Multicast protection algorithms based on aggregated logical topology in survivable multi-domain optical networks

Since the optical network carries a lot of traffic, the survivability is an important issue to ensure the service continuity. At the same time, with the network scale increasing, the optical network has been divided into multi-domains each of which is managed by a unique network provider. Therefore, the survivability in multi-domain optical networks has got more attention in recent years. However, current works mostly addressed the unicast survivability and few or no solved the multicast survivability in multi-domain optical networks. Therefore, in this paper we propose two heuristic algorithms called Multicast Multi-domain Dedicated Protection (MMDP) and Multicast Multi-domain Shared Protection (MMSP) to provide the survivability in multicast multi-domain optical networks. In MMDP and MMSP, to provide the intra-domain protection, we use the modified Minimal-cost Path Heuristic (MPH) algorithm to compute the intra-domain survivable multicast tree. To provide the inter-domain protection, based on multi-domain logical topology, we firstly use the MPH algorithm to compute the inter-domain logical multicast tree and then use the Dijkstra algorithm to compute the inter-domain logical backup sub-path for each inter-link on this logical multicast tree. Simulation results show that MMSP has better resource utilization efficiency and lower blocking probability.     

A method of segment protection based on p-cycle for dynamic multicast with limited-range wavelength converter in WDM network

In the optical multicast network, node and link failures have very important influence on the network survivability which may lead to multiple destinations cannot receive data. Based on the wavelength layered-graph method, a method of efficiency-score based on heuristic algorithm of pre-configured cycle (p-Cycle) based-segment protection (ESHS) for dynamic multicast with limited-range wavelength conversion was presented in this paper. By finding the multicast tree segment protection, the total available p-Cycles are constructed for the multicast. Then we calculate each p-Cycle efficiency-score, the highest efficient-score p-Cycle is selected as the multicast route protection p-Cycle. The simulation results show that the ESHS can get higher performance than the existing ESHT algorithm, in terms of multicast request blocking probability and wavelength utilization.     

Survivable routing and spectrum allocation algorithm based on p-cycle protection in elastic optical networks

With the number of large capacity applications in core network increasing, the bandwidth requirement of optical connections in conventional Wavelength Division Multiplexing (WDM) networks keeps enhancing, so that the Orthogonal Frequency Division Multiplexing (OFDM) technology is adopted to provide higher spectrum efficiency and flexibility in the future elastic optical networks. Meanwhile, survivability in the conventional WDM optical networks has been widely studied as an important issue to ensure the service continuity. However, survivability in OFDM-based elastic optical networks is more challenging than that in conventional WDM optical networks because each fiber usually carries even more connections. Therefore, it is necessary to study the new lightpath protection algorithm in elastic optical networks. Since p-cycle protection scheme has short restoration time and simple protection switching procedure, in this paper, we study the static Survivable p-Cycle Routing and Spectrum Allocation (SC-RSA) problem with providing an Integer Linear Programming (ILP) formulation. Since RSA is a NP-hard problem, we propose a new heuristic algorithm called Elastic p-Cycle Protection (ECP) to tolerate the single-fiber link failure. For each demand, ECP scheme can compute highly-efficient p-cycles to provide protection for all of the on-cycle links and the straddling links. We also consider the load balancing and choose the proper working path for each demand. Simulation results show that the proposed ECP scheme achieves better performances than traditional single-line-rate survivable schemes.     

基于组播树的多粒度波带静态疏导算法

研究了波带交换中的静态业务疏导算法。波带交换可以有效地减少波长交换的端口数量,但是当波带粒度值取固定值时,波带的粒度难以取得合适值。波带的粒度大,有助于减少交换端口的数量,但是波带利用率低;波带粒度小,有助于提高波带利用率,但是交换端口的数量多。为此,提出了多粒度的波带取值方法。根据静态业务疏导与组播路由的相似性,提出了利用构造组播树解决静态疏导问题的方法。另外,为了减少波带与波长交换平面互联的端口数量,采用了同目的地的波带疏导策略,并针对这一疏导策略提出了一种新的波带疏导辅助图。仿真结果表明,相对于固定粒度的波带取值,可以有效地减少交换端口的数量,并提高波带利用率。     

智能光网络组播梳理协议设计与分析

为了节约网络成本和提高网络性能,将RSVP协议和OSPF协议进行扩展,提出了一个支持业务梳理的智能光网络组播协议,给出了消息类型,信令流程及状态机模型,并通过仿真验证协议性能.仿真表明,业务梳理可以一定程度降低组播业务阻塞率,但业务建立时延却大于不存在梳理的情况.梳理的存在使业务建立时延随着业务量的增大有一个由小变大再减小的过程.     

A new multi-granularity traffic grooming routing algorithm in IP over WDM networks

In IP over WDM networks, since there is a large bandwidth gap between a wavelength capacity and the actual bandwidth required by each user, it is necessary to multiplex low-rate traffic streams (LRSs) into lightpaths by traffic grooming. However, with the number of wavelengths increases, a large number of all optical (OOO) transmitting ports are consumed. Meanwhile, the multi-hop grooming with incorporating full-wavelength conversion capacity in each node requires too many optical-electrical-optical (OEO) ports inevitably. To solve theses problems, waveband switching and intra-band wavelength conversion are proposed. By integrating traffic grooming and waveband switching, this paper devises a new multi-granularity traffic grooming mechanism with the function of intra-band wavelength conversion. Based on the proposed mechanism and integrated grooming policy (IGP), a new heuristic routing algorithm called multi-granularity traffic grooming based on integrated auxiliary graph (MGIAG) is also proposed since the traffic grooming problem is NP-hard. Simulation results show that, compared to traditional integrated grooming algorithm (IGA), MGIAG can save more ports and obtain lower blocking probability. Compared to traditional single-hop traffic grooming algorithm (SHA), lower blocking probability and more savings in transmitting ports can be achieved by multi-hop grooming in MGIAG and IGA although they consume more OEO ports.     

Dynamic waveband grooming based on hierarchical integrated grooming auxiliary graph in multi-domain mesh optical networks

With the number of wavelengths in fibers increasing, the number of optical switching ports in conventional Optical Cross-Connect (OXC) keeps enhancing, so that waveband grooming technique is proposed to save the switching ports in OXC. Most of previous works focused on waveband grooming in single-domain optical network. Since the current optical backbone is actually divided to multiple domains according to the different network providers, it is necessary to study the waveband grooming in multi-domain optical networks. However, waveband grooming in multi-domain optical networks is more challenging than that in single domain networks because of the routing scalability and security issues. Therefore, in this paper, we propose a new heuristic Hierarchical Multi-domain Waveband Grooming (HMWG) algorithm based on Hierarchical Integrated Grooming Auxiliary Graph (H-IGAG) to reduce the total number of optical switching ports. The H-IGAG is compared of the Intra-domain Waveband Integrated Auxiliary Graph (Intra-WIAG) and the Inter-domain waveband Virtual Topology Graph (Inter-VTG). For the demand in single-domain, HMWG directly computes the route from the source node to destination node in the single-domain with waveband grooming on Intra-WIAG. For the demand spanning different domains, HMWG first computes the route from the source node to the selected border node in source domain and computes the route from the selected border node to the destination node in destination domain with waveband grooming on Intra-WIAG, respectively. Then, HMWG computes the route from the selected border node in source domain to the selected border node in destination domain with waveband grooming on Inter-VTG. Simulation results show that, compared with previous grooming algorithm, HMWG can obtain better performance.     

Analysis of Connection Availability in an All-Optical Mesh Network

This paper presents the method of an availability performance analysis that can be used for all-optical networks. We compare different schemes of protection and restoration in a fully connected mesh network based on optical cross-connects, optical fibers, and fiber amplifiers. Specifically treated is an optical mesh network physically mapped onto a Scandinavian backbone. In order to compare different survivability strategies, we selected two nodes located roughly 420 km apart. The goal of this work is to point out possible ways to improve connection availability. A number of survivability schemes are compared, for which the availability model of logical connection is derived and a calculation procedure is described. Our results show that unprotected schemes cannot ascertain reasonably high requirements on connection availability in the backbone network. Thus, if a redundant structure of logical connection is considered, the particular survivability scheme should be evaluated in order to maximize connection availability.     

WDM光网络安全生存机制研究

针对WDM光网络安全生存性问题的故障的发现、定位和恢复三个重要环节之中的恢复问题,提出了一种WDM光层中的安全保护与恢复方案。采用了恢复路由选择算法和恢复波长分配算法,提出了一种混合的多层恢复机制,从而构建了一种从故障的发现、定位到故障恢复的覆盖各环节的连续性光网络安全生存机制,并在理论上进行了性能比较。     

Quantum multicast communication over the butterfly network

We propose a scheme where one can exploit auxiliary resources to achieve quantum multicast communication with network coding over the butterfly network.In this paper,we propose the quantum 2-pair multicast communication scheme,and extend it to k-pair multicast communication over the extended butterfly network.Firstly,an EPR pair is shared between each adjacent node on the butterfly network,and make use of local operation and classical communication to generate entangled relationship between non-adjacent nodes.Secondly,each sender adds auxiliary particles according to the multicast number k,in which the CNOT operations are applied to form the multi-particle entangled state.Finally,combined with network coding and free classical communication,quantum multicast communication based on quantum measurements is completed over the extended butterfly network.Not only the bottleneck problem is solved,but also quantum multicast communication can be completed in our scheme.At the same time,regardless of multicast number k,the maximum capacity of classical channel is 2 bits,and quantum channel is used only once.     

Performance analysis of traffic groomed optical network

In this paper we carry out the performance analysis of traffic groomed multilayer optical networks. It is seen that the number of wavelength channels required decreases as the wavelength grooming factor increases. We have evaluated blocking probability for different load and grooming factor. The performance of the network has been evaluated for different conditions; first for fixed number of links with grooming factor set to 3 and subsequently with increase in grooming factor up to 18 in steps. The load on each link is selected as 2, 5, 9, 12, 15 and 20 Erlangs and the blocking probability as function of number of optical channels has been evaluated. In this work the effect of number of wavelength channels, traffic load and grooming factor on network blocking probability has been studied. The investigation reveals that the blocking probability decreases with increase in wavelength channels. Similarly we found that the blocking probability increases with increase in traffic load which is quite evident. Further it is shown that when the grooming factor is increased to significant value (16), the number of wavelengths requirement (8) becomes relatively stable.     

IP/GMPLS/Optical多层网络生存性机制的协调

通过对多层网络生存性问题、独立的网络生存性配置方案和多层网络生存性配置方案的研究分析,基于快速发展的GMPLS技术提出了IP/GMPLS/Optical多层网络结构,明确了多层网络生存性方案存在的问题,并利用GMPLS的统一控制平面进一步提出了基于层间协调机制的集成多层网络生存性方案,获得了优化的多层网络故障恢复能力.     

Ricci Curvature-Based Semi-Supervised Learning on an Attributed Network

In recent years, on the basis of drawing lessons from traditional neural network models, people have been paying more and more attention to the design of neural network architectures for processing graph structure data, which are called graph neural networks (GNN). GCN, namely, graph convolution networks, are neural network models in GNN. GCN extends the convolution operation from traditional data (such as images) to graph data, and it is essentially a feature extractor, which aggregates the features of neighborhood nodes into those of target nodes. In the process of aggregating features, GCN uses the Laplacian matrix to assign different importance to the nodes in the neighborhood of the target nodes. Since graph-structured data are inherently non-Euclidean, we seek to use a non-Euclidean mathematical tool, namely, Riemannian geometry, to analyze graphs (networks). In this paper, we present a novel model for semi-supervised learning called the Ricci curvature-based graph convolutional neural network, i.e., RCGCN. The aggregation pattern of RCGCN is inspired by that of GCN. We regard the network as a discrete manifold, and then use Ricci curvature to assign different importance to the nodes within the neighborhood of the target nodes. Ricci curvature is related to the optimal transport distance, which can well reflect the geometric structure of the underlying space of the network. The node importance given by Ricci curvature can better reflect the relationships between the target node and the nodes in the neighborhood. The proposed model scales linearly with the number of edges in the network. Experiments demonstrated that RCGCN achieves a significant performance gain over baseline methods on benchmark datasets.     

Survivable WDM-PON with self-protection and in-service fault localization capabilities

In this paper, we analyze the survivability of wavelength division multiplexed (WDM) passive optical network (PON). We propose and experimentally demonstrate a novel survivable WDM-PON architecture with self-protection and in-service fault localization capabilities. Two WDM-PONs are combined together and multiple sub-ring architecture is formed. Protection switching is achieved automatically at optical network units (ONUs) when failure occurs. Fiber loss, fiber fault localization and automatic protection switching in each ONU are real-time monitored in central office (CO) without interrupting customer service. No signaling for failure notice or protection switching is required for either CO or ONUs. Extra fibers required for protection are minimized compared with previous protection schemes. The self-protection and in-service fault localization capabilities of the proposed WDM-PON architecture are experimentally verified.     

An optical multicast packet switching architecture shared with limited-range multi-wavelength converter and full-range wavelength converters

Optical packet switch with multicast capability can inspire a broad range of multipoint to multipoint applications in future optical networks. An optical multicast packet switching architecture, equipped with feedback shared small number of limited-range multi-wavelength converters (LMWCs) and output shared some full-range wavelength converters (FRWCs), is proposed for a wavelength-division multiplexed optical multicast network to improve multicast performance in the paper. The FRWCs are used to overcome the performance degradation in terms of packet loss probability due to only use LMWCs. In the architecture, the two converters are shared by all the multicast packets importing to the optical multicast switch node. A maximum bipartite matching with minimum edges weights strategy was designed to employ fewer wavelength converters and avoid useless degradation of optical signal quality for the architecture to improve the node performance. The simulation results show that the proposed architecture and its wavelength converter scheduling algorithm can reduce the multicast packet loss probability with relatively lesser wavelength conversion cost.     

Components in time-varying graphs

Real complex systems are inherently time-varying. Thanks to new communication systems and novel technologies, today it is possible to produce and analyze social and biological networks with detailed information on the time of occurrence and duration of each link. However, standard graph metrics introduced so far in complex network theory are mainly suited for static graphs, i.e., graphs in which the links do not change over time, or graphs built from time-varying systems by aggregating all the links as if they were concurrent in time. In this paper, we extend the notion of connectedness, and the definitions of node and graph components, to the case of time-varying graphs, which are represented as time-ordered sequences of graphs defined over a fixed set of nodes. We show that the problem of finding strongly connected components in a time-varying graph can be mapped into the problem of discovering the maximal-cliques in an opportunely constructed static graph, which we name the affine graph. It is, therefore, an NP-complete problem. As a practical example, we have performed a temporal component analysis of time-varying graphs constructed from three data sets of human interactions. The results show that taking time into account in the definition of graph components allows to capture important features of real systems. In particular, we observe a large variability in the size of node temporal in- and out-components. This is due to intrinsic fluctuations in the activity patterns of individuals, which cannot be detected by static graph analysis.     

Enhancing network lifespan in wireless sensor networks using deep learning based Graph Neural Network

Inadequate energy of sensors is one of the most significant challenges in the development of a reliable wireless sensor network (WSN) that can withstand the demands of growing WSN applications. Implementing a sleep-wake scheduling scheme while assigning data collection and sensing chores to a dominant group of awake sensors while all other nodes are in a sleep state seems to be a potential way for preserving the energy of these sensor nodes. When the starting energy of the nodes changes from one node to another, this issue becomes more difficult to solve. The notion of a dominant set-in graph has been used in a variety of situations. The search for the smallest dominant set in a big graph might be time-consuming. Specifically, we address two issues: first, identifying the smallest possible dominant set, and second, extending the network lifespan by saving the energy of the sensors. To overcome the first problem, we design and develop a deep learning-based Graph Neural Network (DL-GNN). The GNN training method and back-propagation approach were used to train a GNN consisting of three networks such as transition network, bias network, and output network, to determine the minimal dominant set in the created graph. As a second step, we proposed a hybrid fixed-variant search (HFVS) method that considers minimal dominant sets as input and improves overall network lifespan by swapping nodes of minimal dominating sets. We prepared simulated networks with various network configurations and modeled different WSNs as undirected graphs. To get better convergence, the different values of state vector dimensions of the input vectors are investigated. When the state vector dimension is 3 or 4, minimum dominant set is recognized with high accuracy. The paper also presents comparative analyses between the proposed HFVS algorithm and other existing algorithms for extending network lifespan and discusses the trade-offs that exist between them. Lifespan of wireless sensor network, which is based on the dominant set method, is greatly increased by the techniques we have proposed.     

On the ground state of quantum graphs with attractive δ-coupling

We study relations between the ground-state energy of a quantum graph Hamiltonian with attractive δ coupling at the vertices and the graph geometry. We derive a necessary and sufficient condition under which the energy increases with the increase of graph edge lengths. We show that this is always the case if the graph has no branchings while both energy increase and decrease are possible for graphs with a more complicated topology.     

The role of nonlinearity in computing graph-theoretical properties of resting-state functional magnetic resonance imaging brain networks

In recent years, there has been an increasing interest in the study of large-scale brain activity interaction structure from the perspective of complex networks, based on functional magnetic resonance imaging (fMRI) measurements. To assess the strength of interaction (functional connectivity, FC) between two brain regions, the linear (Pearson) correlation coefficient of the respective time series is most commonly used. Since a potential use of nonlinear FC measures has recently been discussed in this and other fields, the question arises whether particular nonlinear FC measures would be more informative for the graph analysis than linear ones. We present a comparison of network analysis results obtained from the brain connectivity graphs capturing either full (both linear and nonlinear) or only linear connectivity using 24 sessions of human resting-state fMRI. For each session, a matrix of full connectivity between 90 anatomical parcel time series is computed using mutual information. For comparison, connectivity matrices obtained for multivariate linear Gaussian surrogate data that preserve the correlations, but remove any nonlinearity are generated. Binarizing these matrices using multiple thresholds, we generate graphs corresponding to linear and full nonlinear interaction structures. The effect of neglecting nonlinearity is then assessed by comparing the values of a range of graph-theoretical measures evaluated for both types of graphs. Statistical comparisons suggest a potential effect of nonlinearity on the local measures-clustering coefficient and betweenness centrality. Nevertheless, subsequent quantitative comparison shows that the nonlinearity effect is practically negligible when compared to the intersubject variability of the graph measures. Further, on the group-average graph level, the nonlinearity effect is unnoticeable.     

Performance evaluation of survivable WDM based SANs in a metro ring network

Storage area networks (SANs) are an essential part of enterprise computing today. There is no comprehensive business continuity plan without SANs in the picture. This paper proposes and evaluates network survivability of optical paths in wavelength division multiplexing (WDM) based storage area networks in a metro ring network. The paper begins with a background on network survivability in metro WDM ring network. Subsequently, the network and node architectures along with their medium access control (MAC) protocols are described. In this work, one link failure (a single cable cut) in metro WDM based SANs in a ring network architecture is considered. Performance evaluation for network survivability in metro WDM SAN is carried out by means of discrete-event computer simulation. Network throughput and packet delay are investigated. The network performance is evaluated for asymmetric (unbalanced) traffic scenarios under Poisson and self-similar traffic.