Valiant load-balanced robust routing algorithm for multi-granularity connection requests in traffic-grooming WDM mesh networks

The paper considers the problem of establishing robust routes for multi-granularity connection requests in traffic-grooming WDM mesh networks and proposes a novel Valiant load-balanced robust routing scheme for the hose uncertain model. Our objective is to minimize the total network cost when construct the stable virtual topology that assure robust routing for all possible multi-granularity connection requests under the hose model. Since the optimization problem is shown to be NP-complete, two heuristic algorithms are proposed and evaluated. Finally we compare the traffic throughput of the virtual topology by Valiant load-balanced robust routing scheme with that of the traditional traffic-grooming algorithm under the same total network cost by computer simulation.     

多信道无线网状网自适应路由算法

针对无线网状网的网络容量优化问题,通过建立无线网状网容量优化的数学模型,利用线性规划公式对无线网状网的路由问题进行描述,在此基础上提出了一个自适应路由算法。根据网络的拓扑结构和业务请求特点,自适应地改变路由扩张因子和负载均衡率进行优化路由,达到提高无线网状网的网络容量的目的。仿真结果表明,该算法能明显提高网络容量。     

Optimization models and methods for planning wireless mesh networks

In this paper novel optimization models are proposed for planning Wireless Mesh Networks (WMNs), where the objective is to minimize the network installation cost while providing full coverage to wireless mesh clients. Our mixed integer linear programming models allow to select the number and positions of mesh routers and access points, while accurately taking into account traffic routing, interference, rate adaptation, and channel assignment. We provide the optimal solutions of three problem formulations for a set of realistic-size instances (with up to 60 mesh devices) and discuss the effect of different parameters on the characteristics of the planned networks. Moreover, we propose and evaluate a relaxation-based heuristic for large-sized network instances which jointly solves the topology/coverage planning and channel assignment problems. Finally, the quality of the planned networks is evaluated under different traffic conditions through detailed system level simulations.     

多信道无线Mesh网络负载均衡路由算法研究

针对无线网状网的网络容量问题,在多信道无线网状网模型的基础上,利用线性规划公式对无线网状网的路由问题进行描述,在此基础上提出了一个负载均衡的路由算法,在对业务请求的路由跳步数进行约束的前提上,通过减少网络链路上的负载,达到提高网络的吞吐量的目的。仿真结果表明,提出的算法能显著提高网络性能。     

Deadlock free routing algorithms for irregular mesh topology NoC systems with rectangular regions

The simplicity of regular mesh topology Network on Chip (NoC) architecture leads to reductions in design time and manufacturing cost. A weakness of the regular shaped architecture is its inability to efficiently support cores of different sizes. A proposed way in literature to deal with this is to utilize the region concept, which helps to accommodate cores larger than the tile size in mesh topology NoC architectures. Region concept offers many new opportunities for NoC design, as well as provides new design issues and challenges. One of the most important among these is the design of an efficient deadlock free routing algorithm. Available adaptive routing algorithms developed for regular mesh topology cannot ensure freedom from deadlocks. In this paper, we list and discuss many new design issues which need to be handled for designing NoC systems incorporating cores larger than the tile size. We also present and compare two deadlock free routing algorithms for mesh topology NoC with regions. The idea of the first algorithm is borrowed from the area of fault tolerant networks, where a network topology is rendered irregular due to faults in routers or links, and is adapted for the new context. We compare this with an algorithm designed using a methodology for design of application specific routing algorithms for communication networks. The application specific routing algorithm tries to maximize adaptivity by using static and dynamic communication requirements of the application. Our study shows that the application specific routing algorithm not only provides much higher adaptivity, but also superior performance as compared to the other algorithm in all traffic cases. But this higher performance for the second algorithm comes at a higher area cost for implementing network routers.     

On basic properties of fault-tolerant multi-topology routing

Multi-topology routing has recently gained popularity as a simple yet efficient traffic engineering concept. Its basic purpose is to separate different classes of network traffic, which are then transported over disjoint logical topologies. Multi-topology routing is used as a basis for implementation of an IP fast reroute scheme called Multiple Routing Configurations (MRC).MRC has a range of attractive properties, but they do come at a cost. In order to guarantee recovery from any single link or node failure in the network, MRC has to maintain several logical topologies and thus an increased amount of routing information. The number of the logical topologies in MRC need not be large; even simple heuristic algorithms often yield good results in practice. However, why this is the case is not fully understood yet.In this paper, we introduce a theoretical framework for fault-tolerant multi-topology routing (FT-MTR). MRC is a practical implementation of FT-MTR in connectionless IP networks. We use FT-MTR to study how the internal topological structure of the communication network relates to two important problems. The first problem is minimizing the number of logical topologies and thus the routing state in FT-MTR. We show how to use the sets of nodes that separate the topology graph to devise an advanced heuristic for “intelligent” construction of the logical topologies. Finding the separating sets in a topology graph is computationally demanding; we present an algorithm that performs well in tested real network topologies. We evaluate the separation-set based heuristic for the logical topology construction and show that it outperforms the known MRC heuristics.The second problem is the FT-MTR load distribution after a failure. We use the separating sets to devise a novel algorithm for failure load distribution. This algorithm does not require knowledge of the traffic demand matrix, still, our tests indicate that it performs as good as, or better than, known MRC load-distribution algorithms that do require the demand matrix as input.     

Joint VM placement and topology optimization for traffic scalability in dynamic datacenter networks

In dynamic datacenter networks (DDNs), there are two ways to handle growing traffic: adjusting the network topology according to the traffic and placing virtual machines (VMs) to change the workload according to the topology. While previous work only focused on one of these two approaches, in this paper, we jointly optimize both virtual machine placement and topology design to achieve higher traffic scalability. We formulate this joint optimization problem to be a mixed integer linear programming (MILP) model and design an efficient heuristic based on Lagrange’s relaxation decomposition. To handle traffic dynamics, we introduce an online algorithm that can balance algorithm performance and overhead. Our extensive simulation with various network settings and traffic patterns shows that compared with randomly placing VMs in fixed datacenter networks, our algorithm can reduce up to 58.78% of the traffic in the network, and completely avoid traffic overflow in most cases. Furthermore, our online algorithm greatly reduces network cost without sacrificing too much network stability.     

带度约束的最小直径应用层多播路由问题的启发式遗传算法

由于IP多播难以在因特网环境中配置，应用层多播作为IP多播的一种替代方案得到越来越多的研究。从网络设计的角度来看，应用层多播在网络代价模型及路由策略方面与传统的IP多播有很大区别。本文研究了带度约束的最小直径应用层网络多播路由问题，提出了解决该问题的启发式遗传算法。通过大量仿真实验，我们对比分析了两种贪婪算法法和遗传算法的性能。实验显示，启发式遗传算法具有较好的性能。     

求解传感器网络生存时间最大化问题的遗传算法编码设计

求解传感器网络最大生存时间是设计高性能路由协议和拓扑控制协议的理论基础，在实践上有很重要的意义。目前主要通过近似算法求解，而且没有考虑到接收功耗。本文对生存时间优化问题进行了形式化描述，给出了最佳传输方案和最大生存时间的定义，从遗传算法角度给出了求解该问题的两个编码方案并进行了比较。     

Joint gateway selection,transmission slot assignment,routing and power control for wireless mesh networks

Wireless mesh networks (WMNs) provide cost effective solutions for setting up a communications network over a certain geographic area. In this paper, we study strategic problems of WMNs such as selecting the gateway nodes along with several operational problems such as routing, power control, and transmission slot assignment. Under the assumptions of the physical interference model and the tree-based routing restriction for traffic flow, a mixed integer linear programming (MILP) formulation is presented, in which the objective is to maximize the minimum service level provided at the nodes. A set of valid inequalities is derived and added to the model in an attempt to improve the solution quality. Since the MILP formulation becomes computationally infeasible for larger instances, we propose a heuristic method that is aimed at solving the problem in two stages. In the first stage, we devise a simple MILP problem that is concerned only with the selection of gateway nodes. In the second stage, the MILP problem in the original formulation is solved by fixing the gateway nodes from the first stage. Computational experiments are provided to evaluate the proposed models and the heuristic method.     

Performance evaluation of mesh-based NoCs: Implementation of a new architecture and routing algorithm

This paper presents the result of experiments conducted in mesh networks on different routing algorithms, traffic generation schemes and switching schemes. A new network on chip (NoC) topology based on partial interconnection of mesh network is proposed and a routing algorithm supporting the proposed architecture is developed. The proposed architecture is similar to standard mesh networks, where four extra bidirectional channels are added which remove the congestion and hotspots compared to standard mesh networks with fewer channels. Significant improvement in delay (60% reduction) and throughput (60% increase) was observed using the proposed network and routing when compared with the ideal mesh networks. An increase in number of channels makes the switches expensive and could increase the area and power consumption. However, the proposed network can be useful in high speed applications with some compromise on area and power.     

Hierarchical multiobjective routing in Multiprotocol Label Switching networks with two service classes: a heuristic solution

Modern multiservice network routing functionalities have to deal with multiple, heterogeneous and multifaceted Quality of Service (QoS) requirements. A heuristic approach devised to find "good" solutions to a hierarchical multiobjective alternative routing optimization problem in Multiprotocol Label Switching networks with two service classes (and different types of traffic flows in each class), namely QoS and Best Effort services, formulated within a hierarchical network-wide optimization framework, is presented. This heuristic solution is based on a bi-objective constrained shortest path model and is applied to a test network used in a benchmarking case study. An experimental study based on analytic and discrete event simulation results is presented, allowing for an assessment of the quality of results obtained with this new heuristic solution for various traffic matrices. A dynamic version of the routing method is formulated and its performance with the same case study network is analysed.     

Discretized learning automata solutions to the capacity assignment problem for prioritized networks

We present a discretized learning automaton (LA) solution to the capacity assignment (CA) problem which focuses on finding the best possible set of capacities for the links that satisfy the traffic requirements in a prioritized network while minimizing the cost. Most approaches consider a single class of packets flowing through the network, but in reality, different classes of packets with different average packet lengths and different priorities are transmitted over the networks. This generalized model is the focus of this paper. Although the problem is inherently NP-hard, a few approximate solutions have been proposed in the literature. Marayuma and Tang (1977) proposed a single algorithm composed of several elementary heuristic procedures. Other solutions tackle the problem by using modern-day artificial intelligence (AI) paradigms such as simulated annealing and genetic algorithms (GAs). In 2000, we introduced a new method, superior to these, that uses continuous LA. In this paper, we present a discretized LA solution to the problem. This solution uses a meta-action philosophy new to the field of LA, and is probably the best available solution to this extremely complex problem.     

A genetic algorithm for the multiple destination routing problems

The multiple destination routing (MDR) problem can be formulated as finding a minimal cost tree which contains designated source and multiple destination nodes so that certain constraints in a given communication network are satisfied. This is a typical NP-hard problem, and therefore only heuristic algorithms are of practical value. As a first step, a new genetic algorithm is developed to solve the MDR problems without constraints. It is based on the transformation of the underlying network of an MDR problem into its distance complete form, a natural chromosome representation of a minimal spanning tree (an individual), and a completely new computation of the fitness of individual. Compared with the known genetic algorithms and heuristic algorithms for the same problem, the proposed algorithm has several advantages. First, it guarantees convergence to an optimal solution with probability one. Second, not only are the resultant solutions all feasible, the solution quality is also much higher than that obtained by the other methods (indeed, in almost every case in our simulations, the algorithm can find the optimal solution of the problem). Third, the algorithm is of low computational complexity, and this can be decreased dramatically as the number of destination nodes in the problem increases. The simulation studies for the sparse and dense networks all demonstrate that the proposed algorithm is highly robust and very efficient in the sense of yielding high-quality solutions     

A two-level location–allocation problem in designing local access fiber optic networks

This paper deals with a two-level facility location–allocation problem on tree topology arising from the design of access networks. The access network design problem seeks to find an optimal location of switch and allocation of demands such that the total cost of switch and fiber cable is minimized, while satisfying switch port constraint, switch capacity constraint, and no-split routing constraint. The problem is formulated as a mixed-integer programming model and alternative formulations are developed by the reformulation-linearization technique (RLT) for improving computational effectiveness. By exploiting the tree structure of the problem, we develop some valid inequalities that have complementary strength and devise separation problems for finding effective valid inequalities that cut off fractional LP solutions. Also, we develop an effective MIP-based tree partitioning heuristic for finding good quality solutions for large size problems. Computational results demonstrate the efficacy of the valid inequalities and the proposed heuristic.     

A note on distributed multicast routing in point-to-point networks

The distributed algorithm for a multicast connection set-up, based on the ‘cheapest insertion’ heuristic, is reviewed. The multicast routing problem is translated into a Steiner tree problem in point-to-point networks where nodes have only a limited knowledge about the network. A solution is proposed in which the time complexity and the amount of information exchanged between network nodes are proportional to the number of members of the multicast group. The Steiner tree is constructed by means of a distributed table-passing algorithm. The analysis of the algorithm presented, backed up by simulation results, confirms its superiority over the algorithm based on ‘waving technique’.Scope and purposeMulticasting is a mechanism used in communication networks that allows distribution of information from a single source to multiple destinations. The problem of finding a multicast connection for a static group of communicating entities in connection-oriented point-to-point network can be formulated in graph theory as a minimum Steiner tree problem. Due to NP-completeness of the Steiner tree problem multicast, routing algorithms are based on heuristics. The diversity of network environments and the lack of centralised information about network topology require an effective distribution of the multicast routing algorithms among the network nodes. This article presents an alternative to the distributed algorithm proposed by Rugelj and Klavzar that implements the same heuristics for the construction of a minimum cost multicast connection in point-to-point networks. The present algorithm constitutes a substantial improvement over that previously proposed with regard to running time and the amount of the information exchanged between network nodes.     

Topology Design of Network-Coding-Based Multicast Networks

It is anticipated that a large amount of multicast traffic needs to be supported in future communication networks. The network coding technique proposed recently is promising for establishing multicast connections with a significantly lower bandwidth requirement than that of traditional Steiner-tree-based multicast connections. How to design multicast network topologies with the consideration of efficiently supporting multicast by the network coding technique becomes an important issue now. It is notable, however, that the conventional algorithms for network topology design are mainly unicast-oriented, and they cannot be adopted directly for the efficient topology design of network-coding-based multicast networks by simply treating each multicast as multiple unicasts. In this paper, we consider for the first time the novel topology design problem of network-coding-based multicast networks. Based on the characteristics of multicast and network coding, we first formulate this problem as a mixed-integer nonlinear programming problem, which is NP-hard, and then propose two heuristic algorithms for it. The effectiveness of our heuristics is verified through simulation and comparison with the exhaustive search method. We demonstrate in this paper that, in the topology design of multicast networks, adopting the network coding technique to support multicast transmissions can significantly reduce the overall topology cost as compared to conventional unicast-oriented design and the Steiner-tree-based design.     

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.     

IMMIGRANTS-ENHANCED MULTI-POPULATION GENETIC ALGORITHMS FOR DYNAMIC SHORTEST PATH ROUTING PROBLEMS IN MOBILE AD HOC NETWORKS

One of the most important characteristics in mobile wireless networks is the topology dynamics, that is, the network topology changes over time as a result of energy conservation or node mobility. Therefore, the shortest path (SP) routing problem turns out to be a dynamic optimization problem in mobile wireless networks. In this article, we propose to use multi-population genetic algorithms (GAs) with an immigrants scheme to solve the dynamic SP routing problem in mobile ad hoc networks, which are the representative of new generation wireless networks. Two types of multi-population GAs are investigated. One is the forking GA in which a parent population continuously searches for a new optimum and a number of child populations try to exploit previously detected promising areas. The other is the shifting-balance GA in which a core population is used to exploit the best solution found and a number of colony populations are responsible for exploring different areas in the solution space. Both multi-population GAs are enhanced by an immigrants scheme to handle the dynamic environments. In the construction of the dynamic network environments, two models are proposed and investigated. One is called the general dynamics model, in which the topologies are changed because the nodes are scheduled to sleep or wake up. The other is called the worst dynamics model, in which the topologies are altered because some links on the current best shortest path are removed. Extensive experiments are conducted based on these two models. The experimental results show that the proposed multi-population GAs with immigrants enhancement can quickly adapt to the environmental changes (i.e., the network topology changes) and produce high-quality solutions after each change.     

On the nominal capacity of multi-radio multi-channel wireless mesh networks

Wireless mesh networking is an emerging technology with a wide range of applications, from community to metropolitan area networking. Mesh networks consist of wireless routers and access points that make up the network backbone which is connected to the wired infrastructure. Client devices are located at the edge. The capacity of a wireless mesh network is an important performance indicator as well as design parameter. It depends on various factors such as network size and topology, expected traffic patterns, number of interfaces per node, number of channels, routing and channel assignment etc. In this paper, we present an analytical framework for estimating the capacity of wireless mesh networks, based on the concept of collision domains. The capacity of grid-oriented mesh networks is investigated for various scenarios to study the impact of different network parameters.