智慧协同网络中基于流量矩阵的负载均衡路由机制

智慧协同网络具有能够实时准确测算流量矩阵的特点。将流量矩阵作为约束,对负载均衡路由优化问题进行建模,利用拉格朗日对偶方法,将原问题转化为优化目标易实现的对偶问题。为实现对偶问题优化目标,提出一种基于流量矩阵的负载均衡路由 (TM-LB,traffic matrix based load balancing) 算法,供控制层根据实时网络情况为后续流规划传输路径。利用OMNET++仿真器在NFSnet拓扑结构上进行仿真实验,结果表明TM-LB相比传统路径规划机制能有效避免拥塞,实现负载均衡。最后,搭建原型系统对TM-LB算法的开销进行测试。     

基于流量工程的IP over WDM网络节能路由算法研究

提出了一种基于流量工程的绿色路由算法,在传统绿色路由算法的基础上,融入流量分割及负载均衡的流量工程,从而实现在减小能耗的同时保证网络性能。仿真结果表明,由于考虑了流量工程,基于流量工程的绿色路由算法能够在有效节约能耗的同时保证网络性能。     

光网络中基于流量均衡的SRLG分离路由算法

基于共享风险链路组(SRLG,shared risk link group)和流量均衡的概念,研究了光网络抗毁设计中基于流量均衡的SRLO尽量分离路由问题,利用网络流量的实际分布来评价链路和SRLG重要性,提出基于流量均衡的SRIG分离算法TBDR.通过计算机仿真表明,TBDR算法性能优于保护路优先算法,该算法能有效降低网络阻塞率,提高网络资源利用率和网络抗毁能力,达到流量均衡的目标.     

基于SVM的电力通信网络路由均衡方法研究

路由均衡过程存在负载开销，导致路由分配风险概率增加，提出基于SVM的电力通信网络路由均衡方法。构建路由均衡模型，通过能量函数分配网络业务路由，基于粒子群优化算法改进最小支持向量机的路由算法，求解均衡模型；通过最小支持向量机估算网络节点剩余能量，选用负载开销最小的路径路由数据，实现电力通信网络全局路由均衡分配。实验结果表明：该方法可均衡电力通信网络中存在的风险，且噪声大小对电力通信网络覆盖率、节点平均剩余能量以及业务中断影响不明显，在均衡电力通信网络业务方面具有可靠性与有效性。     

多目标的Internet路由优化控制算法

研究通过优化链路权值以控制网络路由来实施流量工程.以网络拥塞最小化和时延最小化为流量工程目标,建立了多目标的全局路由优化数学模型.求解该问题是NP困难的,提出一种混沌群搜索优化算法进行求解.算法采用群局部搜索,利用混沌变量产生一组分布好的初始解,并在邻域搜索进程中应用扩展贪心思想,提高了算法的全局搜索能力.仿真结果表明所提算法能够有效减少由于流量分布不平衡造成的网络拥塞,同时限制长路径,提高了网络性能.     

光网络中实现流量工程的负载均衡动态路由算法

提出了一种在光网络中实现流量工程的负载均衡动态路由算法(LBDRO).该算法通过新定义的链路关键度函数和链路当前可用带宽确定链路动态成本,并依据该动态成本运用最短路径优先算法为到达的LSP请求建立动态成本优化路径.该算法的计算复杂度低,仿真实验表明,与MHA、WSP、MIRA算法相比,在光传输网络中,该算法在降低LSP建立请求服务拒绝率、均衡网络负载以及链路失效后重路由等方面有很好的性能.     

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%.     

低开销的MANET网络按需路由协议

针对简单泛洪效率低的问题,提出了一个限制洪泛的高效的路由广播算法,通过Euclidean距离来限制路由发现过程中请求分组被转发的次数;研究了减少路由维护开销,并降低路由发现的频率的方法,提出了一个基于节点高度的路由修复与优化算法,该算法使用节点监听来对链路断裂的路由进行修复与优化.基于限制泛洪的高效的路由广播算法和路由修复优化算法,提出了一种新的低开销的MANET网络按需路由协议LOOR(low overhead on-demand routing).仿真结果表明,新协议增强了路由的顽健性,减少了路由跳数,降低了路由发现的频率,提高了数据分组递送率,并显著地降低了路由控制开销.     

基于混合CS的WSN六边形格状优化分簇路由算法研究

建立基于混合CS的六边形格状WSN分簇模型,定量分析网络数据传输次数与数据压缩比例和分簇大小的关系,并求解最优网络分簇个数。提出基于混合CS的WSN六边形格状优化分簇路由算法,均衡网络通信开销的同时减少数据传输次数。通过仿真实验验证所提出的优化分簇模型与算法优于传统分簇模型,能有效降低网络数据传输次数。建立基于混合CS的六边形格状WSN分簇模型,定量分析网络数据传输次数与数据压缩比例和分簇大小的关系,并求解最优网络分簇个数。提出基于混合CS的WSN六边形格状优化分簇路由算法,均衡网络通信开销的同时减少数据传输次数。通过仿真实验验证所提出的优化分簇模型与算法优于传统分簇模型,能有效降低网络数据传输次数。     

基于拓扑划分的片上网络快速映射算法

该文针对片上网络建立了以能耗和流量均衡为优化目标的映射模型,提出一种基于拓扑划分的快速映射算法(TPBMAP)。该算法不仅考虑芯片的布局特性从而产生规整的拓扑,还采用虚拟IP核技术修正通信核图以完成IP核和网络节点数不等的映射;通过引入以流量均衡为目标的优化模型同时将通信量大的IP核映射到拓扑边缘区域,有效地降低了网络中心的流量;采用迭代的拓扑划分方法以及将通信量大的IP核映射到网络相邻位置,可快速完成低能耗映射。仿真结果表明,相比现有算法,该文提出的算法在映射速度、全网能耗以及网络中心流量等方面有较大优势。     

Making Routing Robust to Changing Traffic Demands: Algorithms and Evaluation

Intra-domain traffic engineering can significantly enhance the performance of large IP backbone networks. Two important components of traffic engineering are understanding the traffic demands and configuring the routing protocols. These two components are inter-linked, as it is widely believed that an accurate view of traffic is important for optimizing the configuration of routing protocols, and through that, the utilization of the network. This basic premise, however, seems never to have been quantified. How important is accurate knowledge of traffic demands for obtaining good utilization of the network? Since traffic demand values are dynamic and illusive, is it possible to obtain a routing that is "robust" to variations in demands? We develop novel algorithms for constructing optimal robust routings and for evaluating the performance of any given routing on loosely constrained rich sets of traffic demands. Armed with these algorithms we explore these questions on a diverse collection of ISP networks. We arrive at a surprising conclusion: it is possible to obtain a robust routing that guarantees a nearly optimal utilization with a fairly limited knowledge of the applicable traffic demands     

Optimal Routing for Wireless Mesh Networks With Dynamic Traffic Demand

Wireless mesh networks have attracted increasing attention and deployment as a high-performance and low-cost solution to last-mile broadband Internet access. Traffic routing plays a critical role in determining the performance of a wireless mesh network. To investigate the best routing solution, existing work proposes to formulate the mesh network routing problem as an optimization problem. In this problem formulation, traffic demand is usually implicitly assumed as static and known a priori. Contradictorily, recent studies of wireless network traces show that the traffic demand, even being aggregated at access points, is highly dynamic and hard to estimate. Thus, in order to apply the optimization-based routing solution into practice, one must take into account the dynamic and unpredictable nature of wireless traffic demand. This paper presents an integrated framework for wireless mesh network routing under dynamic traffic demand. This framework consists of two important components: traffic estimation and routing optimization. By studying the traces collected at wireless access points, we first present a traffic estimation method which predicts future traffic demand based on its historical data using time-series analysis. This method provides not only the mean value of the future traffic demand estimation but also its statistical distribution. We further investigate the optimal routing strategies for wireless mesh network which take these two forms of traffic demand estimations as inputs. The goal is to balance the traffic load so that minimum congestion will be incurred. This routing objective could be transformed into the throughput optimization problem where the throughput of aggregated flows is maximized subject to fairness constraints that are weighted by the traffic demands. Based on linear programming, we present two routing algorithms which consider the mean value and the statistical distribution of the predicted traffic demands, respectively. The trace-driven simulation study demonstrates that our integrated traffic estimation and routing optimization framework can effectively incorporate the traffic dynamics in mesh network routing.     

Routing Strategies to Minimize Packet Loss in an Optical Packet Switched Network with Recirculating FDL Buffers

The major goal of optical packet switching (OPS) is to match switching technology to the huge capacities provided by (D)WDM. We study optical packet switches with recirculating fiber delay line (FDL) buffers. Through simulation, we have assessed the logical performance of a single optical packet router (OPR), focusing on packet loss rate (PLR). By verifying that our scheduling algorithm does not alter the traffic profile characteristics from in- to output, we illustrate how the single node results can be used to assess network-wide performance. We use the capability of assessing end-to-end PLRs to develop network-wide routing algorithms designed to minimize the maximal PLR occurring in the network. In case studies on pan-European networks, we first compare two algorithm variants and thereafter we compare the PLR-based routing algorithm with both load balancing and shortest path routing. While load balancing achieves PLRs that are multiple orders of magnitude lower than shortest path routing, the PLR-based algorithm can reach PLRs up to two orders of magnitude better. The improvement in PLR comes at the price of only a small increase in used bandwidth (a few percent). Subsequently we show that the discussed PLR-based routing algorithm can be easily extended to multiple priorities. By introducing multiple priorities we can keep the loss rates for high priority traffic very low. However, it may lead to an increase of the obtained minimal max-PLR value for low priority traffic. But as we prove this increase to be limited, the cost of introducing multiple priorities is small.     

GATEway: symbiotic inter-domain traffic engineering

There are a group of problems in networking that can most naturally be described as optimization problems (network design, traffic engineering, etc.). There has been a great deal of research devoted to solving these problems, but this research has been concentrated on intra-domain problems where one network operator has complete information and control. An emerging field is inter-domain engineering, for instance, traffic engineering between large autonomous networks. Extending intra-domain optimization techniques to inter-domain problems is often impossible without the information available within a domain, and providers are often unwilling to share such information. This paper presents an alternative: we propose a method for traffic engineering that does not require sharing of important information across domains. The method extends the idea of genetic algorithms to allow symbiotic evolution between two parties. Both parties may improve their performance without revealing their data, other than what would be easily observed in any case. We show the method provides large reductions in network congestion, close to the optimal shortest path routing across a pair of networks. The results are highly robust to measurement noise, the method is very flexible, and it can be applied using existing routing.     

A topology and application‐aware relay path allocation scheme in multipath transport system based on application‐level relay

The ever‐increasing transmission requirements of quality of service (QoS)‐sensitive applications, especially real‐time multimedia applications, can hardly be met by the single path routing protocols. Multipath transmission mechanism is a feasible approach to provide QoS for various applications. On the basis of the general framework of multipath transport system based on application‐level relay, we present a relay path allocation scheme, whose goal is to select suitable relay paths, while balancing the overlay traffic among the different domains and relayers. With the application‐layer traffic optimization service under the standardization within the Internet Engineering Task Force (IETF), the controller has the topology‐aware ability to allocate relay paths with excellent routing performance. To further develop the universality of our method, the controller perceives transmission performance of relay overlay network through relayers' performance detection processes and, thus, has the application‐aware ability to allocate relay paths with excellent transmission performance for different applications by consulting application‐specific transmission metrics. Simulation results demonstrate that the proposed relay path allocation algorithm performs well in allocating superior relay paths and can balance the distribution of overlay traffic across domains in different network situations.     

LEO星座中基于不完全信息的路由联盟博弈策略

针对LEO卫星网络在多跳转发数据包时流量分布不均问题,提出了一种基于不完全信息的最优收益路由联盟博弈算法.各节点协同联盟邻居节点,共同确定数据报文当前最优转发路径,从而分配和平衡节点间流量负载.仿真结果表明,与最短路径卫星路由DSP或智能路由TLR相比,本文算法的平均数据传输延迟降低了18.5%,节点流量负载均衡度提高了65.6%.     

Enabling novel premium service classes in DiffServ over MPLS‐enabled network

Network resources dimensioning and traffic engineering influence the quality in provisioned services required by the Expedited Forwarding (EF) traffic in production networks established through DiffServ over MPLS‐enabled network. By modeling EF traffic flows and the excess of network resources reserved for it, we derive the range of delay values which are required to support these flows at DiffServ nodes. This enables us to develop an end‐to‐end (e2e) delay budget‐partitioning mechanism and traffic‐engineering techniques within a framework for supporting new premium QoS levels, which are differentiated based on e2e delay, jitter and loss. This framework enables ingress routers to control EF traffic flow admission and select appropriate routing paths, with the goal of EF traffic balancing, avoiding traffic congestion and getting the most use out of the available network resources through traffic engineering. As a result, this framework should enable Internet service providers to provide three performance levels of EF service class to their customers provided that their network is DiffServ MPLS TE aware. Copyright © 2008 John Wiley & Sons, Ltd.     

A novel four-tier software-defined network architecture for scalable secure routing and load balancing

Software-defined networking is an emerging paradigm for supporting flexible network management. In the traditional architecture for a software-defined network (SDN), the controller commonly uses a general routing algorithm such as Open Shortest Path First (OSPF), which chooses the shortest path for communication. This may cause the largest amount of network traffic, especially in large-scale environments. In this paper, we present the design for a novel SDN-based four-tier architecture for scalable secure routing and load balancing. In Tier 1, user authentication is conducted using elliptic curve cryptography (ECC); this avoids unnecessary loads from unauthorized users. In Tier 2, packet classification is performed based on the packet characteristics using the fuzzy analytical hierarchy process (fuzzy AHP), and packets are placed into three individual queues. In Tier 3, scalable secure routing is achieved by selecting the optimal path using the improved particle swarm optimization and ant colony optimization algorithms. With these optimization algorithms, we can adaptively change the number of users, the number of switches, and other parameters. In Tier 4, the recommended secure cluster (multicontroller) management is accomplished using an algorithm that employs modified k-means clustering and a recurrent neural network. Deep reinforcement learning (DRL) is also proposed for updating the controller information. Experimental results are analyzed using the OMNeT++ network simulator, and the evaluated performance displayed improvement over a variety of existing methods in terms of response time (50% to 60%), load (55%), execution time (3.2%), throughput (9.8%), packet loss rate (1.02%), end-to-end delay (50%), and bandwidth consumption (45%).     

Optimal Link Weights for IP-Based Networks Supporting Hose-Model VPNs

From traffic engineering point of view, hose-model VPNs are much easier to use for customers than pipe-model VPNs. In this paper we explore the optimal weight setting to support hose-model VPN traffic in an IP-based hop-by-hop routing network. We try to answer the following questions: (1) What is the maximum amount of hose-model VPN traffic with bandwidth guarantees that can be admitted to an IP-based hop-by-hop routing network (as opposed to an MPLS-based network), and (2) what is the optimal link weight setting that can achieve that? We first present a mixed-integer programming formulation to compute the optimal link weights that can maximize the ingress and egress VPN traffic admissible to a hop-by-hop routing network. We also present a heuristic algorithm for solving the link weight searching problem for large networks. We show simulation results to demonstrate the effectiveness of the search algorithm.