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multi-layer network embedding on scc-based network with motif

Digital Communications and networks 2024年第3期10卷 546-556页

作者： Lu Sun Xiaona Li Mingyue Zhang Liangtian Wan Yun Lin Xianpeng Wang Gang Xu Department of Communication Engineering Institute of Information Science TechnologyDalian Maritime UniversityDalian116026China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory for Ubiquitous network and Service Software of Liaoning Province DUT School of Software Technology&DUT-RU International School of Information Science and EngineeringDalian University of TechnologyDalian 116620China College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China School of Information and Communication Engineering Hainan UniversityHaikou 570228China State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast UniversityNanjing 210096China

Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new *** is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based *** previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node ***,the content of semantic information is quite *** graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of ***,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology *** Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node *** verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.

关键词： Semantic communication and computing multi-layer network Graph neural network Motif

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multi-layer network architecture in support of end-to-end transparent optical connectivities

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Science China(Information Sciences) 2011年第3期54卷 674-682页

作者： GUO HongXiang , WU Jian, HONG Xiao Bin & LIN Jin Tong Key Laboratory of Information Photonics and Optical Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China 1. Key Laboratory of Information Photonics and Optical Communications Ministry of Education Beijing University of Posts and Telecommunications Beijing 100876 China

In order to effectively accommodate a wide variety of emerging and future applications with diverse requirements, an intelligent optical network capable of the rapid and resilient delivery of on-demand transparent transmission capacity is required. This paper investigates a multi-layer network architecture where a generalized multiple protocol label switching (GMPLS) controlled transparent wavelength switched optical network (WSON), as the transport core, collaborates with multiple client optical burst switching (OBS) networks distributed at the edge. Dynamic interworking mechanism as well as the related signaling/routing protocol ex- tensions for multi-QoS burst streams transmission among different OBS domains are proposed so as to provision an end-to-end (e2e) transparent optical connectivity with on-demand bandwidth to end-users. Moreover, the survivability of this transparent optical connectivity is also addressed. To validate the feasibility of this architecture, an integrated OBS/WSON network testbed was constructed, and stable e2e transparent connectivities were successfully demonstrated for an efficient multi-QoS burst streams transmission.

关键词： multi-layer network transparent optical network OBS WSON GMPLS

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Identifying disease modules and components of viral infections based on multi-layer networks

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Science China(Information Sciences) 2016年第7期59卷 15-29页

作者： Yuanyuan LI Xiufen ZOU School of Mathematics and Statistics Wuhan University Computational Science Hubei Key Laboratory Wuhan University School of Science Wuhan Institute of Technology

With the emergence of multi-dimensional data, we can more comprehensively analyze the pathogenic mechanisms of complex diseases, and thereby improve the diagnosis, treatment and prevention of these *** study presents a novel multi-layer network-based strategy that integrates multi-dimensional data, and identifies disease-related modules and components of viral infections. We first propose a systematic method that constructs a virus-host interaction network with three layers: a viral protein layer, a host protein layer and a host gene layer. This method combines the data of high-throughput gene expression, viral protein interactions,virus-host interactions, protein-protein interactions and transcriptional regulatory relationships. To extract the underlying mechanisms of viral infections from the multi-layer networks, we identify the intra-layer and crosslayer modules, and investigate the conserved modules across multiple datasets. The essential components in the multi-layer networks are detected by singular-value decomposition. The identified conserved modules and essential components are combined into a functional enrichment analysis that reveals their contributions to influenza virus replication. By this analysis, we elucidate the common and specific mechanisms of the replication cycles of two influenza strains. By combining the different layers of information, we can comprehensively understand pathogenic mechanisms of complex diseases.

关键词： multi-dimensional data multi-layer network complex disease virus infection disease modules

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Intra-layer synchronization in duplex networks

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Chinese Physics B 2018年第10期27卷 245-251页

作者： Jie Shen Longkun Tang Fujian Province University Key Laboratory of Computation Science School of Mathematical SciencesHuaqiao UniversityQuanzhou 362021China Department of Mathematics ＆ Statistics Georgia State UniversityAtlanta 30303USA

This paper explores the intra-layer synchronization in duplex networks with different topologies within layers and different inner coupling patterns between, within, and across layers. Based on the Lyapunov stability method, we prove theoretically that the duplex network can achieve intra-layer synchronization under some appropriate conditions, and give the thresholds of coupling strength within layers for different types of inner coupling matrices across layers. Interestingly,for a certain class of coupling matrices across layers, it needs larger coupling strength within layers to ensure the intra-layer synchronization when the coupling strength across layers become larger, intuitively opposing the fact that the intra-layer synchronization is seemly independent of the coupling strength across layers. Finally, numerical simulations further verify the theoretical results.

关键词： multi-layer network intra-layer synchronization Lyapunov stability method

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A modelling study of awareness and multi-disease transmission in multilayer networks

A modelling study of awareness and multi-disease transmissio...

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第43届中国控制会议

作者： Jiayu Ye Yinzuo Zhou Alibaba Business School Hangzhou Normal University

Infectious disease pandemics have been key to the global health crisis,and understanding their transmission and behavioural dynamics is essential to control their *** this paper,we propose a model based on a multilayer composite network that combines disease transmission and consciousness to simulate the co-evolutionary process of two *** model takes into account the topology of physical contact between populations and the influence of consciousness on the spread of two interacting *** use the Micromarkov Chain Approach(MMCA) to develop a state transition equation and derive transmission thresholds under the epidemic *** also compare the performance of different models in an upper-level network representing the exchange of information between conscious and unconscious *** results provide epidemiological studies with more effective models for understanding the co-evolution of two competing epidemics and conscious *** is revealed that consciousness processes may have opposite effects on epidemics under different conditions of biological *** result is substantially different from the case where consciousness processes act alone.

关键词： multi-layer network Consciousness Micro Markov Chain Method Epidemic model Epidemiology

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Immunizations of Interacting Diseases

Immunizations of Interacting Diseases

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第37届中国控制会议

作者： Shenyu Zhou Shuyang Shi Lin Wang Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

Immunization strategies for epidemics spreading on complex networks have been studied widely for a long ***, most previous studies only pay attention to the single disease scenarios and little effort is devoted to the circumstances where more than one disease exist. In this article, we propose a propagation model of two interacting SIR-type epidemics spreading simultaneously on a two-layer network, and investigate the performance of different immunization strategies under different disease interaction scenarios. Specifically, we introduce two metrics, the spreading scale and the maximum spreading speed, to characterize the performance of acquaintance immunization and targeted immunization strategies. Under different interaction circumstances where the two diseases are mutually enhanced, impaired or not affected with each other, those immunization strategies perform differently. Moreover, immunization of one disease can dramatically influence the propagation of the other disease,which illustrate the necessity to consider the interaction effects between diseases in the design of immunization strategies.

关键词： multi-layer network Interacting epidemics Immunization strategies

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