Relevant bibliographies by topics / Topology Control

Contents

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

Academic literature on the topic 'Topology Control'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Topology Control"

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HAN, Shuang-xia, Yi-ming FAN, Lu ZHANG, and Fu-rong LUO. "Three-layer topology architecture and topology control algorithm." Journal of Computer Applications 29, no. 6 (August 5, 2009): 1523–26. http://dx.doi.org/10.3724/sp.j.1087.2009.01523.

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Christensen, René Depont, and Hans Jørgen Munkholm. "Topology with monoidal control." Homology, Homotopy and Applications 4, no. 1 (2002): 213–34. http://dx.doi.org/10.4310/hha.2002.v4.n1.a12.

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Osborne, Ian S. "Nonlinear control of topology." Science 372, no. 6537 (April 1, 2021): 43.18–45. http://dx.doi.org/10.1126/science.372.6537.43-r.

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Lorenzo, Beatriz, and Savo Glisic. "Traffic adaptive relaying topology control." IEEE Transactions on Wireless Communications 8, no. 11 (November 2009): 5612–20. http://dx.doi.org/10.1109/twc.2009.081613.

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Liu, Ren Ping, Glynn Rogers, Sihui Zhou, and John Zic. "Topology control with Hexagonal Tessellation." International Journal of Sensor Networks 2, no. 1/2 (2007): 91. http://dx.doi.org/10.1504/ijsnet.2007.012987.

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Tereshchenko, T. О., Y. S. Yamnenko, D. V. Kuzin, and L. E. Klepach. "MULTILEVEL INVERTER TOPOLOGY AND CONTROL SIGNALS DEFINITION BASED ON ORTHOGONAL SPECTRAL TRANSFORMATIONS." Tekhnichna Elektrodynamika 2018, no. 4 (May 15, 2018): 57–60. http://dx.doi.org/10.15407/techned2018.04.057.

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M.S, Brindha. "A Survey on Cross Layer Distributed Topology Control in Mobile Adhoc Network." Bonfring International Journal of Networking Technologies and Applications 04, no. 01 (October 31, 2017): 01–03. http://dx.doi.org/10.9756/bijnta.8346.

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Karunakaran. "Topology Control Using Efficient Power Management." Journal of Computer Science 7, no. 4 (April 1, 2011): 561–67. http://dx.doi.org/10.3844/jcssp.2011.561.567.

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Escobedo, Adolfo R., Erick Moreno-Centeno, and Kory W. Hedman. "Topology Control for Load Shed Recovery." IEEE Transactions on Power Systems 29, no. 2 (March 2014): 908–16. http://dx.doi.org/10.1109/tpwrs.2013.2286009.

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Neumann, Florentin, and Hannes Frey. "Foundation of Reactive Local Topology Control." IEEE Communications Letters 19, no. 7 (July 2015): 1213–16. http://dx.doi.org/10.1109/lcomm.2015.2432019.

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Dissertations / Theses on the topic "Topology Control"

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Vanderhyde, James. "Topology Control of Volumetric Data." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/16215.

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Three-dimensional scans and other volumetric data sources often result in representations that are more complex topologically than the original model. The extraneous critical points, handles, and components are called topological noise. Many algorithms in computer graphics require simple topology in order to work optimally, including texture mapping, surface parameterization, flows on surfaces, and conformal mappings. The topological noise disrupts these procedures by requiring each small handle to be dealt with individually. Furthermore, topological descriptions of volumetric data are useful for visualization and data queries. One such description is the contour tree (or Reeb graph), which depicts when the isosurfaces split and merge as the isovalue changes. In the presence of topological noise, the contour tree can be too large to be useful. For these reasons, an important goal in computer graphics is simplification of the topology of volumetric data. The key to this thesis is that the global topology of volumetric data sets is determined by local changes at individual points. Therefore, we march through the data one grid cell at a time, and for each cell, we use a local check to determine if the topology of an isosurface is changing. If so, we change the value of the cell so that the topology change is prevented. In this thesis we describe variations on the local topology check for use in different settings. We use the topology simplification procedure to extract a single component with controlled topology from an isosurface in volume data sets and partially-defined volume data sets. We also use it to remove critical points from three-dimensional volumes, as well as time-varying volumes. We have applied the technique to two-dimensional (plus time) data sets and three dimensional (plus time) data sets.
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Barnett, Adam. "Topology based global crowd control." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/9692.

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We propose a method to determine the flow of large crowds of agents in a scene such that it is filled to its capacity with a coordinated, dynamically moving crowd. Our approach provides a focus on cooperative control across the entire crowd. This is done with a view to providing a method which animators can use to easily populate and fill a scene. We solve this global planning problem by first finding the topology of the scene using a Reeb graph, which is computed from a Harmonic field of the environment. The Maximum flow can then be calculated across this graph detailing how the agents should move through the space. This information is converted back from the topological level to the geometric using a route planner and the Harmonic field. We provide evidence of the system’s effectiveness in creating dynamic motion through comparison to a recent method. We also demonstrate how this system allows the crowd to be controlled globally with a couple of simple intuitive controls and how it can be useful for the purpose of designing buildings and providing control in team sports.
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Komali, Ramakant S. "Game-Theoretic Analysis of Topology Control." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/28358.

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Ad hoc networks are emerging as a cost-effective, yet, powerful tool for communication. These systems, where networks can emerge and converge on-the-fly, are guided by the forward-looking goals of providing ubiquitous connectivity and constant access to information. Due to power and bandwidth constraints, the vulnerability of the wireless medium, and the multi-hop nature of ad hoc networks, these networks are becoming increasingly complex dynamic systems. Besides, modern radios are empowered to be reconfigurable, which harbors the temptation to exploit the system. To understand the implications of these issues, some of which pose significant challenges to efficient network design, we study topology control using game theory. We develop a game-theoretic framework of topology control that broadly captures the radio parameters, one or more of which can be tuned under the purview of topology control. In this dissertation, we consider two parameters, viz. transmit power and channel, and study the impact of controlling these on the emergent topologies. We first examine the impact of node selfishness on the network connectivity and energy efficiency under two levels of selfishness: (a) nodes cooperate and forward packets for one another, but selfishly minimize transmit power levels and; (b) nodes selectively forward packets and selfishly control transmit powers. In the former case, we characterize all the Nash Equilibria of the game and evaluate the energy efficiency of the induced topologies. We develop a better-response-based dynamic that guarantees convergence to the minimal maximum power topology. We extend our analysis to dynamic networks where nodes have limited knowledge about network connectivity, and examine the tradeoff between network performance and the cost of obtaining knowledge. Due to the high cost of maintaining knowledge in networks that are dynamic, mobility actually helps in information-constrained networks. In the latter case, nodes selfishly adapt their transmit powers to minimize their energy consumption, taking into account partial packet forwarding in the network. This work quantifies the energy efficiency gains obtained by cooperation and corroborates the need for incentivizing nodes to forward packets in decentralized, energy-limited networks. We then examine the impact of selfish behavior on spectral efficiency and interference minimization in multi-channel systems. We develop a distributed channel assignment algorithm to minimize the spectral footprint of a network while establishing an interference-free connected network. In spite of selfish channel selections, the network spectrum utilization is shown to be within 12% of the minimum on average. We then extend the analysis to dynamic networks where nodes have incomplete network state knowledge, and quantify the price of ignorance. Under the limitations on the number of available channels and radio interfaces, we analyze the channel assignment game with respect to interference minimization and network connectivity goals. By quantifying the interference in multi-channel networks, we illuminate the interference reduction that can be achieved by utilizing orthogonal channels and by distributing interference over multiple channels. In spite of the non-cooperative behavior of nodes, we observe that the selfish channel selection algorithm achieves load balancing. Distributing the network control to autonomous agents leaves open the possibility that nodes can act selfishly and the overall system is compromised. We advance the need for considering selfish behavior from the outset, during protocol design. To overcome the effects of selfishness, we show that the performance of a non-cooperative network can be enhanced by appropriately incentivizing selfish nodes.
Ph. D.
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Wightman, Rojas Pedro Mario. "Topology Control in Wireless Sensor Networks." Scholar Commons, 2010. https://scholarcommons.usf.edu/etd/1807.

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Wireless Sensor Networks (WSN) offer a flexible low-cost solution to the problem of event monitoring, especially in places with limited accessibility or that represent danger to humans. WSNs are made of resource-constrained wireless devices, which require energy efficient mechanisms, algorithms and protocols. One of these mechanisms is Topology Control (TC) composed of two mechanisms, Topology Construction and Topology Maintenance. This dissertation expands the knowledge of TC in many ways. First, it introduces a comprehensive taxonomy for topology construction and maintenance algorithms for the first time. Second, it includes four new topology construction protocols: A3, A3Lite, A3Cov and A3LiteCov. These protocols reduce the number of active nodes by building a Connected Dominating Set (CDS) and then turning off unnecessary nodes. The A3 and A3-Lite protocols guarantee a connected reduced structure in a very energy efficient manner. The A3Cov and A3LiteCov protocols are extensions of their predecessors that increase the sensing coverage of the network. All these protocols are distributed -they do not require localization information, and present low message and computational complexity. Third, this dissertation also includes and evaluates the performance of four topology maintenance protocols: Recreation (DGTRec), Rotation (SGTRot), Rotation and Recreation (HGTRotRec), and Dynamic Local-DSR (DLDSR). Finally, an event-driven simulation tool named Atarraya was developed for teaching, researching and evaluating topology control protocols, which fills a need in the area of topology control that other simulators cannot. Atarraya was used to implement all the topology construction and maintenance cited, and to evaluate their performance. The results show that A3Lite produces a similar number of active nodes when compared to A3, while spending less energy due to its lower message complexity. A3Cov and A3CovLite show better or similar coverage than the other distributed protocols discussed here, while preserving the connectivity and energy efficiency from A3 and A3Lite. In terms of network lifetime, depending on the scenarios, it is shown that there can be a substantial increase in the network lifetime of 450% when a topology construction method is applied, and of 3200% when both topology construction and maintenance are applied, compared to the case where no topology control is used.
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Li, Xiaoyun. "Distributed topology-aware algorithms & topology control probabilistic analysis for wireless sensor networks." Thesis, University of Essex, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.446490.

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Zhao, Liang. "Topology control for mobile ad hoc networks." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 162 p, 2007. http://proquest.umi.com/pqdweb?did=1362541141&sid=26&Fmt=2&clientId=8331&RQT=309&VName=PQD.

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Hassan, Ahmed Mohamed Ali Omer. "Topology control in wireless ad hoc networks." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86709.

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Thesis (MSc)--Stellenbosch University, 2014.
ENGLISH ABSTRACT: Wireless ad hoc networks are increasingly used in today’s life in various areas ranging from environmental monitoring to the military. For technical reasons, they are severely limited in terms of battery power, communication capacity and computation capability. Research has been carried out to deal with these limitations using different approaches. A theoretical treatment of the subject is topology control whose basic task is to design network topologies with special properties that make them energy-efficient and interference-optimal. We study, implement and compare the XTC and CBTC algorithms in terms of interference reduction, length stretch factor and maximum degree. These two algorithms have two features that are absent in almost all competitive topology control algorithms which are practicality and maintaining connectivity. Both algorithms show good performance in terms of interference reduction and maintaining a good length stretch factor. Regarding CBTC, we prove that it is a power spanner. We show through extensive simulation that the degree distribution of wireless ad hoc networks modelled by the log-normal model is binomial if the average degree is not high. We find that there is no fixed threshold for the average degree at which the distribution is distorted and no longer binomial. We show through simulation that the node density which ensures the absence of isolated nodes is a tight lower bound for the node density which ensures connectivity. The implication of this result is that connectivity is ensured with high probability if the minimum node degree is equal to 1. Finally we show through simulation that the log-normal model is not a realistic representation of wireless ad hoc networks if the environmental parameter is at least 6. This result is important because there are no available measurements to determine the range of the environmental parameter for typical frequencies used in wireless ad hoc networks.
AFRIKAANSE OPSOMMING: Koordlose ad hoc netwerke word toenemend gebruik in vandag se lewe op verskillende gebiede wat wissel van die omgewing monitor tot militêregebruik. Vir tegniese redes is hulle ernstig beperk in terme van battery krag, kommunikasie kapasiteit en berekeningsvermoë. Navorsing vanuit verkillende benaderings word gedoen om met hierdie beperkings te deel. ’n Teoretiese benadering tot onderwerp is topologie beheer. Die basiese taak is om netwerktopologieë met spesiale eienskappe wat hulle energie-doeltreffend en interferensieoptimaal maak te ontwerp. Ons bestudeer, implementeer en vergelyk die XTC en CBTC algoritmes in terme van interferensie vermindering, lengte rek faktor en maksimum graad. Beide hierdie algoritmes het twee eienskappe wat afwesig is in byna al die mededingende topologie beheer algoritmes: hulle is prakties en handhaf verbindings. Beide algoritmes toon goeie prestasie in terme van interferensie verminder en die handhawing van ’n goeie lengte rek faktor. Ten opsigte van CBTC bewys ons dat dit ’n “power spanner” is. Ons wys deur middel van uitgebreide simulasie dat die graad verdeling van die koordlose ad hoc netwerke wat deur die log-normale model gemodelleer kan word binomiaal is as die gemiddelde graad nie hoog is nie. Ons vind dat daar geen vaste drempel is vir die gemiddelde graad waarby die verdeling vervorm en nie meer binomiaal is nie. Ons wys deur simulasie dat die node digtheid wat die afwesigheid van geïsoleerde nodusse verseker ’n streng ondergrens vir die node digtheid wat konnektiviteit verseker is. Die implikasie van hierdie resultaat is dat ‘n konneksie verseker word as die minimum node graad gelyk is aan 1. Ten slotte wys ons deur simulasie dat die log-normale model nie ’n realistiese voorstelling van koordlose ad hoc netwerke is wanneer die “environmental parameter” groter is as 6 nie. Hierdie resultaat is belangrik, want daar is geen beskikbare metings om die grense van hierdie parameter vir ’n tipiese frekwensie gebruik in koordlose ad hoc netwerke te bepaal nie.
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Liu, Yunhuai. "Probabilistic topology control in wireless sensor networks /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?CSED%202008%20LIU.

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Javali, Nagesh. "Topology control for wireless ad-hoc networks." Click here for download, 2008. http://proquest.umi.com/pqdweb?did=1580780361&sid=1&Fmt=2&clientId=3260&RQT=309&VName=PQD.

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Thesis (M.S.)--Villanova University, 2008.
"This research work is funded in part by National Science Foundation (NSF), Computing and Communication Foundation (CCF) award 0728909"--P. iii. Computer Science Dept. Includes bibliographical references.
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Volbert, Klaus. "Geometric spanners for topology control in wireless networks." [S.l. : s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=97580975X.

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Books on the topic "Topology Control"

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Jonckheere, Edmond A. Algebraic and differential topology of robust stability. New York: Oxford University Press, 1997.

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

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

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Robust stabilization in the gap-topology. Berlin: Springer-Verlag, 1991.

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

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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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Piecewise linear control systems: A computational approach. Berlin: Springer, 2003.

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T, Ivancevic Tijana, ed. Complex nonlinearity: Chaos, phase transitions, topology change, and path integrals. Berlin: Springer, 2008.

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V, Gamkrelidze R., ed. Selected research papers. New York: Gordon and Breach Science Publishers, 1986.

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Book chapters on the topic "Topology Control"

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Erciyes, K. "Topology Control." In Computer Communications and Networks, 229–57. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5173-9_15.

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Ghosh, Sukumar, Kevin Lillis, Saurav Pandit, and Sriram Pemmaraju. "Robust Topology Control Protocols." In Lecture Notes in Computer Science, 94–109. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11516798_7.

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Piechowiak, Maciej, and Piotr Zwierzykowski. "Topology Properties of Ad-Hoc Networks with Topology Control." In Computer Networks, 89–98. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07941-7_9.

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Fabian Garcia Nocetti, D., and Peter J. Fleming. "Performance Issues: Granularity, Topology, Mapping Strategies." In Parallel Processing in Digital Control, 91–131. London: Springer London, 1992. http://dx.doi.org/10.1007/978-1-4471-1945-6_5.

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Tiwari, Ravi Shankar. "HVDC Transmission Topology and Control Analysis." In Lecture Notes in Electrical Engineering, 171–80. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7994-3_15.

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Wang, Yu. "Topology Control for Wireless Sensor Networks." In Wireless Sensor Networks and Applications, 113–47. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-49592-7_5.

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Lillis, Kevin, and Sriram V. Pemmaraju. "Topology Control with Limited Geometric Information." In Lecture Notes in Computer Science, 427–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11795490_32.

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Lou, Tiancheng, Haisheng Tan, Yuexuan Wang, and Francis C. M. Lau. "Minimizing Average Interference through Topology Control." In Algorithms for Sensor Systems, 115–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28209-6_10.

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Haslinger, Jaroslav. "Imbedding/Control Approach for Solving Optimal Shape Design Problems." In Topology Design of Structures, 303–6. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1804-0_20.

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Tolić, Domagoj, and Sandra Hirche. "Topology-Triggering of Multi-Agent Systems." In Networked Control Systems with Intermittent Feedback, 145–76. Boca Raton : Taylor & Francis, CRC Press, 2017. |: CRC Press, 2017. http://dx.doi.org/10.1201/9781315367934-8.

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Conference papers on the topic "Topology Control"

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Pan, Yang, and Feng Gao. "Mechanism topology design for novel parallel-parallel hexapod robot." In 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915231.

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Moscibroda, Thomas, Roger Wattenhofer, and Aaron Zollinger. "Topology control meets SINR:." In the seventh ACM international symposium. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1132905.1132939.

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Meyer, David G. "On The Graph Topology." In 1989 American Control Conference. IEEE, 1989. http://dx.doi.org/10.23919/acc.1989.4790303.

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Lijing Dong, Senchun Chai, and Baihai Zhang. "Necessary and sufficient conditions for consensus of multi-agent systems with nonlinear dynamics and variable topology." In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334778.

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Bender, Dylan, and Ahmad Barari. "Convergence Control For Topology Optimization." In 2018 Canadian Society for Mechanical Engineering (CSME) International Congress. York University Libraries, 2018. http://dx.doi.org/10.25071/10315/35269.

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Yan, Dongmei, JinKuan Wang, Li Liu, Bin Wang, and Peng Xu. "Topology Control Target Tracking-Oriented." In 2009 IITA International Conference on Control, Automation and Systems Engineering, CASE 2009. IEEE, 2009. http://dx.doi.org/10.1109/case.2009.126.

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Burkhart, Martin, Pascal von Rickenbach, Roger Wattenhofer, and Aaron Zollinger. "Does topology control reduce interference?" In the 5th ACM international symposium. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/989459.989462.

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Anguera, J., M. Blesa, J. Farré, V. López, and J. Petit. "Topology control algorithms in WISELIB." In the 2010 ICSE Workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1809111.1809118.

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"System control and converter topology." In 2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551). IEEE, 2004. http://dx.doi.org/10.1109/pesc.2004.1355745.

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Stein, Michael, Geza Kulcsar, Immanuel Schweizer, Gergely Varro, Andy Schurr, and Max Muhlhauser. "Topology control with application constraints." In 2015 IEEE 40th Conference on Local Computer Networks (LCN). IEEE, 2015. http://dx.doi.org/10.1109/lcn.2015.7366313.

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Reports on the topic "Topology Control"

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Kezunovic, Mladen, Shmuel Oren, Kory Hedman, Erick Moreno Centeno, Garng Huang, and Alex Sprintson. Robust Adaptive Topology Control Project (RATC). Office of Scientific and Technical Information (OSTI), July 2015. http://dx.doi.org/10.2172/1209678.

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Puskas, Judit, Gregory McKenna, and Julia Kornfield. Collaborative Research: Polymer Macrocycles: A novel topology to control dynamics of rubbery materials. Office of Scientific and Technical Information (OSTI), June 2019. http://dx.doi.org/10.2172/1654432.

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