Rearrangeable multihop lightwave networks: congestion minimization on regular topologies

We address the design of rearrangeable multihop lightwave networks having regular connectivity topology (such as Perfect Shuffle (PS), de Bruijn (dB) graph, GEneralized shuffleexchange Multihop NETwork (GEMNET) and Manhattan Street Network (MSN)). We propose a new formulation of the combined station assignment/flow routing problem with the congestion minimization objective. The formulation is applicable to any regular topology. We then develop a heuristic solution strategy based on tabu search. Given our objective, we want to assess the merit of a regular versus an arbitrary topology, as well as compare different regular topologies across several data instances. In terms of achieving small congestion (as obtained heuristically), the results suggest that with increased problem sizes, regular topologies become more attractive. In such cases the benefit of having less restricted arbitrary network topology might not be fully utilized. Equivalently, having regular topology for larger instances will still provide a large enough search space to (heuristically) obtain good throughput (i.e., small congestion). Moreover, such design will implicitly offer benefits associated with management and operations of regular topologies.     

一种计算缩减级型广义洗牌网络平均跳距的算法

简单介绍了广义洗牌网络（ＧＳＮ）的结构和分类,着重分析缩减级型ＧＳＮ的平均跳距性能,并提出一种计算平均跳距的算法     

Channel sharing in multi-hop WDM lightwave networks: realizationand performance of multicast traffic

A local lightwave network can be constructed by employing two-way fibers to connect nodes in a passive-star physical topology, and the available optical bandwidth may be effectively accessed by the nodal transmitters and receivers at electronic rates using wavelength division multiplexing (WDM). The number of channels, ω, in a WDM network is limited by technology and is usually less than the number of nodes, N, in the network. We provide a general method using channel sharing to construct practical multi-hop networks under this limitation. Channel sharing may be achieved through time division multiplexing. The method is applied to a generalized shuffle-exchange-based multi-hop architecture, called GEMNET. Multicasting-the ability to transmit information from a single source node to multiple destination nodes-is becoming an important requirement in high-performance networks. Multicasting, if improperly implemented, can be bandwidth-abusive. Channel sharing is one approach toward efficient management of multicast traffic. We develop a general modeling procedure for the analysis of multicast (point-to-multipoint) traffic in shared-channel, multihop WDM networks. The analysis is comprehensive in that it considers all components of delay that packets in the network experience-namely, synchronization, queuing, transmission, and propagation. The results show that, in the presence of multicast traffic, WDM networks with ω相似文献   

基于图论的无线传感器网络并行禁忌搜索信道分配方法

Wireless sensor networks are suffering from serious frequency interference. In this paper, we propose a channel assignment algorithm based on graph theory in wireless sensor networks. We first model the conflict infection graph for channel assignment with the goal of global optimization minimizing the total interferences in wireless sensor networks. The channel assignment problem is equivalent to the generalized graph coloring problem which is a NP complete problem. We further present a meta heuristic Wireless Sensor Network Parallel Tabu Search (WSN PTS) algorithm, which can optimize global networks with small numbers of iterations. The results from a simulation experiment reveal that the novel algorithm can effectively solve the channel assignment problem.     

Analysing social behaviour and message dissemination in human based delay tolerant network

Recent advances in mobile communication shows proliferation in networks formed by human carried devices known as the pocket switched network (PSN). Human beings are social animals. They tend to form groups and communities, and have repetitive mobility pattern which can be used to disseminate information in PSNs. In this paper, we give a deeper insight to the nature of community formation and how such information can be used to help opportunistic forwarding in mobile opportunistic networks. Using real world mobility traces, we first derive the adjacency list for each node and form the contact graph. Using tools from social network analysis we then determine various node properties like centrality and clustering coefficient and graph properties like average path length and modularity. Based on the derived graph properties, node encounter process and nature of message dissemination in PSNs, we propose two social based routing, known as the contact based routing and community aware two-hop routing. We compare the proposed routing techniques with generic epidemic and prophet routing and Bubble-Rap, a social based routing. Results show that the proposed algorithms is able to achieve better delivery ratio and lower delay than Bubble Rap, while reducing the high overhead ratio of epidemic and prophet routing.     

Separability and topology control of quasi unit disk graphs

A deep understanding of the structural properties of wireless networks is critical for evaluating the performance of network protocols and improving their designs. Many protocols for wireless networks—routing, topology control, information storage/retrieval and numerous other applications—have been based on the idealized unit-disk graph (UDG) network model. The significant deviation of the UDG model from many real wireless networks is substantially limiting the applicability of such protocols. A more general network model, the quasi unit-disk graph (quasi-UDG) model, captures much better the characteristics of wireless networks. However, the understanding of the properties of general quasi-UDGs has been very limited, which is impeding the designs of key network protocols and algorithms. In this paper, we present results on two important properties of quasi-UDGs: separability and the existence of power efficient spanners. Network separability is a fundamental property leading to efficient network algorithms and fast parallel computation. We prove that every quasi-UDG has a corresponding grid graph with small balanced separators that captures its connectivity properties. We also study the problem of constructing an energy-efficient backbone for a quasi-UDG. We present a distributed local algorithm that, given a quasi-UDG, constructs a nearly planar backbone with a constant stretch factor and a bounded degree. We demonstrate the excellent performance of these auxiliary graphs through simulations and show their applications in efficient routing.     

Lightwave networks based on de Bruijn graphs

Proposes de Bruijn graphs as logical topologies for multihop lightwave networks. After deriving bounds on the throughput and delay performance of any logical topology, the authors compute the throughput and delay performance of de Bruijn graphs for two different routing schemes and compare it with their bounds and the performance of shufflenets. For a given maximum nodal in- and out-degree and average number of hops between stations, a logical topology based on a de Bruijn graph can support a larger number of stations than a shufflenet and this number is close to the maximum that can be supported by any topology. The authors also propose de Bruijn graphs as good physical topologies for wavelength routing lightwave networks consisting of all-optical routing nodes interconnected by point-to-point fiber links. The worst-case loss experienced by a transmission is proportional to the maximum number of hops (diameter). For a given maximum nodal in- and out-degree and diameter, a physical topology based on a de Bruijn graph can support a large number of stations using a relatively small number of wavelengths     

Mapping a class of neural networks on k-ary n-cubes

In this paper we propose a scheme for mapping two important artificial neural network (ANN) models on the popular k-ary n-cube parallel architectures (KNCs). The scheme is based on generalizing the mapping of a bipartite graph onto the KNC architecture and thus can be adapted to any model whose computations can be represented by a bipartite task graph. Our approach is the first to adjust the granularity of parallelism so as to achieve the best possible performance based on properties of the computational model and the target architecture. We first introduce a methodology for optimal implementation of multi-layer feedforward artificial neural networks (FFANNs) trained with the backpropagation algorithm on KNCs. We prove that our mapping methodology is time-optimal and that it provides for maximum processor utilization regardless of the structure of the FFANN. We show that the same methodology can be utilized for efficient mapping of Radial Basis Function neural networks (RBFs) on KNCs. This revised version was published online in June 2006 with corrections to the Cover Date.     

Geometric spanners for routing in mobile networks

We propose a new routing graph, the restricted Delaunay graph (RDG), for mobile ad hoc networks. Combined with a node clustering algorithm, the RDG can be used as an underlying graph for geographic routing protocols. This graph has the following attractive properties: 1) it is planar; 2) between any two graph nodes there exists a path whose length, whether measured in terms of topological or Euclidean distance, is only a constant times the minimum length possible; and 3) the graph can be maintained efficiently in a distributed manner when the nodes move around. Furthermore, each node only needs constant time to make routing decisions. We show by simulation that the RDG outperforms previously proposed routing graphs in the context of the Greedy perimeter stateless routing (GPSR) protocol. Finally, we investigate theoretical bounds on the quality of paths discovered using GPSR.     

The forwarding index of communication networks

A network is defined as an undirected graph and a routing which consists of a collection of simple paths connecting every pair of vertices in the graph. The forwarding index of a network is the maximum number of paths passing through any vertex in the graph. Thus it corresponds to the maximum amount of forwarding done by any node in a communication network with a fixed routing. For a given number of vertices, each having a given degree constraint, we consider the problem of finding networks that minimize the forwarding index. Forwarding indexes are calculated' for cube networks and generalized de Bruijn networks. General bounds are derived which show that de Bruijn networks are asymptotically optimal. Finally, efficient techniques for building large networks with small forwarding indexes out of given component networks are presented and analyzed.     

Maximum flow and network capacity of network coding for ad-hoc networks

Network coding is an effective way to achieve the maximum flow of multicast networks. In this letter, we focus on the statistical properties of the maximum flow or the capacity of network coding for ad-hoc networks based on random graph models. Theoretical analysis shows that the maximum flow can be modelled as extreme order statistics of Gaussian distribution for both wired and wireless ad-hoc networks as the node number is relatively large under a certain condition. We also investigate the effects of the nodes' covering capabilities on the capacity of network coding.     

Fault‐tolerant spanners for ad hoc networks

Spanners for ad hoc networks provide several benefits such as low communication cost and resource consumption. These spanners need to be fault tolerant in resource‐constrained ad hoc networks. In this paper, we have proposed three spanners, called fault‐tolerant local Delaunay triangulation (FTLDel), fault‐tolerant relative neighborhood graph (FTRNG), and fault‐tolerant Gabriel graph (FTGG). The fault‐tolerant spanners provide reliability to the network by avoiding heavy packet loss and retaining useful geometric properties. The performance of fault‐tolerant spanners FTLDel, FTRNG, and FTGG are evaluated using the network simulator ns2.28. Copyright © 2011 John Wiley & Sons, Ltd.     

Reliability polynomials and link importance in networks

The reliability polynomial is a graph invariant which is of interest where graphs are used as models of systems such as communication networks, computer networks, and transportation networks. This paper examines the use of reliability polynomials to rank the edges in a graph in terms of overall importance to graph reliability. For a given edge e in the graph G, G-e and G*e denote the graph with the link deleted and contracted (respectively); p (0相似文献   

Product Multicommodity Flow in Wireless Networks

We provide a tight approximate characterization of the n-dimensional product multicommodity flow (PMF) region for a wireless network of n nodes. Separate characterizations in terms of the spectral properties of appropriate network graphs are obtained in both an information-theoretic sense and for a combinatorial interference model (e.g., protocol model). These provide an inner approximation to the n ²-dimensional capacity region. Our results hold for general node distributions, traffic models, and channel fading models. We first establish that the random source-destination model assumed in many previous results on capacity scaling laws, is essentially a one-dimensional approximation to the capacity region and a special case of PMF. We then build on the results for a wireline network (graph) that relate PMF to its spectral (or cut) properties. Specifically, for a combinatorial interference model given by a network graph and a conflict graph, we relate the PMF to the spectral properties of the underlying graphs resulting in simple computational upper and lower bounds. These results show that the 1/radicn scaling law obtained by Gupta and Kumar for a geometric random network can be explained in terms of the scaling law of the conductance of a geometric random graph. For the more interesting random fading model with additive white Gaussian noise (AWGN), we show that the scaling laws for PMF can again be tightly characterized by the spectral properties of appropriately defined graphs-such a characterization for general wireless networks has not been available before. As an implication, we obtain computationally efficient upper and lower bounds on the PMF for any wireless network with a guaranteed approximation factor.     

Simplified Analysis of Coupled Transmission-Line Networks

A relatively simple method is presented for analyzing coupled transmission-line networks by using network graphs and graph transformations. The network graph symbolism is easy to draw and to manipulate. All the graphs consist only of inductor, capacitor, and transformer symbols, and straight lines, which represent unit elements. The method of analysis is illustrated by several two-wire-line and multiwire-line examples. Also presented are several new useful transmission-line transformations and a graph equivalent for the general coupled transmission-line network. The graph-transformation method has four principal advantages: 1) explicit open-wire-line equivalent circuits of coupled line networks can be obtained relatively easily and without knowledge of network synthesis techniques; 2) the form of equivalent circuits can often be obtained without using any algebra; 3) at each step of the analysis, a positive-real network in graph form is available; consequently, in many analysis problems several equivalent circuits for the same network are derived; and 4) multiport networks are as easily dealt with as two-port networks.     

A new architecture and a new metric for lightwave networks

The notion of a logically routed network was developed to overcome the bottlenecks encountered during the design of a large purely optical network. In the last few years, researchers have proposed the use of torus. Perfect shuffle, hypercube, de Bruijn graph, Kautz graph, and Cayley graph as an overlay structure on top of a purely optical network. All these networks have regular structures. Although regular structures have many virtues, it is often difficult in a realistic setting to meet these stringent structural requirements. In this paper, we propose generalized multimesh (GM), a semiregular structure, as an alternate to the proposed architectures. In terms of simplicity of interconnection and routing, this architecture is comparable to the torus network. However, the new architecture exhibits significantly superior topological properties to the torus. For example, whereas a two-dimensional (2-D) torus with N nodes has a diameter of Θ(N^0.5), a generalized multimesh network with the same number of nodes and links has a diameter of Θ(N^0.25). In this paper, we also introduce a new metric, flow number, that can be used to evaluate topologies for optical networks. For optical networks, a topology with a smaller flow number is preferable, as it is an indicator of the number of wavelengths necessary for full connectivity. We show that the flow numbers of a 2-D torus, a multimesh, and a de Bruijn network, are Θ(N^1.5), Θ(N^1.25), and Θ(N log N), respectively, where N is the number of nodes in the network. The advantage of the generalized multimesh over the de Bruijn network lies in the bet that, unlike the de Bruijn network, this network can be constructed for any number of nodes and is incrementally expandable     

Graph-theoretic analysis of structured peer-to-peer systems: routing distances and fault resilience

This paper examines graph-theoretic properties of existing peer-to-peer networks and proposes a new infrastructure based on optimal-diameter de Bruijn graphs. Since generalized de Bruijn graphs exhibit very short average distances and high resilience to node failure, they are well suited for distributed hash tables (DHTs). Using the example of Chord, CAN, and de Bruijn, we study the routing performance, graph expansion, clustering properties, and bisection width of each graph. Having confirmed that de Bruijn graphs offer the best diameter and highest connectivity among the existing peer-to-peer structures, we offer a very simple incremental building process that preserves optimal properties of de Bruijn graphs under uniform user joins/departures. We call the combined peer-to-peer architecture optimal diameter routing infrastructure.     

Maximizing the Mean Number of Communicating Vertex Pairs in Series-Parallel Networks

A communication network can be modelled as a probabilistic graph where each of b edges represents a communication line and each of n vertices represents a communication processor. Each edge e (vertex v) functions with probability Pe (pv). If edges fail independently with uniform probability p and vertices do not fail, the probability that the network is connected is the probabilistic connectedness and is a standard measure of network reliability. The most reliable maximal series-parallel networks by this measure are those with exactly two vertices of degree two. However, as p becomes small, or n becomes large, the probability that even the most reliable series-parallel network is connected falls very quickly. Therefore, we wish to optimize a network with respect to another reliability measure, mean number of communicating vertex pairs. Experimental results suggest that this measure varies with p, with the diameter of the network, and with the number of minimum edge cutsets. We show that for large p, the most reliable series-parallel network must have the fewest minimum edge cutsets and for small p, the most reliable network must have maximum pairs of adjacent edges. We present a construction which incrementally inproves the communicating vertex pair mean for many networks and demonstrates that a fan maximizes this measure over maximal series parallel networks with exactly two edge cutsets of size two.     

Optimum Integrated Link Scheduling and Power Control for Multihop Wireless Networks

In this paper, a new mathematical programming formulation is developed for minimizing the schedule length in multihop wireless networks based on the optimal joint scheduling of transmissions across multi-access communication links and the allocation of transmit power levels while meeting the requirements on the signal-to-interference-plus-noise ratio at intended receivers. The authors prove that the problem can be represented as a mixed-integer linear programming (MILP) and show that the latter yields a solution that consists of transmit power levels that are "strongly Pareto optimal". It was demonstrated that the MILP formulation can be used effectively to derive optimal scheduling and power levels for networks with as many as 30 designated communication links. The authors show that the MILP formulation can also be effectively solved to provide upper and lower bounds (corresponding to an approximation factor Delta) for the optimum schedule length of networks with as many as 100 designated links. It is proved that the integrated link scheduling and power control problem (ILSP) is NP-complete. Consequently, a heuristic algorithm of polynomial complexity is developed and investigated for solving the problem in a timely and practical manner. The algorithm is based on the properties of a novel interference graph, i.e., the "generalized power-based interference graph", whose "chromatic" and "independence numbers" provide fundamental bounds for the ILSP. It is demonstrated that the frame length of schedules realized by the heuristic scheme resides in the 25th percentile of those attained by the optimal mechanism for randomly generated topologies with as many as 30 designated communication links. Furthermore, it is shown that the algorithm significantly outperforms a corresponding algorithm presented in the literature     

Bitcoin's dynamic peer‐to‐peer topology

Topology discovery is a prerequisite when investigating the network properties; with the enormous number of Bitcoin users and performance issues, it becomes critical to analyse the network in a fashion that makes it possible to detect all Bitcoin's nodes and understand their behaviour. In massive, dynamic, and distributed peer‐to‐peer (P2P) networks like Bitcoin, where thousands of updates occur per second, it is hard to obtain an accurate topology representing the structure of the network as a graph with nodes and links by using the traditional local measurement approaches based on batches, offline data, or on the discovery of the topology around a small set of nodes and then combine them to discover an approximate network topology. All of which present some limitation when applying them on blockchain‐based networks. In this paper, we propose a topology discovery system that performs a real‐time data collection and analysis for Bitcoin P2P links, which assembles incoming nodes information for deeper graph analysis processing. The topology discovery system allows us to gain knowledge on the Bitcoin network size, the network stability in terms of reachable, churn, and well‐connected nodes, as well as some data regarding the effects of some countries' Internet infrastructure on Bitcoin traffic.