A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

Long Short-Term Memory Recurrent Neural Network-Based Acoustic Model Using Connectionist Temporal Classification on a Large-Scale Training Corpus

A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model(HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic model and a deep learning-based acoustic model. In order to solve this problem, an acoustic model using CTC algorithm is proposed. CTC algorithm does not require the GMM-based acoustic model because it does not use the forced aligned HMM state sequence. However, previous works on a LSTM RNN-based acoustic model using CTC used a small-scale training corpus. In this paper, the LSTM RNN-based acoustic model using CTC is trained on a large-scale training corpus and its performance is evaluated. The implemented acoustic model has a performance of 6.18% and 15.01% in terms of Word Error Rate(WER) for clean speech and noisy speech, respectively. This is similar to a performance of the acoustic model based on the hybrid method.

A Game-Theoretic Perspective on Resource Management for Large-Scale UAV Communication Networks

As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerous advantages,resource management among various domains in large-scale UAV communication networks is the key challenge to be solved urgently.Specifically,due to the inherent requirements and future development trend,distributed resource management is suitable.In this article,we investigate the resource management problem for large-scale UAV communication networks from game-theoretic perspective which are exactly coincident with the distributed and autonomous manner.By exploring the inherent features,the distinctive challenges are discussed.Then,we explore several gametheoretic models that not only combat the challenges but also have broad application prospects.We provide the basics of each game-theoretic model and discuss the potential applications for resource management in large-scale UAV communication networks.Specifically,mean-field game,graphical game,Stackelberg game,coalition game and potential game are included.After that,we propose two innovative case studies to highlight the feasibility of such novel game-theoretic models.Finally,we give some future research directions to shed light on future opportunities and applications.

Efficient Routing Protection Algorithm in Large-Scale Networks

With an increasing urgent demand for fast recovery routing mechanisms in large-scale networks,minimizing network disruption caused by network failure has become critical.However,a large number of relevant studies have shown that network failures occur on the Internet inevitably and frequently.The current routing protocols deployed on the Internet adopt the reconvergence mechanism to cope with network failures.During the reconvergence process,the packets may be lost because of inconsistent routing information,which reduces the network’s availability greatly and affects the Internet service provider’s(ISP’s)service quality and reputation seriously.Therefore,improving network availability has become an urgent problem.As such,the Internet Engineering Task Force suggests the use of downstream path criterion(DC)to address all single-link failure scenarios.However,existing methods for implementing DC schemes are time consuming,require a large amount of router CPU resources,and may deteriorate router capability.Thus,the computation overhead introduced by existing DC schemes is significant,especially in large-scale networks.Therefore,this study proposes an efficient intra-domain routing protection algorithm(ERPA)in large-scale networks.Theoretical analysis indicates that the time complexity of ERPA is less than that of constructing a shortest path tree.Experimental results show that ERPA can reduce the computation overhead significantly compared with the existing algorithms while offering the same network availability as DC.

Gateways Placement in Backbone Wireless Mesh Networks

This paper presents a novel algorithm for the gateway placement problem in Backbone Wireless Mesh Networks (BWMNs). Different from existing algorithms, the new algorithm incrementally identifies gateways and assigns mesh routers to identified gateways. The new algorithm can guarantee to find a feasible gateway placement satisfying Quality-of-Service (QoS) constraints, including delay constraint, relay load constraint and gateway capacity constraint. Experimental results show that its performance is as good as that of the best of existing algorithms for the gateway placement problem. But, the new algorithm can be used for BWMNs that do not form one connected component, and it is easy to implement and use.

A Distributed Virtual Backbone Formation for Wireless Ad Hoc and Sensor Networks

The virtual backbone is an approach for solving routing problems in wireless ad hoc and sensor networks. A connected dominating set (CDS) was proposed as a virtual backbone to improve the performance of wireless networks. The quality of a virtual backbone is measured not only by approximation factor, which is the ratio of its size to that of minimum CDS, but also time complexity and message complexity. In this paper, a distributed algorithm is presented to construct a minimum CDS for ad hoc and sensor networks. By destroying triangular loops in the virtual backbone, the proposed algorithm can effectively construct a CDS with smaller size. Moreover, our algorithm, which is fully localized, has a constant approximation ratio, linear message and time complexity, and low implementation complexity. The simulation results and theoretical analysis show that our algorithm has better efficiency and performance than conventional approaches.

A Study of Configuration Evolution of an Operational IP Backbone Network

Configuration errors are proved to be the main reasons for network interruption and anomalies.Many researchers have paid their attention to configuration analysis and provisioning,but few works focus on understanding the configuration evolution.In this paper,we uncover the configuration evolution of an operational IP backbone based on the weekly reports gathered from January 2006 to January 2013.We find that rate limiting and launching routes for new customers are configured most frequently.In addition,we conduct an analysis of network failures and find that link failures are the main causes for network failures.We suggest that we should configure redundant links for the links which are easy to break down.At last,according to the analysis results,we illustrate how to provide semi-automated configuration for rate limiting and adding customers.

Robust Virtual Network Embedding Based on Component Connectivity in Large-Scale Network

Virtual network embedding problem which is NP-hard is a key issue for implementing software-defined network which is brought about by network virtualization. Compared with other studies which focus on designing heuristic algorithms to reduce the hardness of the NP-hard problem we propose a robust VNE algorithm based on component connectivity in large-scale network. We distinguish the different components and embed VN requests onto them respectively. And k-core is applied to identify different VN topologies so that the VN request can be embedded onto its corresponding component. On the other hand, load balancing is also considered in this paper. It could avoid blocked or bottlenecked area of substrate network. Simulation experiments show that compared with other algorithms in large-scale network, acceptance ratio, average revenue and robustness can be obviously improved by our algorithm and average cost can be reduced. It also shows the relationship between the component connectivity including giant component and small components and the performance metrics.

Software-Defined Space-Air-Ground Integrated Network Architecture with the Multi-Layer Satellite Backbone Network

Under the background of the rapid development of ground mobile communication,the advantages of high coverage,survivability,and flexibility of satellite communication provide air support to the construction of space information network.According to the requirements of the future space information communication,a software-defined Space-Air-Ground Integrated network architecture was proposed.It consisted of layered structure satellite backbone network,deep space communication network,the stratosphere communication network and the ground network.The Space-Air-Ground Integrated network was supported by the satellite backbone network.It provided data relay for the missions such as deep space exploration and controlled the deep-space spacecraft when needed.In addition,it safeguarded the anti-destructibility of stratospheric communication and assisted the stratosphere to supplement ground network communication.In this paper,algorithm requirements of the congestion control and routing of satellite backbone protocols for heterogeneous users’services were proposed.The algorithm requirements of distinguishing different service objects for the deep space communication and stratospheric communication network protocols were described.Considering the realistic demand for the dynamic coverage of the satellite backbone network and node cost,the multi-layer satellite backbone network architecture was constructed.On this basis,the proposed Software-defined Space-Air-Ground Integrated network architecture could be built as a large,scalable and efficient communication network that could be integrated into space,air,and ground.

The enlightenment of artificial intelligence large-scale model on the research of intelligent eye diagnosis in traditional Chinese medicine

Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However;the research on intelligent eye diagnosis still faces many challenges;including the lack of standardized and precisely labeled data;multi-modal information analysis;and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis;and explores the implications for the research of eye diagno-sis intelligence.First;a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next;the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last;the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary;research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications.

Sewage flow optimization algorithm for large-scale urban sewer networks based on network community division

By considering the flow control of urban sewer networks to minimize the electricity consumption of pumping stations, a decomposition-coordination strategy for energy savings based on network community division is developed in this paper. A mathematical model characterizing the steady-state flow of urban sewer networks is first constructed, consisting of a set of algebraic equations with the structure transportation capacities captured as constraints. Since the sewer networks have no apparent natural hierarchical structure in general, it is very difficult to identify the clustered groups. A fast network division approach through calculating the betweenness of each edge is successfully applied to identify the groups and a sewer network with arbitrary configuration could be then decomposed into subnetworks. By integrating the coupling constraints of the subnetworks, the original problem is separated into N optimization subproblems in accordance with the network decomposition. Each subproblem is solved locally and the solutions to the subproblems are coordinated to form an appropriate global solution. Finally, an application to a specified large-scale sewer network is also investigated to demonstrate the validity of the proposed algorithm.

Parameterless Pruning Algorithms for Similarity-Weight Network and Its Application in Extracting the Backbone of Global Value Chain

Purpose:With the availability and utilization of Inter-Country Input-Output(ICIO)tables,it is possible to construct quantitative indices to assess its impact on the Global Value Chain(GVC).For the sake of visualization,ICIO networks with tremendous low-weight edges are too dense to show the substantial structure.These redundant edges,inevitably make the network data full of noise and eventually exert negative effects on Social Network Analysis(SNA).In this case,we need a method to filter such edges and obtain a sparser network with only the meaningful connections.Design/methodology/approach:In this paper,we propose two parameterless pruning algorithms from the global and local perspectives respectively,then the performance of them is examined using the ICIO table from different databases.Findings:The Searching Paths(SP)method extracts the strongest association paths from the global perspective,while Filtering Edges(FE)method captures the key links according to the local weight ratio.The results show that the FE method can basically include the SP method and become the best solution for the ICIO networks.Research limitations:There are still two limitations in this research.One is that the computational complexity may increase rapidly while processing the large-scale networks,so the proposed method should be further improved.The other is that much more empirical networks should be introduced to testify the scientificity and practicability of our methodology.Practical implications:The network pruning methods we proposed will promote the analysis of the ICIO network,in terms of community detection,link prediction,and spatial econometrics,etc.Also,they can be applied to many other complex networks with similar characteristics.Originality/value:This paper improves the existing research from two aspects,namely,considering the heterogeneity of weights and avoiding the interference of parameters.Therefore,it provides a new idea for the research of network backbone extraction.

Spanning tree-based algorithm for hydraulic simulation of large-scale water supply networks

With the purpose of making calculation more efficient in practical hydraulic simulations, an improved algorithm was proposed and was applied in the practical water distribution field. This methodology was developed by expanding the traditional loop-equation theory through utilization of the advantages of the graph theory in efficiency. The utilization of the spanning tree technique from graph theory makes the proposed algorithm efficient in calculation and simple to use for computer coding. The algorithms for topological generation and practical implementations are presented in detail in this paper. Through the application to a practical urban system, the consumption of the CPU time and computation memory were decreased while the accuracy was greatly enhanced compared with the present existing methods.

Backbone formulation algorithm in wireless sensor network based on cross-entropy method

In wireless sensor network,virtual backbone is a cost effective broadcasting method.Connected dominating set formation is proposed to construct a virtual backbone.However,it is NP-Hard to find a minimum connected dominating set in an arbitrary graph.In this paper,based on cross-entropy method,we present a novel backbone formulation algorithm(BFA-CE)in wireless sensor network.In BFA-CE,a maximal independent set is got at first and nodes in the independent set are required to get their action sets.Based on those action sets,a backbone is generated with the cross-entropy method.Simulation results show that our algorithm can effectively reduce the size of backbone network within a reasonable message overhead,and it has lower average node degree.This approach can be potentially used in designing efficient broadcasting strategy or working as a backup routing of wireless sensor network.

Method of Distribution Network Resources after Restoration, the Networks MPLS-TE Use of Various Telecommunications Technologies to Construct Backbone Networks

The modern telecommunication system is characterized by the rapid improvement of information and communication technologies, such as the improvement in the data rate, power consumption and Quality of Service (QoS). Based on this development, the next generation network (NGN) is shaped. The NGN is represented by a packet transport network demarcated functions and services. To provide transport functions in NGN, using Multi-Protocol Label Switching (MPLS) technology, there are two main problems, which are multipath routing and traffic distribution, which are what this paper works with. Accordingly, this paper proposes a solution to these two problems using optimization procedures to find the shortest path Dijkstra and Bellman-Ford, which is characterized by a high-speed-oriented selection of a single shortest path between the source and the destination, based on several selected criteria related to the optimal use of the network resources. Solving the information flow distribution problems in large number of nodes network applying salesman procedure or having NP-completeness, causes significant time delay, which means that the proposed solution is not suitable for real time applications. Accordingly, for real time applications, there is a need to move to other methods based on the use of several independent shortest paths.

Intelligent Networking Technology and Experimental Demonstration of Large-Scale Heterogeneous Optical Networks

A novel routing architecture named DREAMSCAPE is presented to solve the problem of path computation in multi-layer, multi-domain and multi-constraints scenarios, which includes Group Engine (GE) and Unit Engine (UE). GE, UE and their cooperation relationship form the main feature of DREAMSCAPE, i.e. Dual Routing Engine (DRE). Based on DRE, two routing schemes are proposed, which are DRE Forward Path Computation (DRE-FPC) and Hierarchical DRE Backward Recursive PCE-based Computation (HDRE-BRPC). In order to validate various intelligent networking technologies of large-scale heterogeneous optical networks, a DRE-based transport optical networks testbed is built with 1000 GMPLS-based control nodes and 5 optical transport nodes. The two proposed routing schemes, i.e. DRE-FPC and HDRE-BRPC, are validated on the testbed, compared with traditional Hierarchical Routing (HR) scheme. Experimental results show a good performance of DREAMSCAPE.

A Summary of the Large-Scale Access Convergence Network Structure

Under the requirement of everything over IP, network service shows the following characteristics:(1) network service increases its richness;(2) broadband streaming media becomes the mainstream. To achieve unified multi-service bearing in the IP network, the largescale access convergence network architecture is proposed. This flat access convergence structure with ultra-small hops, which shortens the service transmission path, reduces the complexity of the edge of the network, and achieves IP strong waist model with the integration of computation, storage and transmission. The key technologies are also introduced in this paper, including endto-end performance guarantee for real time interactive services, fog storing mechanism, and built-in safety transmission with integration of aggregation and control.

An Adaptive Sliding Mode Tracking Controller Using BP Neural Networks for a Class of Large-scale Nonlinear Systems

A new type controller, BP neural-networks-based sliding mode controller is developed for a class of large-scale nonlinear systems with unknown bounds of high-order interconnections in this paper. It is shown that decentralized BP neural networks are used to adaptively learn the uncertainty bounds of interconnected subsystems in the Lyapunov sense, and the outputs of the decentralized BP neural networks are then used as the parameters of the sliding mode controller to compensate for the effects of subsystems uncertainties. Using this scheme, not only strong robustness with respect to uncertainty dynamics and nonlinearities can be obtained, but also the output tracking error between the actual output of each subsystem and the corresponding desired reference output can asymptotically converge to zero. A simulation example is presented to support the validity of the proposed BP neural-networks-based sliding mode controller.

Essential Topics on Constructing WCDS-based Virtual Backbone in Wireless Sensor/Mesh Networks

Clustering or connected dominating set (CDS) both approaches can establish a virtual backbone (VB) in wireless sensor networks (WSNs) or wireless mesh networks (WMNs). Each cluster consisting of a cluster head (CH) and its neighboring nodes can form a dominating set. After some bridging nodes were selected, cluster heads (CHs) connected through these bridging nodes naturally formed a CDS. Although CDS provides obvious backbone architecture, however, the number of cluster heads and bridging nodes may be too large, this may cause the loss of advantages of virtual backbone. When we effectively reduce their numbers, more effectively WCDS (Weakly Connected Dominating Set) can be fining out. Some essential topics on constructing WCDS-based VB in WSN/WMN are discussed in this paper. From the point of view of three different protocol layers, including network (NWK) layer, MAC layer, and physical (PHY) layer, we explore their cross-layer research topics and design algorithms. For NWK layer, area-based WCDS algorithms and routing strategies including via VB and not via VB are discussed. For MAC layer, a WCDS-based energy-efficient MAC protocol is presented. For PHY layer, battery-aware alternative VB selections and sensor nodes with different transmission ranges are addressed.

Design of High Precision Horizontal Control Network for Large-Scale Hydropower Project

A new solution of combination network of GPS and high precise distance measurements with EDM is proposed. Meanwhile, it’s inadvisable only using GPS network without distance measurements. Three schemes: terrestrial network, GPS network and combination network are discussed for horizontal control network design of Xiangjiaba Dam in view of precision, reliability, coordinate and outlay in detail.