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Efficient Community Detection in Large-Scale Dynamic Networks Using Topological Data Analysis [article]

Wei Guo, Ruqian Chen, Yen-Chi Chen, Ashis G. Banerjee
2022 arXiv   pre-print
In this paper, we propose a method that extends the persistence-based topological data analysis (TDA) that is typically used for characterizing shapes to general networks.  ...  We introduce the concept of the community tree, a tree structure established based on clique communities from the clique percolation method, to summarize the topological structures in a network from a  ...  Supplemental Materials: Efficient Community Detection in Large-Scale Dynamic Networks Using Topological Data Analysis S1 Design of Data Structure We assign each vertex v with a unique ID, denoted by  ... 
arXiv:2204.03191v1 fatcat:rowa63emrrftlmlv4envlaarlq

Visual analysis of large-scale network anomalies

Q. Liao, L. Shi, C. Wang
2013 IBM Journal of Research and Development  
In this paper, we provide a brief overview of several useful visualization techniques for the analysis of spatiotemporal anomalies in large-scale networks.  ...  TEMG transforms network topologies into directed trees so that efficient search is more likely to be performed for anomalous changes in network behavior and routing topology in large dynamic networks.  ...  In this paper, we present a brief overview of five potentially useful graph visualization techniques for anomaly analysis on large-scale network data.  ... 
doi:10.1147/jrd.2013.2249356 fatcat:foajq5zrmzhkfl4rnjh7hvdzei

2019 Index IEEE Transactions on Network Science and Engineering Vol. 6

2019 IEEE Transactions on Network Science and Engineering  
., +, TNSE April -June 2019 158-172 Numerical analysis Threshold Models of Cascades in Large-Scale Networks.  ...  -Dec. 2019 844-856 Threshold Models of Cascades in Large-Scale Networks.  ...  Probability density function Identification of Missing Links Using Susceptible-Infected-Susceptible Spreading Traces. Vajdi, A., +, TNSE Oct.-Dec. 2019  ... 
doi:10.1109/tnse.2020.2964975 fatcat:mb5jt4io7jfbdiso323jgi7hlm

Research on MAC Protocols in Cluster-Based Ad Hoc Networks

Yutao Liu, Yue Li, Yimeng Zhao, Chunhui Zhang, Xin Liu
2021 Wireless Communications and Mobile Computing  
Mobile ad hoc networks can be widely used in many scenes, for example, military communication, emergency communication, and 5G wide area coverage as well as ultradense network scenes.  ...  In view of multiservice simultaneous transmission demand for small-scale dense networking scene and large-scale extended networking scene, a MAC protocol based on scheduling of cluster head is proposed  ...  Analysis for Large-Scale Extended Coverage Networking Scene.  ... 
doi:10.1155/2021/5513469 fatcat:ryhqe35uxbbfjgv7lha7uglcqq

Complex Networks, Communities and Clustering: A survey [article]

Biswajit Saha, Amitabha Mandal, Soumendu Bikas Tripathy, Debaprasad Mukherjee
2015 arXiv   pre-print
Complex networks describe a widespread variety of systems in nature and society especially systems composed by a large number of highly interconnected dynamical entities.  ...  Complex networks like real networks can also have community structure. There are several types of methods and algorithms for detection and identification of communities in complex networks.  ...  As can be seen community detection in complex networks is an active research area and has got real life applications in the fields of large scale engineering, social media analysis, biomedical data analysis  ... 
arXiv:1503.06277v1 fatcat:6rllcyatpzblhocuny76fwpk2u

A Novel Emerging Topic Identification and Evolution Discovery Method on Time-Evolving and Heterogeneous Online Social Networks

Xiaoyan Xu, Wei Lv, Beibei Zhang, Shuaipeng Zhou, Wei Wei, Yusen Li
2021 Complexity  
; secondly, a novel dynamic community detection method is proposed by which the new emerging topic is detected on the modeled time-evolving and scalable KeyGraph network; thirdly, a unified directional  ...  This paper proposed a novel early emerging topic detection and its evolution law identification framework based on dynamic community detection method on time-evolving and scalable heterogeneous social  ...  E t+Δt 􏼈 􏼉, which enables its applications in the large-scale network. e flow chart of our proposed dynamic community detection method is presented in Figure 2 .  ... 
doi:10.1155/2021/8859225 doaj:66c1eb9e63284b80953f2fe3507f4ffc fatcat:dv6xk3hr5zey3ohxoxmwdgx2ga

Dynamic Community Detection via Adversarial Temporal Graph Representation Learning [article]

Changwei Gong, Changhong Jing, Yanyan Shen, Shuqiang Wang
2022 arXiv   pre-print
In this work, an adversarial temporal graph representation learning (ATGRL) framework is proposed to detect dynamic communities from a small sample of brain network data.  ...  Dynamic community detection has been prospered as a powerful tool for quantifying changes in dynamic brain network connectivity patterns by identifying strongly connected sets of nodes.  ...  Introduction Neuroscience is emerging into a generation marked by a large amount of complex neural data obtained from large-scale neural systems [1] .  ... 
arXiv:2207.03580v1 fatcat:gp25wftdmjhhxefjgdrcqi6b5y

Design of Complex Network Distributed Computing Information Mining Method

Yiran Wang, Guang Zheng
2015 International Journal of Grid and Distributed Computing  
The information that caused by the complex network is massive, but because of a large amount of information, so the use of traditional data analysis has been unable to meet the search and mining complex  ...  This paper presents a data mining model matrix, according to this model can integrate different information, optimization of data mining, so as to improve the efficiency of complex network distributed  ...  (No 61103143), basic and frontier project of Science and Technology Department of Henan province, China (No 142300410334), the funding scheme for young backbone teachers of colleges and universities in  ... 
doi:10.14257/ijgdc.2015.8.5.09 fatcat:oxmndlmbjze37jdxf6dpd4ynle

Problem Domains in Complex Networks

Mini Singh Ahuja
2016 IOSR Journal of Computer Engineering  
In this paper most important research domains related to complex networks are reviewed such as Community detection, Influence Maximization, network sampling etc.  ...  Complex networks are special graphs with non trivial topological properties-features that do not occur in simple networks such as lattices or random graphs.  ...  So the modeling and analysis of such huge data is also one of the challenging problems. In order to study these massive graphs, we need to represent and process large scale graphs.  ... 
doi:10.9790/0661-1805026568 fatcat:nxcrszgskjbkfmgzel4ml5a4sq

Neural Signaling and Communication [chapter]

Syeda Huma Jabeen, Nadeem Ahmed, Muhammad Ejaz Sandhu, Nauman Riaz Chaudhry, Reeha Raza
2019 New Frontiers in Brain-Computer Interfaces [Working Title]  
In this chapter we focus on how neurosignaling and communication is playing its part in medical psychology, furthermore, we have also reviewed how the interaction of network topology and dynamic models  ...  The neuroscientific community is interested in the network architecture of the human brain its simulation and for prediction of emergent network states.  ...  to a burst of data developed using a diverse array of measurement methods, and at scales fluctuating from a level of single cells to large brain areas.  ... 
doi:10.5772/intechopen.86318 fatcat:xy6tuwguavhetpkou5uaewgxji

Systems for Near Real-Time Analysis of Large-Scale Dynamic Graphs [article]

Luis M. Vaquero, Felix Cuadrado, Matei Ripeanu
2014 arXiv   pre-print
The sheer amount of data to be processed has prompted the creation of a myriad of systems that help us cope with massive scale graphs.  ...  Graphs are widespread data structures used to model a wide variety of problems.  ...  Some work has been done beyond topological measurements: information-theoretical adaptive algorithms. [66] use network entropy for detecting temporal uncertainty in communication networks.  ... 
arXiv:1410.1903v1 fatcat:axdwyivrlfev5phapnwng7jgoy

Mass Cooperative Transmission and QoS Supported Mechanism in Wireless Sensor Networks

Gelan Yang, Deguang Le, Yong Jin, Su-Qun Cao
2014 International Journal of Distributed Sensor Networks  
Zhu et al. proposes a dynamic Bayesian model averaging method for highaccuracy prediction analytics in large-scale IoT applications.  ...  The simulation results show that the proposed topologies have small-world, scale-free feathers and a better performance in improving energy efficiency and enhancing network robustness.  ...  Zhu et al. proposes a dynamic Bayesian model averaging method for highaccuracy prediction analytics in large-scale IoT applications.  ... 
doi:10.1155/2014/363584 fatcat:3dgywtg7ezehhl42norpkzemue

Graph theory methods: applications in brain networks

Olaf Sporns
2018 Dialogues in Clinical Neuroscience  
Network neuroscience is a thriving and rapidly expanding field. Empirical data on brain networks, from molecular to behavioral scales, are ever increasing in size and complexity.  ...  A number of emerging trends are the growing use of generative models, dynamic (time-varying) and multilayer networks, as well as the application of algebraic topology.  ...  A recent example used topological data analysis to reveal dynamical organization in multitask fMRI time series, by creating graphical representations of relations among single image frames at the level  ... 
pmid:30250388 pmcid:PMC6136126 fatcat:xgy23bv45ve3pmtu5msj73crcu

Interactive Wormhole Detection in Large Scale Wireless Networks

Weichao Wang, Aidong Lu
2006 2006 IEEE Symposium On Visual Analytics And Technology  
This paper develops an approach, Interactive Visualization of Wormholes (IVoW), to monitor and detect such attacks in large scale wireless networks in real time.  ...  We characterize the topology features of a network under wormhole attacks through the node position changes and visualize the information at dynamically adjusted scales.  ...  The method introduced in this paper, Interactive Visualization of Wormhole (IVoW), provides a visual approach through which the users can detect multiple wormholes in a large scale, dynamic wireless network  ... 
doi:10.1109/vast.2006.261435 dblp:conf/ieeevast/WangL06 fatcat:hay3euigpbc6vn5ggjc22acm7u

RETRACTED ARTICLE: Invulnerability mechanism based on mobility prediction and opportunistic cloud computing with topological evolution for wireless multimedia sensor networks

Jianming Zhou, Tao Dong
2015 EURASIP Journal on Wireless Communications and Networking  
Experimental results show that compared with the static scheme for WMSNs, the proposed survivability mechanism has the obvious advantage in the node protection, data communication, network life cycle,  ...  Finally, using the network topology reconfiguration and opportunities for cloud computing, an enhanced WMSN survivability and end-to-end quality of service guarantee mechanism was proposed.  ...  consumption, and dynamic evolution of network topology in real time.  ... 
doi:10.1186/s13638-015-0471-6 fatcat:yawhcput7zh4nbxkmnef3xu73m
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