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Books on the topic 'Network topology'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 May 2024

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1

Sakavalas, Dimitris, and Lewis Tseng. Network Topology and Fault-Tolerant Consensus. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-031-02014-8.

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2

Network topology optimization: The art and science of network design. New York: Van Nostrand Reinhold, 1990.

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3

Network and Algebraic Topology of Influenza Evolution. [New York, N.Y.?]: [publisher not identified], 2013.

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4

Ofosu-Amaah, Betty. Morp hology of organisation structure and network topology. London: University of East London, 1990.

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5

Anthony, Maxwell, ed. DNA topology. Oxford: IRL Press at Oxford University Press, 1993.

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6

Dhillon, Santpal Singh. Ant routing, searching and topology estimation algorithms for ad hoc netwoks. Amsterdam: IOS Press, 2008.

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7

Dhillon, Santpal Singh. Ant routing, searching and topology estimation algorithms for ad hoc netwoks. Amsterdam: IOS Press, 2008.

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8

Grant, T. J. Network topology in command and control: Organization, operation, and evolution. Hershey, PA: Information Science Reference, 2014.

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9

Qin, Jiahu, Qichao Ma, Huijun Gao, Wei Xing Zheng, and Yu Kang. Consensus Over Switching Network Topology: Characterizing System Parameters and Joint Connectivity. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85657-1.

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10

Ofek, Yoram. The topology, algorithms, and analysis of a synchronous optical hypergraph architecture. Urbana, Ill: Dept. of Computer Science, University of Illinois at Urbana-Champaign, 1987.

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11

Diebold, Francis X. On the network topology of variance decompositions: Measuring the connectedness of financial firms. Cambridge, MA: National Bureau of Economic Research, 2011.

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12

Diebold, Francis X. On the network topology of variance decompositions: Measuring the connectedness of financial firms. Cambridge, MA: National Bureau of Economic Research, 2011.

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13

Dafik, ed. Proceedings of the 6th International Conference on Combinatorics, Graph Theory, and Network Topology (ICCGANT 2022). Dordrecht: Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-138-8.

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14

Wuyi, Yue, Takahashi Yataka, and Takagi Hideaki, eds. Advances in queueing theory and network applications. New York, N.Y: Springer, 2009.

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15

IEEE P802.3 System Topology Technical Advisory Group., ed. Network systems tutorial for the IEEE std. 802.3: Repeater functions and system design topology considerations for carrier sense multiple access with collision detection (CSMA/CD) local area networks (LANs). New York: IEEE Standards Press, 1995.

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16

Tony, Peatfield, IEEE P802.3 Working Group., and IEEE Computer Society, eds. Network systems tutorial for the IEEE std. 802.3: Repeater functions and system design topology considerations for carrier sense multiple access with collision detection (CSMA/CD) local area networks (LANs). New York: IEEE Standards Press, 1995.

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17

Naimzada, Ahmad K., Silvana Stefani, and Anna Torriero, eds. Networks, Topology and Dynamics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-68409-1.

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18

Guo, Xuerong. All-optic networks based on Debruijn topology. Ottawa: National Library of Canada, 1994.

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19

Santi, Paolo. Topology Control in Wireless Ad Hoc and Sensor Networks. Chichester, UK: John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470094559.

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20

Topology control in wireless ad hoc and sensor networks. Chichester, UK: John Wiley & Sons, 2004.

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21

Santi, Paolo. Topology Control in Wireless Ad Hoc and Sensor Networks. New York: John Wiley & Sons, Ltd., 2005.

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22

MobiSec 2009 (2009 Turin, Italy). Security and privacy in mobile information and communication systems: First international ICST conference, MOBISEC 2009, Turin, Italy, June 3-5, 2009, revised selected papers. Berlin: Springer, 2009.

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23

Liu, Jilei. Topology control in wireless sensor and mobile ad hoc networks. Ottawa: National Library of Canada, 2002.

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24

Ding, Wei. Topology construction for bootstrapping peer-to-peer systems over ad-hoc networks. Hauppauge, NY, USA: Nova Science, 2009.

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25

Avanessian, Jay Varoujan. Error-correcting routing algorithm for bidirectional de Brujin topology based all-optical networks. Ottawa: National Library of Canada, 1996.

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26

International Symposium on Topological Aspects of Critical Systems and Networks (2006 Sapporo, Japan). Proceedings of the International Symposium on Topological Aspects of Critical Systems and Networks, Sapporo, Japan, 13-14 February 2006. Edited by Yakubo K. Singapore: World Scientific, 2007.

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27

Labrador, Miguel A. Topology Control in Wireless Sensor Networks: With a companion simulation tool for teaching and research. Dordrecht: Springer Netherlands, 2009.

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28

Adaptive networks: Theory, models and applications. Dordrecht: Springer, 2009.

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29

Decato, Steven W. Parallel processing performance evaluation of mixed T10. Monterey, Calif: Naval Postgraduate School, 1997.

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30

Flapan, Erica. Knots, molecules, and the universe: An introduction to topology. Providence, Rhode Island: American Mathematical Society, 2015.

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31

Six degrees: The science of a connected age. New York: Norton, 2003.

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32

Blokdyk, Gerardus. Network topology Standard Requirements. 5STARCooks, 2018.

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33

Sakavalas, Dimitris, Lewis Tseng, and Michel Raynal. Network Topology and Fault-Tolerant Consensus. Morgan & Claypool Publishers, 2019.

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34

Sakavalas, Dimitris, and Lewis Tseng. Network Topology and Fault-Tolerant Consensus. Springer International Publishing AG, 2019.

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35

Sakavalas, Dimitris, Lewis Tseng, and Michel Raynal. Network Topology and Fault-Tolerant Consensus. Morgan & Claypool Publishers, 2019.

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36

Sakavalas, Dimitris, Lewis Tseng, and Michel Raynal. Network Topology and Fault-Tolerant Consensus. Morgan & Claypool Publishers, 2019.

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37

Hekmat, Ramin. Ad-Hoc Networks: Fundamental Properties and Network Topologies. Springer Netherlands, 2017.

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38

Ad-hoc Networks: Fundamental Properties and Network Topologies. Springer, 2006.

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39

Hekmat, Ramin. Ad-Hoc Networks: Fundamental Properties and Network Topologies. Springer, 2006.

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40

Hekmat, Ramin. Ad-Hoc Networks: Fundamental Properties and Network Topologies. Springer, 2010.

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41

Kurt, Engr Wilson. Network Topology: The Physical and Logical Structure of a Network Connection Between Model and Nodes. Independently Published, 2019.

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42

Gao, Huijun, Wei Xing Zheng, Yu Kang, Jiahu Qin, and Qichao Ma. Consensus over Switching Network Topology: Characterizing System Parameters and Joint Connectivity. Springer International Publishing AG, 2022.

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43

Gao, Huijun, Wei Xing Zheng, Yu Kang, Jiahu Qin, and Qichao Ma. Consensus over Switching Network Topology: Characterizing System Parameters and Joint Connectivity. Springer International Publishing AG, 2021.

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44

Network Topologies: Types, Performance Impact and Advantages/Disadvantages. Nova Science Pub Inc, 2013.

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45

Stein, Denis. Mobile Laser Scanning Based Determination of Railway Network Topology and Branching Direction on Turnouts. Saint Philip Street Press, 2020.

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46

Parsons, Michael Raymond. Spatial and temporal changes in stream network topology: Post-eruption drainage, Mount St. Helens. 1985.

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47

McLochlin, Charles D. Formulas and algorithms for optimizing the performance of rapidly changing satellite networks. 1989.

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48

Bianconi, Ginestra. Structural Correlations of Multiplex Networks. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0007.

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Multiplex networks encode relevant information in their correlated structure, including interlayer degree correlation, link overlap, weight–topology correlations in weighted multiplex networks and activity of the nodes. Interlayer degree correlations among a pair of layers indicates for instance whether or not the hub nodes of one layer are also hub nodes in the other. Link overlap indicates that a finite fraction of nodes are connected in more than one layer. Weight–topology correlations of weighted complex networks reveal that the weight of the links is not random, but often correlated with the link overlap. Finally, the nodes of a multiplex network might be connected only in a subset of the network, leading to a heterogeneity node activity. This chapter identifies the main multiplex network measures for characterizing these correlations, and evaluates their significance using statistical and information theory methods and novel multiplex network measures, including multilinks and multidegrees.
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49

Namatame, Akira, and Takanori Komatsu. Modeling of Desirable Socioeconomic Networks. Edited by Shu-Heng Chen, Mak Kaboudan, and Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.15.

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This chapter discusses the issues of designing desirable socioeconomic networks. Such networks permeate our lives. Evidence of this has generated increasing interest in dynamic processes in complex networks, especially the interplay between processes and the influences of network structure on performance and robustness. Performance optimization and robustness are important issues of socioeconomic networks. Diffusion is the process by which new products are invented and successfully introduced into a society (good diffusion) or infectious diseases spread (bad diffusion). Many studies shed light on how network topology interacts with the structure of social networked systems such as financial institutions to determine systemwide crises. In this context, entire classes of optimization problems range from maximizing the diffusion of innovations to minimizing risk distributions and cascade failures. The structure of interconnections influences network performance.
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50

Bianconi, Ginestra. Multilayer Networks. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.001.0001.

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Multilayer networks are formed by several networks that interact with each other and co-evolve. Multilayer networks include social networks, financial markets, transportation systems, infrastructures and molecular networks and the brain. The multilayer structure of these networks strongly affects the properties of dynamical and stochastic processes defined on them, which can display unexpected characteristics. For example, interdependencies between different networks of a multilayer structure can cause cascades of failure events that can dramatically increase the fragility of these systems; spreading of diseases, opinions and ideas might take advantage of multilayer network topology and spread even when its single layers cannot sustain an epidemic when taken in isolation; diffusion on multilayer transportation networks can significantly speed up with respect to diffusion on single layers; finally, the interplay between multiplexity and controllability of multilayer networks is a problem with major consequences in financial, transportation, molecular biology and brain networks. This field is one of the most prosperous recent developments of Network Science and Data Science. Multilayer networks include multiplex networks, multi-slice temporal networks, networks of networks, interdependent networks. Multilayer networks are characterized by having a highly correlated multilayer network structure, providing a significant advantage for extracting information from them using multilayer network measures and centralities and community detection methods. The multilayer network dynamics (including percolation, epidemic spreading, diffusion, synchronization, game theory and control) is strongly affected by the multilayer network topology. This book will present a comprehensive account of this emerging field.
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