Synchronization of Complex Dynamical Networks with Dynamical Behavior Links

In this paper, synchronization of a complex dynamical network (CDN) is investigated while the coupling connections of the network exhibit dynamic behavior. As it is shown in simulations, the dynamic links can cause synchronization losing in the network whereas the links in many real‐world CDNs have dynamic behavior. To analyzing the effect of these links, two different CDN models are considered: without time delays and with delays in the coupling connections. By means of Lyapunov(‐Krasovskii) theory, stability analysis of the error dynamics between the nodes of these CDNs and an introduced individual node is investigated which yields some conditions in the form of linear matrix inequalities (LMIs). These LMIs can be solved easily by various existing LMI solvers. Moreover, the gain matrices of state feedback controllers will be obtained by solving the LMIs. In the end, illustrative numerical examples are given to specify the effectiveness of the proposed method.     

Adding multiple-fault tolerance to generalized cube networks

Generalized cube networks are limited to single-fault tolerance with respect to permutation connections. The vector space approach presented here yields many fault-tolerance schemes that can tolerate two and three faults. In each scheme, redundant switches and links are added to networks and interconnected in certain ways. These redundancies are represented by a matrix called the redundancy matrix. A fault-free network without redundancy is represented by an identity matrix. As faulty switches and links are discovered, the remaining switches and links are remapped to establish an intact network. The remapping is analogous to converting an invertible redundancy matrix back to an identity matrix     

无线网络中的一种基于小世界模型的路由协议

最近,利用节点的移动性提升网络系统性能的方法引起了不少关注。这些方法已经被运用于包括移动Adhoc网络（MANET）、无线传感网络（WSN）和容忍延时网络（DTN）在内的一些新兴网络中,他们都认为节点是随机或者可控移动的。为了达到优化或平衡包括延时、平均中继节点数目和移动距离在内的一些度量参数的目的,本文提出了一种基于于小世界模型的路由协议（SWR）。通过分析,该协议只有多对数数量级的中继节点,大大减少了报文传输过程中中继节点的数量。文中定义了短链接与长链接的概念,其中每一节点与其最邻近的节点之间存在“短”链接,而与其他遵循桌一概率分布的节点间存在着“长”链接。短链接通常是无线链接,而长链接通常是利用移动节点来实现的。本文在网络规模、使用数据搭乘者、多重长链接和等待移动节点时间方面进行了分析。通过仿真结果,我们对各方面性能进行了评估。     

LIAD: Adaptive bandwidth prediction based Logarithmic Increase Adaptive Decrease for TCP congestion control in heterogeneous wireless networks

For accessing plentiful resources in the Internet through wireless mobile hosts, diverse wireless network standards and technologies have been developed and progressed significantly. The most successful examples include IEEE 802.11 WiFi for wireless networks and 3G/HSDPA/HSUPA for cellular communications. All IP-based applications are the primary motivations to make these networks successful. In TCP/IP transmissions, the TCP congestion control operates well in the wired network, but it is difficult to determine an accurate congestion window in a heterogeneous wireless network that consists of the wired Internet and various types of wireless networks. The primary reason is that TCP connections are impacted by not only networks congestion but also error wireless links. This paper thus proposes a novel adaptive window congestion control (namely Logarithmic Increase Adaptive Decrease, LIAD) for TCP connections in heterogeneous wireless networks. The proposed RTT-based LIAD has the capability to increase throughput while achieving competitive fairness among connections with the same TCP congestion mechanism and supporting friendliness among connections with different TCP congestion control mechanisms. In the Congestion Avoidance (CA) phase, an optimal shrink factor is first proposed for Adaptive Decreasing cwnd rather than a static decreasing mechanism used by most approaches. Second, we adopt a Logarithmic Increase algorithm to increase cwnd while receiving each ACK after causing three duplicate ACKs. The analyses of congestion window and throughput under different packet loss rate are analyzed. Furthermore, the state transition diagram of LIAD is detailed. Numerical results demonstrate that the proposed LIAD outperforms other approaches in goodput, fairness, and friendliness under diverse heterogeneous wireless topologies. Especially, in the case of 10% packet loss rate in wireless links, the proposed approach increases goodput up to 156% and 1136% as compared with LogWestwood+ and NewReno, respectively.     

Smith's principle for congestion control in high-speed datanetworks

In high-speed communication networks, large propagation delays could have an adverse impact on the stability of feedback control algorithms. In this paper, the classical control theory and Smith's principle are exploited to design an algorithm for controlling “best effort” traffic in high-speed asynchronous transfer mode (ATM) networks. The designed algorithm guarantees the stability of network queues, along with the fair and full utilization of network links, in a realistic traffic scenario in which multiple available bit rate connections, with different propagation delays, share the network with high priority traffic     

Load-aware routing in mesh networks: Models, algorithms and experimentation

In this paper we consider wireless mesh networks (WMNs) used to share the Internet connectivity of sparsely deployed fixed lines with heterogeneous capacity, ranging from ISP-owned high-speed links to subscriber-owned low-speed connections. If traffic is routed in the mesh without considering the load distribution and the bandwidth of Internet connections, some gateways may rapidly get overloaded because they are selected by too many mesh nodes. This may cause a significant reduction of the overall network capacity. To address this issue, in this paper we first develop a queuing network model that predicts the residual capacity of network paths, and identifies network bottlenecks. By taking advantage of this model, we design a novel Load-Aware Route Selection algorithm, named LARS, which improves the network capacity by allocating network paths to upstream Internet flows so as to ensure a more balanced utilization of wireless network resources and gateways’ Internet connections. Using simulations and a prototype implementation, we show that the LARS scheme significantly outperforms the shortest-path first routing protocol using a contention-aware routing metric, providing up to 240% throughput improvement in some network scenarios.     

SmallWorld Model-Based Polylogarithmic Routing Using Mobile Nodes

The use of mobile nodes to improve network system performance has drawn considerable attention recently. The movement-assisted model considers mobility as a desirable feature,where routing is based on the store-carry-forward paradigm with random or controlled movement of resource rich mobile nodes.The application of such a model has been used in several emerging networks,including mobile ad hoc networks(MANETs),wireless sensor networks(WSNs),and delay tolerant networks(DTNs).It is well known that mobility increases the capacity of MANETs by reducing the number of relays for routing,prolonging the lifespan of WSNs by using mobile nodes in place of bottleneck static sensors,and ensuring network connectivity in DTNs using mobile nodes to connect different parts of a disconnected network.Trajectory planning and the coordination of mobile nodes are two important design issues aiming to optimize or balance several measures, including delay,average number of relays,and moving distance.In this paper,we propose a new controlled mobility model with an expected polylogarithmic number of relays to achieve a good balance among several contradictory goals,including delay,the number of relays,and moving distance.The model is based on the small-world model where each static node has"short"link connections to its nearest neighbors and"long"link connections to other nodes following a certain probability distribution.Short links are regular wireless connections whereas long links are implemented using mobile nodes.Various issues are considered,including trade-offs between delay and average number of relays,selection of the number of mobile nodes,and selection of the number of long links.The effectiveness of the proposed model is evaluated analytically as well as through simulation.     

Preemption With Rerouting to Minimize Service Disruption in Connection-Oriented Networks

Resource allocation is a fundamental problem in connection-oriented networks. A preemption mechanism would provide available and reliable services to new connections with higher priority by tearing down existing connections of lower priority. However, end users of the existing connections that are preempted will suffer service disruptions. The duration spent and the work done for these connections are wasted, leading to lower useful utilization of the overall network resources. Soft preemption can alleviate this by rerouting a connection that is about to be preempted before actually tearing it down so that the interruption of ongoing service can be avoided. In this paper, we focus on minimizing the service disruptions caused as a result of preemption by proposing algorithms that incorporate the soft preemption feature. A centralized algorithm is developed to select the network links that have a high number of reroutable connections in order to minimize service disruptions. For feasible deployment, a decentralized preemption algorithm that uses local information is subsequently proposed. Simulation results indicate that these approaches not only reduce the service disruption but also lead to higher network throughput than what can be achieved by existing preemption algorithms.      

Dynamic routing and spectrum (re)allocation in future flexgrid optical networks

Future flexible-grid elastic optical networks are very promising due to their higher spectrum efficiency and flexibility comparing to the rigid spectrum grid optical networks realized with the traditional wavelength division multiplexing (WDM) technology. The maturity of key system components enabling flexgrid optical networks, such as advanced modulation techniques and multi-granular switching, is already high enough and thus their deployment is expected in the near future. The main feature of such networks is the removal of fix grid-space assignment (in general 50 GHz) to the optical connections independently of the required bandwidth. In fact, the available optical spectrum in flexgrid network is divided into frequency slots of a fixed spectrum width and an optical connection can be allocated into the number of slots that better matches the actual bandwidth of the connection demand. Nonetheless, such allocation must satisfy two constraints, i.e. the slots must be (i) contiguous in the spectrum domain and (ii) continuous along the links on the routing path. These constraints result in a need for dedicated Routing and Spectrum Allocation (RSA) algorithms able to operate under dynamic traffic conditions. From the network design perspective, an important issue is the selection of the frequency slot width which may have an impact on the network performance. Last but not least, network dynamicity entails spectrum fragmentation, which significantly reduces the network performance. In this paper we address these topics and, in particular: (1) we present an RSA algorithm to be used in dynamic network scenarios, (2) we study the optimal slot width as a function of the foreseen traffic to be served, and (3) we propose an algorithm to reallocate already established optical connections so that to make room in the spectrum for the new ones. Exhaustive simulation results reveal that the proposed approach improves the blocking probability performance in flexgrid optical networks.     

A utility-based algorithm for joint uplink/downlink scheduling in wireless cellular networks

The major driver for deploying next generation wireless cellular systems is their ability to efficiently deliver resource-demanding services, many of which require symmetric communication between an uplink mobile user and a downlink mobile user that belong to the same network. In this work, we propose a utility-based joint uplink/downlink scheduling algorithm suitable for wireless services involving pairwise communication among mobile users. While most existing literature focuses on downlink-only or uplink-only scheduling algorithms, the proposed algorithm aims at ensuring a utility function that jointly captures the quality of service in terms of delay and channel quality on both links. By jointly considering the time varying channel conditions in both the uplink and the downlink directions, the proposed algorithm avoids wasting of resources and achieves notable performance gains in terms of increased number of active connections, lower packet drop rate, and increased network throughput. These gains are achieved with a tradeoff cost in terms of complexity and signaling overhead. For overhead reduction in practical scenarios, we propose an implementation over clusters within the network.     

SRNET: A Shallow Skip Connection Based Convolutional Neural Network Design for Resolving Singularities

Convolutional neural networks (CNNs) have shown tremendous progress and performance in recent years. Since emergence, CNNs have exhibited excellent performance in most of classification and segmentation tasks. Currently, the CNN family includes various architectures that dominate major vision-based recognition tasks. However, building a neural network (NN) by simply stacking convolution blocks inevitably limits its optimization ability and introduces overfitting and vanishing gradient problems. One of the key reasons for the aforementioned issues is network singularities, which have lately caused degenerating manifolds in the loss landscape. This situation leads to a slow learning process and lower performance. In this scenario, the skip connections turned out to be an essential unit of the CNN design to mitigate network singularities. The proposed idea of this research is to introduce skip connections in NN architecture to augment the information flow, mitigate singularities and improve performance. This research experimented with different levels of skip connections and proposed the placement strategy of these links for any CNN. To prove the proposed hypothesis, we designed an experimental CNN architecture, named as Shallow Wide ResNet or SRNet, as it uses wide residual network as a base network design. We have performed numerous experiments to assess the validity of the proposed idea. CIFAR-10 and CIFAR-100, two well-known datasets are used for training and testing CNNs. The final empirical results have shown a great many of promising outcomes in terms of performance, efficiency and reduction in network singularities issues.

     

Performance evaluation of TCP connections in ideal and non-ideal network environments

In this paper, we study the performance of TCP in both ideal and non-ideal network environments. For the ideal environments, we develop a simple analytical model for the throughput and transfer time of TCP as a function of the file size and TCP parameters. Our simulation measurements demonstrate that this model can accurately predict the throughput for ideal TCP connections characterized by no packet loss due to congestion or bit errors. If these ideal conditions are not met, the model gives an upper bound for throughput and lower bound for transfer time. For the non-ideal environments, we concentrate on wireless links. While our ideal model provides an easy to use tool to calculate bounds on the performance of all TCP implementations in such environments, we also show through simulation the relative performance of four well-known TCP implementations. We also present simulation results that demonstrate the dominant factors affecting the performance of wireless TCP.     

Link Prediction based on Structural Properties of Online Social Networks

Question-Answering Bulletin Boards (QABB), such as Yahoo! Answers and Windows Live QnA, are gaining popularity recently. Questions are submitted on QABB and let somebody in the internet answer them. Communications on QABB connect users, and the overall connections can be regarded as a social network. If the evolution of social networks can be predicted, it is quite useful for encouraging communications among users. Link prediction on QABB can be used for recommendation to potential answerers. Previous approaches for link prediction based on structural properties do not take weights of links into account. This paper describes an improved method for predicting links based on weighted proximity measures of social networks. The method is based on an assumption that proximities between nodes can be estimated better by using both graph proximity measures and the weights of existing links in a social network. In order to show the effectiveness of our method, the data of Yahoo! Chiebukuro (Japanese Yahoo! Answers) are used for our experiments. The results show that our method outperforms previous approaches, especially when target social networks are sufficiently dense.

Proximity measures for link prediction based on temporal events

Link prediction is a well-known task from the Social Network Analysis field that deals with the occurrence of connections in a network. It consists of using the network structure up to a given time in order to predict the appearance of links in a close future. The majority of previous work in link prediction is focused on the application of proximity measures (e.g., path distance, common neighbors) to non-connected pairs of nodes at present time in order to predict new connections in the future. New links can be predicted for instance by ordering the pairs of nodes according to their proximity scores. A limitation usually observed in previous work is that only the current state of the network is used to compute the proximity scores, without taking any temporal information into account (i.e., a static graph representation is adopted). In this work, we propose a new proximity measure for link prediction based on the concept of temporal events. In our work, we defined a temporal event related to a pair of nodes according to the creation, maintenance or interruption of the relationship between the nodes in consecutive periods of time. We proposed an event-based score which is updated along time by rewarding the temporal events observed between the pair of nodes under analysis and their neighborhood. The assigned rewards depend on the type of temporal event observed (e.g., if a link is conserved along time, a positive reward is assigned). Hence, the dynamics of links as the network evolves is used to update representative scores to pairs of nodes, rewarding pairs which formed or preserved a link and penalizing the ones that are no longer connected. In the performed experiments, we evaluated the proposed event-based measure in different scenarios for link prediction using co-authorship networks. Promising results were observed when the proposed measure was compared to both static proximity measures and a time series approach (a more competitive method) that also deploys temporal information for link prediction.     

Defeasible inheritance with doubt index and its axiomatic characterization

This article introduces and uses a representation of defeasible inheritance networks where links in the network are viewed as propositions, and where defeasible links are tagged with a quantitative indication of the proportion of exceptions, called the doubt index. This doubt index is used for restricting the length of the chains of inference.The representation also introduces the use of defeater literals that disable the chaining of subsumption links. The use of defeater literals replaces the use of negative defeasible inheritance links, expressing “most A are not B”. The new representation improves the expressivity significantly.Inference in inheritance networks is defined by a combination of axioms that constrain the contents of network extensions, a heuristic restriction that also has that effect, and a nonmonotonic operation of minimizing the set of defeater literals while retaining consistency.We introduce an underlying semantics that defines the meaning of literals in a network, and prove that the axioms are sound with respect to this semantics. We also discuss the conditions for obtaining completeness.Traditional concepts, assumptions and issues in research on nonmonotonic or defeasible inheritance are reviewed in the perspective of this approach.     

A mixed-integer approach to Core-Edge design of storage area networks

In this paper we address the problem of optimal network design for a storage area network. We consider the Core-Edge reference topology and present two formulations for the Core-Edge storage area network design problem. One formulation excludes explicit host/device connections to the edge (as is common in currently available heuristics), the other includes these connections to allow the modeling of multiple disjoint paths between hosts and devices. These formulations include generic component types to reduce the number of constraints and variables, with the properties of these components being determined as part of the solution process. The size of the formulation is further reduced by a preprocessing method that removes suboptimal switches and links from consideration.     

Optimal placement of vertical connections in 3D Network-on-Chip

Due to technological limitations, manufacturing yield of vertical connections (Through Silicon Vias, TSVs) in 3D Networks-on-Chip (NoC) decreases rapidly when the number of TSVs grows. The adoption of 3D NoC design depends on the performance and manufacturing cost of the chip. This article presents methods for allocating and placing a minimal number of vertical links and the corresponding vertical routers to achieve specified performance goals. A second optimization step allows to maximize redundancy in order to deal with failing TSVs. Globally optimal solutions are determined for the first time for meshes up to 17 × 17 nodes in size. A 64-core 3D NoC is modeled based on state-of-the-art 2D chips. We present benchmark results using a cycle accurate full system simulator based on realistic workloads. Experiments show that under different workloads, an optimal placement with 25% of vertical connections achieved 81.3% of average network latency and 76.5% of energy delay product, compared with full layer–layer connection. The performance with 12.5% and 6.25% of vertical connections are also evaluated. Our analysis and experiment results provide a guideline for future 3D NoC design.     

A self-processing network model for relational databases

In this paper, a model which combines relational databases with self-processing networks is proposed in order to improve the performance of very large databases. The proposed model uses an approach which is radically different from all other distributed database models, where each computer processes a portion of the database. In the self-processing network model, the network structure which consists of nodes and connections, captures the data and the relationships by assigning them unique, connected control, and data nodes. The network activity is the mechanism that performs the relational algebra operations. No data transmission is needed, and since data nodes are common to all the relations, integrity and elimination of data redundancy are achieved. An extension of the model, by interconnecting the data nodes via weighted links, provides us with properties that are embedded in neural networks, such as fuzziness and learning.     

便携式计算机的路由选择设计

该文详细介绍了移动用户与网络连接的过程,设计出了移动主机与网络连接的模型。重点从外地代理访问移动主机、移动主机登录、外地代理与移动主机建立联系方面全面阐述了移动用户的登录和退出过程,安全、快速、便捷的实现了便携式移动主机与网络的连接。     

基于迭代框架的主动链接选择半监督社区发现算法

针对非负矩阵分解（NMF）半监督社区发现方法随机选择先验约束,导致提升相同性能需要更多约束信息的问题,提出一种基于迭代框架的主动链接选择半监督社区发现算法——ALS_GNMF。在迭代框架下,首先,主动选择不确定性高且对社区划分指导性强的链接对作为先验信息;其次,为主动选择的链接对增加must-link约束,增强社区间连接,生成先验矩阵;同时,增加cannot-link约束,减弱社区间连接,修改邻接矩阵;最后,将先验矩阵作为正则项,加入基于NMF的最优化目标函数,并融合网络拓扑结构信息,以期用较少的先验信息,达到较高的社区发现准确性和鲁棒性。实验结果表明,ALS_GNMF算法在真实网络及人工网络上,相同的先验比例下,性能比未采用迭代框架和主动策略的NMF半监督社区发现方法有更大的提升,且在结构不清晰的网络中表现稳定。