Relevant bibliographies by topics / Network topology

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Network topology'

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

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Journal articles on the topic "Network topology"

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Hobbs, Linn W. "Network topology in aperiodic networks." Journal of Non-Crystalline Solids 192-193 (December 1995): 79–91. http://dx.doi.org/10.1016/0022-3093(95)00431-9.

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Han Zengfu, Kong Jiankun, Wang Zhiguo, Zhang Yiwei, Liu Ke, Pan Liang, Li Sicong, and Wu Desheng. "AI-based network topology optimization system." ITU Journal on Future and Evolving Technologies 2, no. 4 (August 9, 2021): 81–90. http://dx.doi.org/10.52953/yxtb5085.

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Existing network topology planning does not fully consider the increasing network traffic and problem of uneven link capacity utilization, resulting in lower resource utilization and unnecessary investments in network construction. The AI-based network topology optimization system introduced in this paper builds a Long Short-Term Memory (LSTM) model for time series traffic forecasting, which uses NetworkX, a Python library, for graph analysis, dynamically optimizes the network topology by edge deletion or addition based on traffic over nodes, and ensures network load balancing when node traffic increases, mainly introducing the LSTM forecasting model building process, parameter optimization strategy, and network topology optimization in some detail. As it effectively enhances resource utilization, this system is vital to the optimization of complex network topology. The end of this paper looks forward to the future development of artificial intelligence, and suggests the possibility of how to cooperate with operator networks and how to establish cross-border ecological development.
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Widodo, Charles, Marchellius Yana, and Halim Agung. "IMPLEMENTASI TOPOLOGI HYBRID UNTUK PENGOPTIMALAN APLIKASI EDMS PADA PROJECT OFFICE PT PHE ONWJ." JURNAL TEKNIK INFORMATIKA 11, no. 1 (May 4, 2018): 19–30. http://dx.doi.org/10.15408/jti.v11i1.6472.

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ABSTRAK Penggunaan aplikasi EDMS di project office PT PHE ONWJ dinilai masih belum optimal karena masih lambat dalam pengunaan aplikasi EDMS. Oleh karena itu dilakukanlah penelitian ini dengan tujuan untuk mengoptimalkan jaringan yang digunakan untuk mengakses aplikasi EDMS pada project office PT PHE ONWJ. Pengoptimalan jaringan yang dimaksud adalah dengan membangun topologi di project office PT PHE ONWJ dan menerapkan metro sebagai perantara topologi star di project office dan topologi star dikantor pusat sehingga menciptakan topologi hybrid. Topologi hybrid yang dimaksud adalah penggabungan antara topologi star yang ada di jaringan pusat, metro sebagai perantara kantor pusat dengan project office PT PHE ONWJ dan topologi star yang akan dibangun di project office PT ONWJ. Diharapkan setelah menerapkan topologi yang telah dirancang dapat mengoptimalkan penggunaan aplikasi EDMS. Topologi star di project office PT ONWJ dan metro sebagai perantara 2 topologi kantor pusat dan project office menghasilkan topologi hybrid. Kesimpulan dari penelitian ini adalah penerapan topologi dalam jaringan dapat memberikan optimalisasi dibandingkan dengan tanpa menerapkan topologi. Hasil rata-rata ping saat pengaksesan aplikasi EDMS sebelum menerapkan topologi hybrid mendapatkan hasil sebesar 392,98 ms dan setelah menerapkan topologi hybrid mendapatkan hasil sebesar 143,50 ms, sehingga disimpulkan bahwa penerapan topologi hybrid lebih baik dalam menjalankan aplikasi EDMS. ABSTRACT The use of EDMS application in PT PHE ONWJ project office is considered not optimal because it is still slow in the use of EDMS applications. Therefore this study was conducted with the aim to optimize the network used to access the EDMS application on the PT PHE ONWJ project office. Network optimization in question is to build a topology in the project office of PT PHE ONWJ and apply the metro as an intermediate star topology in the project office and star topology at the headquarters so as to create a hybrid topology. Hybrid topology in question is a merger between the star topology in the central network, metro as an intermediary head office with PT PHE ONWJ project office and star topology to be built at PT ONWJ project office. It is expected that after applying the topology that has been designed to optimize the use of EDMS applications. Star topology in PT ONWJ project office and metro as intermediary 2 topology headquarters and project office produce hybrid topology. The conclusion of this research is application of topology in network can give optimization compared with without applying topology. The average result of ping when accessing EDMS application before applying hybrid topology got 392.98 ms result and after applying hybrid topology get result of 143,50 ms, so it is concluded that application of hybrid topology is better in running EDMS application. How To Cite : Widodo, C. Yana, M. Agung, H. (2018). IMPLEMENTASI TOPOLOGI HYBRID UNTUK PENGOPTIMALAN APLIKASI EDMS PADA PROJECT OFFICE PT PHE ONWJ. Jurnal Teknik Informatika, 11(1), 19-30. doi 10.15408/jti.v11i1.6472 Permalink/DOI: http://dx.doi.org/10.15408/jti.v11i1.6472
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Parinyataramas, Jamreonta, Sakuntam Sanorpim, Chanchana Thanachayanont, Hiroyaki Yaguchi, and Misao Orihara. "TEM Analysis of Structural Phase Transition in MBE Grown Cubic InN on MgO (001) by MBE: Effect of Hexagonal Phase Inclusion in an C-Gan Nucleation Layer." Applied Mechanics and Materials 229-231 (November 2012): 219–22. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.219.

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In this paper, we introduced dbcube topology for Network-on Chips(NoC). We predicted the dbcube topology has high power and low latency comparing to other topologies, and in particular mesh topology. By using xmulator simulator,we compared power and latency of this topologyto mesh topology. Finally, it is demonstrated that the network has higher power and lower latency than the mesh topology.
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Mosafaie, Razieh, and Reza Sabbaghi-Nadooshan. "Using Dbcupe Topology for NoCs." Applied Mechanics and Materials 229-231 (November 2012): 2741–44. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.2741.

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In this paper, we introduced dbcube topology for Network-on Chips(NoC). We predicted the dbcube topology has high power and low latency comparing to other topologies, and in particular mesh topology. By using xmulator simulator,we compared power and latency of this topologyto mesh topology. Finally, it is demonstrated that the network has higher power and lower latency than the mesh topology.
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Kamiyama, Noriaki. "DESIGNING NETWORK TOPOLOGY USING DATA ENVELOPMENT ANALYSIS." Journal of the Operations Research Society of Japan 56, no. 3 (2013): 199–220. http://dx.doi.org/10.15807/jorsj.56.199.

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Jian, Feng, and Zhu Li. "WebNMS-Based Topology Discovery in EPON Network." International Journal of Future Generation Communication and Networking 6, no. 6 (December 31, 2013): 161–68. http://dx.doi.org/10.14257/ijfgcn.2013.6.6.17.

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Yegorova, N. V., A. V. Yakovlev, and A. G. Nikiforov. "Heating network topology." Journal of Physics: Conference Series 1683 (December 2020): 042078. http://dx.doi.org/10.1088/1742-6596/1683/4/042078.

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Fencl, T., P. Burget, and J. Bilek. "NETWORK TOPOLOGY DESIGN." IFAC Proceedings Volumes 41, no. 2 (2008): 13581–86. http://dx.doi.org/10.3182/20080706-5-kr-1001.02300.

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Fencl, Tomas, Pavel Burget, and Jan Bilek. "Network topology design." Control Engineering Practice 19, no. 11 (November 2011): 1287–96. http://dx.doi.org/10.1016/j.conengprac.2011.07.001.

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Dissertations / Theses on the topic "Network topology"

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Oliveira, Olga Margarida Fajarda. "Network topology discovery." Doctoral thesis, Universidade de Aveiro, 2017. http://hdl.handle.net/10773/18692.

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Doutoramento em Matemática
A monitorização e avaliação do desempenho de uma rede são essenciais para detetar e resolver falhas no seu funcionamento. De modo a conseguir efetuar essa monitorização, e essencial conhecer a topologia da rede, que muitas vezes e desconhecida. Muitas das técnicas usadas para a descoberta da topologia requerem a cooperação de todos os dispositivos de rede, o que devido a questões e políticas de segurança e quase impossível de acontecer. Torna-se assim necessário utilizar técnicas que recolham, passivamente e sem a cooperação de dispositivos intermédios, informação que permita a inferência da topologia da rede. Isto pode ser feito recorrendo a técnicas de tomografia, que usam medições extremo-a-extremo, tais como o atraso sofrido pelos pacotes. Nesta tese usamos métodos de programação linear inteira para resolver o problema de inferir uma topologia de rede usando apenas medições extremo-a-extremo. Apresentamos duas formulações compactas de programação linear inteira mista (MILP) para resolver o problema. Resultados computacionais mostraram que a medida que o número de dispositivos terminais cresce, o tempo que as duas formulações MILP compactas necessitam para resolver o problema, também cresce rapidamente. Consequentemente, elaborámos duas heurísticas com base nos métodos Feasibility Pump e Local ranching. Uma vez que as medidas de atraso têm erros associados, desenvolvemos duas abordagens robustas, um para controlar o número máximo de desvios e outra para reduzir o risco de custo alto. Criámos ainda um sistema que mede os atrasos de pacotes entre computadores de uma rede e apresenta a topologia dessa rede.
Monitoring and evaluating the performance of a network is essential to detect and resolve network failures. In order to achieve this monitoring level, it is essential to know the topology of the network which is often unknown. Many of the techniques used to discover the topology require the cooperation of all network devices, which is almost impossible due to security and policy issues. It is therefore, necessary to use techniques that collect, passively and without the cooperation of intermediate devices, the necessary information to allow the inference of the network topology. This can be done using tomography techniques, which use end-to-end measurements, such as the packet delays. In this thesis, we used some integer linear programming theory and methods to solve the problem of inferring a network topology using only end-to-end measurements. We present two compact mixed integer linear programming (MILP) formulations to solve the problem. Computational results showed that as the number of end-devices grows, the time need by the two compact MILP formulations to solve the problem also grows rapidly. Therefore, we elaborate two heuristics based on the Feasibility Pump and Local Branching method. Since the packet delay measurements have some errors associated, we developed two robust approaches, one to control the maximum number of deviations and the other to reduce the risk of high cost. We also created a system that measures the packet delays between computers on a network and displays the topology of that network.
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Norangshol, Roy Sindre. "Open network topology services." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-23100.

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This master project examines whether there is an existing model fordescribing network topologies in abstract and generic manner. I alsolooked for networking protocols for exchanging network topologiesand handling of dynamically creation of circuit connections acrossdomains. I?ve also been working on a prototype for visualization ofnetwork topologies using Network Administration Visualized (NAV)as a data backend, and further to check the possibilities to use thefound topology model in my prototype.My findings shows that there is progress towards creating a stan-dard topology model to describe network topologies in an abstractand generic manner. There is also progress in creating a network ar-chitecture with networking protocols for exchanging network topolo-gies across domains and providing a connection reservation service tohandle creation of dynamically circuit connections. Prototype showsthere is lots of ideas for further works on what to implement in re-gards of the found network topology model and networking systemsthat was found.
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Gu, Yuwei Ph D. Massachusetts Institute of Technology. "Controlling polymer network topology." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122851.

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Thesis: Ph. D. in Organic Chemistry, Massachusetts Institute of Technology, Department of Chemistry, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references.
Chapter 1: Introduction to Polymer Network Topology on a (Macro)Molecular Level Polymer network topology, comprising the ways in which strands and junctions are connected in polymer networks, plays a critical role in dictating many material properties. Here we discuss classical challenges in the field and review existing strategies to characterize and manipulate polymer network topology from a (macro)molecular level. Chapter 2: Semibatch Monomer Addition as a General Method to Tune and Enhance the Mechanics of Polymer Networks via Loop-defect Control In this chapter we introduce semibatch monomer addition as a general strategy to reduce/control an important topological feature at short length scale-primary loops, thus providing materials with tunable and significantly improved mechanical properties without changing their composition.
Chapter 3: Leaving Groups as Traceless Topological Modifiers for Controlling Topological Structure in Chemically Identical Polymer Networks Here we report "traceless topological modification" as a general approach to control an important long length-scale topological feature-junction distribution. Using self-assembled structures as templates that are not themselves incorporated into the network, our method enables us to synthesize truly topologically isomeric networks with drastically different macroscopic properties. Chapter 4: Photoswitching Topology in Polymer Networks with Metal-Organic Cages as Crosslinks Based on our works in Chapter 2 and Chapter 3, we further explored topology as the central design principle to create novel functional materials.
In this chapter we introduce topology switching via cooperative self-assembly as a design principle to reversibly alter multiple network properties simultaneously and enable the preparation of one material that can exist in multiple topological states. Chapter 5: Living Additive Manufacturing: Transformation of Parent Gels into Diversely Functionalized Daughter Gels Made Possible by Visible Light Photoredox Catalysis Our ability to control polymer network topology has been further enhanced by developing living additive manufacturing as an effective strategy to expand the original topology of parent networks in a photo-growth fashion. This approach enables us to transform the mechanical/physical properties of parent networks post-synthetically.
Chapter 6: polyMOF Nanoparticles: Dual Roles of a Multivalent polyMOF Ligand in Size Control and Surface Functionalization Here we present a novel approach to synthesizing well defined metal-organic framework nanoparticles (MOF NPs), where the size control and surface functionalization of MOF-5 NPs were simultaneously achieved using multivalent polyMOF ligands.
by Yuwei Gu.
Ph. D. in Organic Chemistry
Ph.D.inOrganicChemistry Massachusetts Institute of Technology, Department of Chemistry
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Fard, Pedram J. "Dynamic reconfiguration of network topology in optical networks." College Park, Md. : University of Maryland, 2007. http://hdl.handle.net/1903/7412.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2007.
Thesis research directed by: Electrical Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Yao, Ye. "Ad Hoc Networks Measurement Model and Methods Based on Network Tomography." Phd thesis, Université de Technologie de Belfort-Montbeliard, 2011. http://tel.archives-ouvertes.fr/tel-00636282.

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The measurability of Mobile ad hoc network (MANET) is the precondition of itsmanagement, performance optimization and network resources re-allocations. However, MANET is an infrastructure-free, multi-hop, andself-organized temporary network, comprised of a group of mobile nodes with wirelesscommunication devices. Not only does its topology structure vary with time going by, butalso the communication protocol used in its network layer or data link layer is diverse andnon-standard.In order to solve the problem of interior links performance (such as packet loss rate anddelay) measurement in MANET, this thesis has adopted an external measurement basedon network tomography (NT). To the best of our knowledge, NT technique is adaptable for Ad Hoc networkmeasurement.This thesis has deeply studied MANET measurement technique based on NT. The maincontributions are:(1) An analysis technique on MANET topology dynamic characteristic based onmobility model was proposed. At first, an Ad Hoc network mobility model formalizationis described. Then a MANET topology snapshots capturing method was proposed to findand verify that MANET topology varies in steady and non-steady state in turnperiodically. At the same time, it was proved that it was practicable in theory to introduceNT technique into Ad Hoc network measurement. The fitness hypothesis verification wasadopted to obtain the rule of Ad Hoc network topology dynamic characteristic parameters,and the Markov stochastic process was adopted to analyze MANET topology dynamiccharacteristic. The simulation results show that the method above not only is valid andgenerable to be used for all mobility models in NS-2 Tool, but also could obtain thetopology state keeping experimental formula and topology state varying probabilityformula.IV(2) An analysis technique for MANET topology dynamic characteristic based onmeasurement sample was proposed. When the scenario file of mobile models could notbe obtained beforehand, End-to-End measurement was used in MANET to obtain thepath delay time. Then topology steady period of MANET is inferred by judging whetherpath delay dithering is close to zero. At the same time, the MANET topology wasidentified by using hierarchical clustering method based on measurement sample of pathperformance during topology steady period in order to support the link performanceinference. The simulation result verified that the method above could not only detect themeasurement window time of MANET effectively, but also identify the MANETtopology architecture during measurement window time correctly.(3) A MANET link performance inference algorithm based on linear analysis modelwas proposed. The relation of inequality between link and path performance, such as lossrate of MANET, was deduced according to a linear model. The phenomena thatcommunication characteristic of packets, such as delay and loss rate, is more similarwhen the sub-paths has longer shared links was proved in the document. When the rankof the routing matrix is equal to that of its augmentation matrix, the linear model wasused to describe the Ad Hoc network link performance inference method. The simulationresults show that the algorithm not only is effective, but also has short computing time.(4) A Link performance inference algorithm based on multi-objectives optimizationwas proposed. When the rank of the routing matrix is not equal to that of its augmentationmatrix, the link performance inference was changed into multi-objectives optimizationand genetic algorithm is used to infer link performance. The probability distribution oflink performance in certain time t was obtained by performing more measurements andstatistically analyzing the hypo-solutions. Through the simulation, it can be safelyconcluded that the internal link performance, such as, link loss ratio and link delay, can beinferred correctly when the rank of the routing matrix is not equal to that of itsaugmentation matrix.
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Pfennig, Stefan, and Elke Franz. "Secure Network Coding: Dependency of Efficiency on Network Topology." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-128456.

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Network Coding is a new possibility to transmit data through a network. By combining different packets instead of simply forwarding, network coding offers the opportunity to reach the Min-Cut/Max-Flow capacity in multicast data transmissions. However, the basic schemes are vulnerable to so-called pollution attacks, where an attacker can jam large parts of the transmission by infiltrating only one bogus message. In the literature we found several approaches which aim at handling this kind of attack with different amounts of overhead. Though, the cost for a specific secure network coding scheme highly depends on the underlying network. The goal of this paper is on the one hand to describe which network parameters influence the efficiency of a certain scheme and on the other hand to provide concrete suggestions for selecting the most efficient secure network coding scheme considering a given network. We will illustrate that there does not exist “the best” secure network scheme concerning efficiency, but all selected schemes are more or less suited under certain network topologies.
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Khorramzadeh, Yasamin. "Network Reliability: Theory, Estimation, and Applications." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/64383.

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Network reliability is the probabilistic measure that determines whether a network remains functional when its elements fail at random. Definition of functionality varies depending on the problem of interest, thus network reliability has much potential as a unifying framework to study a broad range of problems arising in complex network contexts. However, since its introduction in the 1950's, network reliability has remained more of an interesting theoretical construct than a practical tool. In large part, this is due to well-established complexity costs for both its evaluation and approximation, which has led to the classification of network reliability as a NP-Hard problem. In this dissertation we present an algorithm to estimate network reliability and then utilize it to evaluate the reliability of large networks under various descriptions of functionality. The primary goal of this dissertation is to pose network reliability as a general scheme that provides a practical and efficiently computable observable to distinguish different networks. Employing this concept, we are able to demonstrate how local structural changes can impose global consequences. We further use network reliability to assess the most critical network entities which ensure a network's reliability. We investigate each of these aspects of reliability by demonstrating some example applications.
Ph. D.
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Jin, Xing. "Topology inference and tree construction for topology-aware overlay streaming /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?CSED%202007%20JIN.

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Long, Weili. "On the topology design of hose-model VPN networks /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?ECED%202008%20LONG.

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Deccio, Casey T. "Network-layer Selective Security." Diss., CLICK HERE for online access, 2004. http://contentdm.lib.byu.edu/ETD/image/etd560.pdf.

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Books on the topic "Network topology"

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

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

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

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

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

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

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

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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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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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Book chapters on the topic "Network topology"

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Hoffmann, Frank, and Michael Fröba. "Network Topology." In The Chemistry of Metal-Organic Frameworks: Synthesis, Characterization, and Applications, 5–40. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2016. http://dx.doi.org/10.1002/9783527693078.ch2.

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Smith, Andrew Bruce. "Network Topology." In Share This Too, 287–94. Hoboken, NJ, USA: John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781119207993.ch32.

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Weik, Martin H. "network topology." In Computer Science and Communications Dictionary, 1091. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_12281.

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Kolaczyk, Eric D., and Gábor Csárdi. "Network Topology Inference." In Use R!, 115–40. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44129-6_7.

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Jin, Guangxu. "Network Topology Motif." In Encyclopedia of Systems Biology, 1523–24. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_590.

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Monticelli, A. "Network Topology Processing." In State Estimation in Electric Power Systems, 143–59. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4999-4_6.

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Kolaczyk, Eric D., and Gábor Csárdi. "Network Topology Inference." In Use R!, 111–34. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0983-4_7.

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Kolaczyk, Eric D. "Network Topology Inference." In Springer Series in Statistics, 1–48. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-88146-1_7.

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Paul, Andreas, Franka Schuster, and Hartmut König. "Network Topology Exploration for Industrial Networks." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 62–76. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52569-3_6.

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Korzun, Dmitry, and Andrei Gurtov. "Adaptable Overlay Network Topology." In Structured Peer-to-Peer Systems, 87–109. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5483-0_4.

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Conference papers on the topic "Network topology"

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Christiansen, Eric M., Mohammad F. Hadi, and Victor H. Barocas. "Relating Network Topology to Network Mechanics." In ASME 2012 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/sbc2012-80684.

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Soft tissues are comprised of underlying fiber networks of collagen and other fibrous proteins and biopolymers. Thus, the ability to model the deformation of fiber networks is critical to understanding the mechanics of tissues in vivo and in vitro [1]. Complicating the issue, protein fiber networks are comprised of a range of different topologies that behave differently under load. There is a clear need for a method to derive network parameters that characterize the network and allow for the prediction of their behavior. In this study, we characterized several different random fiber network types based on their intrinsic mechanical and topological properties. Such characterization would improve our ability to select microscale network topologies that match the mechanical properties we observe in healthy and diseased native tissues [2]. It would also improve our ability to discern the outcome of microstructural changes in tissues (such as from remodeling or injury) on their overall mechanics.
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Yang, Liang, Zesheng Kang, Xiaochun Cao, Di Jin, Bo Yang, and Yuanfang Guo. "Topology Optimization based Graph Convolutional Network." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/563.

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In the past few years, semi-supervised node classification in attributed network has been developed rapidly. Inspired by the success of deep learning, researchers adopt the convolutional neural network to develop the Graph Convolutional Networks (GCN), and they have achieved surprising classification accuracy by considering the topological information and employing the fully connected network (FCN). However, the given network topology may also induce a performance degradation if it is directly employed in classification, because it may possess high sparsity and certain noises. Besides, the lack of learnable filters in GCN also limits the performance. In this paper, we propose a novel Topology Optimization based Graph Convolutional Networks (TO-GCN) to fully utilize the potential information by jointly refining the network topology and learning the parameters of the FCN. According to our derivations, TO-GCN is more flexible than GCN, in which the filters are fixed and only the classifier can be updated during the learning process. Extensive experiments on real attributed networks demonstrate the superiority of the proposed TO-GCN against the state-of-the-art approaches.
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Tangmunarunkit, Hongsuda, Ramesh Govindan, Sugih Jamin, Scott Shenker, and Walter Willinger. "Network topology generators." In the 2002 conference. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/633025.633040.

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Zhang, Yu, Yuanda Cao, and Baodong Cheng. "A Layered P2P Network Topology Based on Physical Network Topology." In 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2008. http://dx.doi.org/10.1109/wicom.2008.1010.

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Kamiyama, Noriaki. "Network Topology Design with Multiple Criteria." In Networks 2006. 12th International Telecommunications Network Strategy and Planning Symposium. IEEE, 2006. http://dx.doi.org/10.1109/netwks.2006.300406.

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Mao, Yanbing, and Emrah Akyol. "On Network Topology Inference of Social Networks." In 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2019. http://dx.doi.org/10.1109/allerton.2019.8919870.

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"A Clustering Topology for Wireless Sensor Networks - New Semantics over Network Topology." In 2nd International Conference on Data Management Technologies and Applications. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004423101530160.

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Segarra, Santiago, Antonio G. Marques, Gonzalo Mateos, and Alejandro Ribeiro. "Robust network topology inference." In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2017. http://dx.doi.org/10.1109/icassp.2017.7953412.

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Baleski, Ljupcho, Dragi Kimovski, and Ninoslav Marina. "Hexagon interconnection network topology." In 2015 7th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). IEEE, 2015. http://dx.doi.org/10.1109/icumt.2015.7382439.

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Hadi, Mohammad F., and Victor H. Barocas. "Generating Random Fiber Network Topologies That Mimic Previously Characterized Networks." In ASME 2013 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/sbc2013-14615.

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Fibrous proteins, such as collagen and elastin, form the underlying structure of many soft tissues. These proteins form micrometer-scale networks of varying topology that play a role in governing the mechanics of tissues at larger length scales [1]. The relationship between a network’s topology and its mechanics, however, are poorly understood. This disconnect presents an important challenge in constructing realistic multiscale models of tissues informed by collagen network micrographs and subsequently reconstructed networks [2]. Accurate multiscale simulations may require thousands to millions of such unique networks. It is imperative that a method be developed to generate random networks that are functionally similar to ones derived experimentally. In the current study, we present a probabilistic method for generating de novo networks that mimic the mechanical properties of previously characterized networks. We chose Delaunay and Voronoi networks as model targets because they have been used successfully to model the mechanics of collagenous tissues [3] and since their topologies are well characterized. Understanding the role of topology in network mechanics is fundamental to building improved models of the mechanics of fibrous soft tissues — models that can aid in the rational design of engineered tissues or that can help assess the mechanical impact of damage or disease on native tissues.
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Reports on the topic "Network topology"

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Kalb, Jeffrey L., and David S. Lee. Network topology analysis. Office of Scientific and Technical Information (OSTI), January 2008. http://dx.doi.org/10.2172/1028919.

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Olson, Jamie, and Kathleen M. Carley. Visualizing Spatial Dependencies in Network Topology. Fort Belvoir, VA: Defense Technical Information Center, July 2010. http://dx.doi.org/10.21236/ada525370.

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Frantz, Terrill L., and Kathleen M. Carley. Relating Network Topology to the Robustness of Centrality Measures. Fort Belvoir, VA: Defense Technical Information Center, May 2005. http://dx.doi.org/10.21236/ada456108.

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Lemon, T., and T. Mrugalski. Customizing DHCP Configuration on the Basis of Network Topology. RFC Editor, October 2016. http://dx.doi.org/10.17487/rfc7969.

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Nguyen, Binh Q. A Tool for Visualizing Mobile Ad-Hoc Network Topology Definitions Files. Fort Belvoir, VA: Defense Technical Information Center, February 2006. http://dx.doi.org/10.21236/ada444158.

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Wilson, C. L., and O. M. Omidvar. Optimization of neural network topology and information content using Boltzmann methods. Gaithersburg, MD: National Institute of Standards and Technology, 1992. http://dx.doi.org/10.6028/nist.ir.4766.

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Henderson, Thomas R., Kyle Bae, Jin Fang, and David M. Kushi. Integrated Autonomous Network Management (IANM) Multi-Topology Route Manager and Analyzer. Fort Belvoir, VA: Defense Technical Information Center, February 2008. http://dx.doi.org/10.21236/ada476793.

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Diebold, Francis, and Kamil Yilmaz. On the Network Topology of Variance Decompositions: Measuring the Connectedness of Financial Firms. Cambridge, MA: National Bureau of Economic Research, October 2011. http://dx.doi.org/10.3386/w17490.

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Bednar, Amy. Topological data analysis : an overview. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/40943.

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A growing area of mathematics topological data analysis (TDA) uses fundamental concepts of topology to analyze complex, high-dimensional data. A topological network represents the data, and the TDA uses the network to analyze the shape of the data and identify features in the network that correspond to patterns in the data. These patterns extract knowledge from the data. TDA provides a framework to advance machine learning’s ability to understand and analyze large, complex data. This paper provides background information about TDA, TDA applications for large data sets, and details related to the investigation and implementation of existing tools and environments.
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Соловйов, В. М., and О. С. Лук’янчук. Фолксономія соціально-економічних об’єктів в складних мережах засобами CorrRank. Брама-Україна, 2014. http://dx.doi.org/10.31812/0564/1307.

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The financial and economic crisis 2007-2009 shown that economic institutions are closely linked and the behavior of complex systems is difficult predictable. There is an urgent need to develop new quantitative methods that adequately describe the dynamic changes in complex systems during normal conditions and during the crisis. There is a need for methods that describe the topology of the interaction between economic institutions, using the tools developed in the theory of networks. The paper used a method of investigation of nonlinear dynamics, as the random matrices theory, which when combined with network methods are adequate means for the study of complex systems. The given technique we have implemented the study in the real time series of global stock markets.
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