic engineering. The problem of QoS routing with multiple additive constraints is known to be NP-complete but researchers have been designing heuristics and approximation algorithms for multi-constrained paths algorithms to propose pseudo-polynomial time algorithms. This paper introduces a polynomial time approximation quality of service (QoS) routing algorithm and constructs dynamic state-dependent routing policies. The proposed algorithm uses an inductive approach based on trial/error paradigm combined with swarm adaptive approaches to optimize lexicographically various QoS criteria. The originality of our approach is based on the fact that our system is capable to take into account the dynamics of the network where no model of the network dynamics is assumed initially. Our approach samples, estimates, and builds the model of pertinent aspects of the environment which is very important in heterogeneous networks. The algorithm uses a model that combines both a stochastic planned pre-navigation for the exploration phase and a deterministic approach for the backward phase. Multiple paths are searched in parallel to find the K best qualified ones. To improve the overall network performance, a load adaptive balancing policy is defined and depends on a dynamic traffic path probability distribution function. We conducted a performance analysis of the proposed QoS routing algorithm using OPNET based on a platform simulated network. The obtained results demonstrate substantial performance improvements as well as the benefits of learning approaches over networks with dynamically changing traffic.