A generalized service deployment framework for OSPF networks using multi‐topology routing: Modeling and methodology

The exponential growth of various applications requires deploying an ever‐growing number of network services. A generalized service deployment framework for Open Shortest Path First (OSPF) networks is proposed in this paper. The framework includes placing programmable routers, distributing different types of services on these routers, and leading traffic flow through them according to the predetermined sequence order requirement. However, it is not possible to direct all the traffic flows through the required service nodes along the shortest path with a single and suitable set of link weights. To address the issue, multiple topology routing (MTR) technique is incorporated to have various logical topologies with multiple sets of link weights. Correspondingly, the problem of jointly optimizing Placement of programmable routers, Distribution of different types of services among these routers, and Link Weights setting based on MTR (shortened to PD‐LW‐MTR) and its mixed integer linear programming formulation are presented in this paper. A novel decomposition algorithm is also proposed to address this problem efficiently. Experiment results validate the correctness and feasibility of our algorithm. It is also shown that the optimization algorithm can obtain near‐optimal solution and just only a few logical topologies over multiple sets of link weights are necessary for traffic flows to guarantee service order requirements.     

A novel all-optical transport network with time-shared wavelength channels

High-speed and high-capacity transport networks are necessary for providing future broadband services and multimedia applications. Optical networks, such as wavelength-routed networks and optical switching networks, are the most popular solutions. However, the limited electronic switching capability constrains the scalability of the multihop wavelength routed networks, while the difficulty and complexity of implementing efficient optical buffers and optical contention resolution schemes constrains the development of optical switching networks. This paper proposes a new architecture for the optical transport networks based on time-wavelength-space routers (TWSRs). The TWSR is equipped without optical buffers and optical contention resolution devices. A connection is established by constructing a time-slot based lightpath (ts-lightpath) between source TWSR and destination TWSR. The paper also proposes a heuristic algorithm for the problem of establishing the set of efficient ts-lightpaths for a given set of connection requests. The effectiveness of the proposed network architecture with the heuristic algorithm is demonstrated by simulation.     

一种在DS-TE网络环境中新的LSP抢占算法

现有的启发式抢占算法不易找到最优解,容易造成带宽的浪费。文中通过分析DS-TE（Differentiated Services Traffic Engineering）网络环境中的抢占策略,提出了一种优化的抢占算法GA-PREPT（Genetic Algorithm Preemption）。GA-PREPT利用遗传算法进行LSP（Label Switch Path）的优化选择,同时针对抢占问题的约束条件在进行选择操作时引入模拟退火选择算子,指导进化过程的选择操作。仿真结果表明GA-PREPT性能相比现有的启发式抢占算法有较大改善。     

Optimal Advertising Campaign Generation for Multiple Brands Using MOGA

The paper proposes a new modified multiobjective genetic algorithm (MOGA) for the problem of optimal television (TV) advertising campaign generation for multiple brands. This NP-hard combinatorial optimization problem with numerous constraints is one of the key issues for an advertising agency when producing the optimal TV mediaplan. The classical approach to the solution of this problem is the greedy heuristic, which relies on the strength of the preceding commercial breaks when selecting the next break to add to the campaign. While the greedy heuristic is capable of generating only a group of solutions that are closely related in the objective space, the proposed modified MOGA produces a Pareto-optimal set of chromosomes that: 1) outperform the greedy heuristic; and 2) let the mediaplanner choose from a variety of uniformly distributed tradeoff solutions. To achieve these results, the special problem-specific solution encoding, genetic operators, and original local optimization routine were developed for the algorithm. These techniques allow the algorithm to manipulate with only feasible individuals, thus, significantly improving its performance that is complicated by the problem constraints. The efficiency of the developed optimization method is verified using the real data sets from the Canadian advertising industry.     

Filtering Location Optimization for Defending Against Large-Scale BDoS Attacks

This paper focuses on selecting the appro-priate filtering location to minimize the amount of filter-ing routers in the traceback-based packet filtering for de-fending against the large-scale Bandwidth denial-of-service (BDoS) attacks. The filtering location can be viewed as a resource allocation problem and further we formulate it to an integer linear programming model and design an exact and computationally efficient filtering location algorithm. The evaluation results show that our algorithm brings sig-nificant benefits in practice.     

An energy efficient channel assignment and routing algorithm for multi-radio wireless mesh networks

Endowing mesh routers with multiple radios is a recent solution to improve the performance of wireless mesh networks. Solving the problem how to assign channels to radios has attracted a lot of attention in the recent years, partly because of the hardness of solving the channel assignment problem jointly with the routing problem. However, the approaches proposed in the literature so far have mainly focused on reducing interference or maximizing the throughput. Little attention has been paid to the energy consumption of wireless mesh networks, given that mesh nodes are usually connected to a power source. However, with the rising concerns about the energy consumed by communication infrastructures, it makes sense to consider the minimization of the energy consumption as an objective of the channel assignment and routing problem. Our work stems from the observation that an idle radio simply overhearing a frame consumes nearly the same power as the radio actually receiving the frame. Hence, energy may be saved by turning off a number of radios, if the performance of the network is not impaired. In this paper, we define the energy efficient channel assignment and routing problem, show that it is NP-hard and propose a heuristic algorithm. For the purpose of comparing the solution found by the proposed algorithm to the optimal solution, we also present two Mixed Integer Linear Programs (MILPs) that optimally solve the problem we address. Finally, we show the results of extensive simulation studies we conducted to assess the effectiveness of the proposed algorithm.     

Design of OSPF networks using subpath consistent routing patterns

We address the problem of designing IP networks where the traffic is routed using the OSPF protocol. Routers in OSPF networks use link weights set by an administrator for determining how to route the traffic. The routers use all shortest paths when traffic is routed to a destination, and the traffic is evenly balanced by the routers when several paths are equally short. We present a new model for the OSPF network design problem. The model is based on routing patterns and does not explicitly include OSPF weights. The OSPF protocol is modeled by ensuring that all pairs of routing patterns are subpath consistent, which is a necessary condition for the existence of weights. A Lagrangean heuristic is proposed as solution method, and feasible solutions to the problem are generated using a tabu search method. Computational results are reported for random instances and for real-life instances.     

路由器接口别名解析技术研究

描述了现行的路由器接口解决方法,在对关键技术进行了分析的基础上,提出了并实现了一种路由器别名解析归并算法,该算法通过对协议进行分析,综合数据融合技术,将路由器的接口地址集合转换为能够反映实际网络状况的路由器集合,从而较好地提高了路由器探测的准确性和完整性。     

A heuristic algorithm for lightpath scheduling in next-generation WDM optical networks

We study the routing and wavelength assignment (RWA) problem of scheduled lightpath demands (SLDs) in all-optical wavelength division multiplexing networks with no wavelength conversion capability. We consider the deterministic lightpath scheduling problem in which the whole set of lightpath demands is completely known in advance. The objective is to maximize the number of established lightpaths for a given number of wavelengths. Since this problem has been shown to be NP complete, various heuristic algorithms have been developed to solve it suboptimally. In this paper, we propose a novel heuristic RWA algorithm for SLDs based on the bee colony optimization (BCO) metaheuristic. BCO is a newborn swarm intelligence metaheuristic approach recently proposed to solve complex combinatorial optimization problems. We compare the efficiency of the proposed algorithm with three simple greedy algorithms for the same problem. Numerical results obtained by numerous simulations performed on the widely used realistic European Optical Network topology indicate that the proposed algorithm produces better-quality solutions compared to those obtained by greedy algorithms. In addition, we compare the results of the BCO–RWA–SLD algorithm with four other heuristic/metaheuristic algorithms proposed in literature to solve the RWA problem in the case of permanent (static) traffic demands.     

SS/TDMA scheduling for satellite clusters

The authors present a novel approach to the optimal time-slot assignment problem for a general satellite-switched time-division multiple-access (SS/TDMA) satellite cluster with intersatellite links (ISLs) interconnection. The proposed allocation algorithm accounts for the following: systems with any number of satellites; each satellite covers an arbitrary number of zones; no onboard buffering at the satellites; and ISLs with arbitrary capacities. They present an analogy between the satellite cluster scheduling problem and the modified openshop scheduling problem. Using this analogy the authors introduce a heuristic algorithm and an optimal branch-and-bound algorithm. They investigate the performance of the proposed heuristic both by theoretical bounds and by comparing the simulation results produced by the heuristic with the optimal results. In all cases the heuristic algorithm results are within 10% of the optimum     

Network Topology Inference Based on End-to-End Measurements

We consider using traceroute-like end-to-end measurement to infer the underlay topology for a group of hosts. One major issue is the measurement cost. Given N hosts in an asymmetric network without anonymous routers, traditionally full N(N-1) traceroutes are needed to determine the underlay topology. We investigate how to efficiently infer an underlay topology with low measurement cost, and propose a heuristic called Max-Delta. In the heuristic, a server selects appropriate host-pairs to measure in each iteration so as to reveal the most undiscovered information on the underlay. We further observe that the presence of anonymous routers significantly distorts and inflates the inferred topology. Previous research has shown that obtaining both exact and approximate topology in the presence of anonymous routers under certain consistency constraints is intractable. We hence propose fast algorithms on how to practically construct an approximate topology by relaxing some constraints. We investigate and compare two algorithms to merge anonymous routers. The first one uses Isomap to map routers into a multidimensional space and merges anonymous routers according to their interdistances. The second algorithm is based on neighbor router information, which trades off some accuracy with speed. We evaluate our inference algorithms on Internet-like and real Internet topologies. Our results show that almost full measurement is needed to fully discover the underlay topology. However, substantial reduction in measurements can be achieved if a little accuracy, say 5%, can be compromised. Moreover, our merging algorithms in the presence of anonymous routers can efficiently infer an underlay topology with good accuracy     

Survivable deployment of cloud-integrated fiber-wireless networks against multi-fiber failure

Cloud-integrated fiber-wireless (FiWi) networks inheriting advantages of optical and wireless access networks have a broad prospect in the future. As various component failures may occur in cloud-integrated FiWi networks, survivability is becoming one of the key important issues. It is necessary to provide survivability strategies for cloud-integrated FiWi networks. Hence, this paper mainly focuses on the survivability of cloud-integrated FiWi networks against multiple fibers failure. Firstly, in this paper, a novel integer linear programming (ILP) solution is proposed to tolerate the failure of multiple distribution fibers with capacity and coverage constraints in the context of urban area. Then, considering the complexity of ILP models, an efficient heuristic scheme is proposed, in order to get the approximate solutions of ILP. Simulation results and analysis give the configurations of optical network units (ONUs) and wireless routers with different constraints and show the network coverage of clients for different number of ONUs and wireless routers with ILP solution and heuristic approach, respectively.     

Recherche locale à voisinage variable pour le routage optique dans des réseaux utilisant des routeurs latins

This paper proposes an approach based on Variable Neighbourhood Search (vns) to solve the Routing and Wavelength Assignment (rwa) problem in optical networks including latin routers. It can be summed up as establishing routing (finding intermediate routers on optical paths between each origin/destination pair) and wavelength assignment of these optical paths in such networks. The problem will be tackled according to two scenarii: to optimize the number of established connections (scenario 1) or to answer as well as possible an accurate traffic array (scenario 2). In traditional optical networks (without latin routers), one often separates routing and wavelength assignment because of the general problem complexity (each of the two sub-problems isnp-hard). However, latin routers introduce constraints connecting routing and assignment, this requires a simultaneous treatment of the two problems. A local search heuristic,vnsfor, based on the definition of different neighbourhoods (with simple and double moves) is proposed in this paper to provide us with solutions close to the optimum. Experimental results show howvnsfor leads to better solutions, according to both scenarii, in comparison with the reference algorithmlonca.     

Minimizing the Number of Multicast Transmissions in Single-Hop WDM Networks

The problem of minimizing the number of transmissions for a multicast transmission under the condition that the packet delay is minimum in single-hop wavelength division multiplexing (WDM) networks is studied in this paper. This problem is proved to be NP-complete. A heuristic multicast scheduling algorithm is proposed for this problem. Extensive simulations are performed to compare the performance of the proposed heuristic algorithm with two other multicast scheduling algorithms, namely, the greedy and no-partition scheduling algorithms. The greedy algorithm schedules as many destination nodes as possible in the earliest data slot. The no-partition algorithm schedules the destination nodes of a multicast packet to receive the packet in the same data slot without partitioning the multicast transmission into multiple unicast or multicast transmissions. Our simulation results show that (i) an algorithm which partitions a multicast transmission into multiple unicast or multicast transmissions may not always produce lower mean packet delay than the no-partition algorithm when the number of data channels in the system is limited and (ii) the proposed heuristic algorithm always produces lower mean packet delay than the greedy and the no-partition algorithms because this algorithm not only partitions a multicast transmission into multiple unicast or multicast transmissions to keep the packet delay low but also reduces the number of transmissions to conserve resources.     

基于压缩NH表的高速IP路由查找算法的研究

由于因特网速度不断提高、网络流量不断增加和路由表规模不断扩大,IP路由查找已经成为制约核心路由器性能的主要原因,因而受到了广泛重视.目前人们已经提出几种高速IP路由查找算法,但没有一种是理想的.本文提出一种使用压缩NH表进行IP路由查找的方法,它具有查找速率高、更新时间快、存储代价低、易于实现等特点,能满足10Gbps速率核心路由器环境的要求.     

一种约束布局求解算法的改进

针对一个实际问题,讨论了一种约束布局的启发式算法,提出了约束布局求解的启发式规则及相应的布局方案求解策略,改进后的算法具有很强的灵活性和柔性,同时还对该算法的实际性能进行了仿真,结果表明了改进算法的有效性和合理性.     

A new channel, power and rate assignment algorithm for?multi-radio wireless mesh networks

Endowing mesh routers with multiple radios is a recent solution to improve the performance of wireless mesh networks. The consequent problem to assign channels to radios has been recently investigated and its relation to the routing problem has been revealed. The joint channel assignment and routing problem has been shown to be NP-complete and hence mainly heuristics have been proposed. However, such heuristics consider wireless links just like wired links, whereas disregarding their peculiar features. In this paper, we consider the impact of tuning the transmission power and rate of the wireless links on the efficiency of the channel assignment. Then, we present a channel, power and rate assignment heuristic and compare its performance to previously proposed algorithms.     

Design and analysis of distributed utility maximization algorithm for multihop wireless network with inaccurate feedback

Distributed network utility maximization (NUM) is receiving increasing interests for cross‐layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time‐varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. Copyright © 2013 John Wiley & Sons, Ltd.     

Multicast Flow Aggregation in IP over Optical Networks

It is widely believed that IP over optical networks will be a major component of the next generation Internet However, it is not efficient to map a single multicast IP flow into one light-tree, since the bandwidth of an IP flow required is usually much less than that of a light-tree. In this paper, we study the problem of multicast flow aggregation (MFA) in the IP over optical two-layered networks under the overlay model, which can be defined as follows: given a set of head ends (i.e. optical multicasting sources), each of which can provide a set of contents (i.e. multicast IP flows) with different required transmission bandwidth, and a set of requested content at the access routers (i.e. optical multicasting destinations), find a set of light-trees as well as the optimal aggregation of multicast IP flows in each light-tree. We model MFA by a tri-partite graph with multiple criteria and show that the problem is NP-complete. Optimal solutions are designed by exploiting MFA to formulate an integer linear programming (ILP), with two parameters: the multicast receiving index alpha and the redundant transmitting index beta. We also propose a heuristic algorithm. Finally, we compare the performance of MFA for different combination of alpha and beta via experiments and show our heuristic algorithm is effective for large-scale network in numerical results     

Multiclass scheduling algorithms for the DAVID metro network

The data and voice integration over dense wavelength-division-multiplexing (DAVID) project proposes a metro network architecture based on several wavelength-division-multiplexing (WDM) rings interconnected via a bufferless optical switch called Hub. The Hub provides a programmable interconnection among rings on the basis of the outcome of a scheduling algorithm. Nodes connected to rings groom traffic from Internet protocol routers and Ethernet switches and share ring resources. In this paper, we address the problem of designing efficient centralized scheduling algorithms for supporting multiclass traffic services in the DAVID metro network. Two traffic classes are considered: a best-effort class, and a high-priority class with bandwidth guarantees. We define the multiclass scheduling problem at the Hub considering two different node architectures: a simpler one that relies on a complete separation between transmission and reception resources (i.e., WDM channels) and a more complex one in which nodes fully share transmission and reception channels using an erasure stage to drop received packets, thereby allowing wavelength reuse. We propose both optimum and heuristic solutions, and evaluate their performance by simulation, showing that heuristic solutions exhibit a behavior very close to the optimum solution.