Relevant bibliographies by topics / Deterministic networks

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

Academic literature on the topic 'Deterministic networks'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 February 2022

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Journal articles on the topic "Deterministic networks"

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Barrière, L., F. Comellas, C. Dalfó, and M. A. Fiol. "Deterministic hierarchical networks." Journal of Physics A: Mathematical and Theoretical 49, no. 22 (May 3, 2016): 225202. http://dx.doi.org/10.1088/1751-8113/49/22/225202.

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Li, Xin-Feng, Zhe-Ming Lu, and Hui Li. "Controllability of deterministic complex networks." International Journal of Modern Physics C 26, no. 03 (February 25, 2015): 1550028. http://dx.doi.org/10.1142/s012918311550028x.

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Recently, the controllability of complex networks has attracted wide attention of researchers. The main contribution comes from Liu et al. who proposed the structural controllability as an analytical framework for making predictions regarding the control of directed networks in Nature. Since then, the controllability of many model and real networks has been deeply investigated except deterministic complex networks. In this paper, we focus on studying the controllability of deterministic complex networks. We examine six typical deterministic networks, the simulation results show that the minimum number of driver nodes grows linearly with network size. When the network size is large enough, the controllability approximates to a constant not more than 0.4, indicating that the deterministic networks are relatively easy to control. Furthermore, we investigate the characteristics of driver nodes in deterministic complex networks, finding that the driver nodes tend to avoid high degree nodes but to have high clustering coefficients.
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Benzaoui, Nihel, Mijail Szczerban Gonzalez, Jose Manuel Estaran, Haik Mardoyan, Wolfram Lautenschlaeger, Ulrich Gebhard, Lars Dembeck, Sebastien Bigo, and Yvan Pointurier. "Deterministic Dynamic Networks (DDN)." Journal of Lightwave Technology 37, no. 14 (July 15, 2019): 3465–74. http://dx.doi.org/10.1109/jlt.2019.2917280.

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Barabási, Albert-László, Erzsébet Ravasz, and Tamás Vicsek. "Deterministic scale-free networks." Physica A: Statistical Mechanics and its Applications 299, no. 3-4 (October 2001): 559–64. http://dx.doi.org/10.1016/s0378-4371(01)00369-7.

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Comellas, Francesc, and Michael Sampels. "Deterministic small-world networks." Physica A: Statistical Mechanics and its Applications 309, no. 1-2 (June 2002): 231–35. http://dx.doi.org/10.1016/s0378-4371(02)00741-0.

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Xing, Changming, Lin Yang, and Jun Ma. "A deterministic pseudo-fractal networks with time-delay." International Journal of Modern Physics B 29, no. 22 (September 7, 2015): 1550155. http://dx.doi.org/10.1142/s0217979215501556.

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In this paper, inspired by the pseudo-fractal networks (PFN) and the delayed pseudo-fractal networks (DPFN), we present a novel delayed pseudo-fractal networks model, denoted by NDPFN. Different from the generation algorithm of those two networks, every edge of the novel model has a time-delay to generate new nodes after producing one node. We derive exactly the main structural properties of the novel networks: degree distribution, clustering coefficient, diameter and average path length. Analytical results show that the novel networks have small-world effect and scale-free topology. Comparing topological parameters of these three networks, we find that the degree exponent of the novel networks is the largest while the clustering coefficient and the average path length are the smallest. It means that this kind of delay could weaken the heterogeneity and the small-world features of the network. Particularly, the delay effect in the NDPFN is contrary to that in the DPFN, which illustrates the variety of delay method could produce different effects on the network structure. These present findings may be helpful for a deeper understanding of the time-delay influence on the network topology.
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Ma, Y., X. Jiang, M. Li, and Z. Zheng. "Trapping on Deterministic Multiplex Networks." Acta Physica Polonica B 46, no. 4 (2015): 789. http://dx.doi.org/10.5506/aphyspolb.46.789.

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Ciszak, M., and R. Meucci. "Spontaneous Transitions in Deterministic Networks." Acta Physica Polonica B 45, no. 6 (2014): 1157. http://dx.doi.org/10.5506/aphyspolb.45.1157.

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Roy, Saptarshi, Titas Chanda, Tamoghna Das, Aditi Sen(De), and Ujjwal Sen. "Deterministic quantum dense coding networks." Physics Letters A 382, no. 26 (July 2018): 1709–15. http://dx.doi.org/10.1016/j.physleta.2018.04.033.

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Comellas, Francesc, Javier Ozón, and Joseph G. Peters. "Deterministic small-world communication networks." Information Processing Letters 76, no. 1-2 (November 2000): 83–90. http://dx.doi.org/10.1016/s0020-0190(00)00118-6.

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Dissertations / Theses on the topic "Deterministic networks"

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Gibson, David James. "Deterministic SpaceWire networks." Thesis, University of Dundee, 2017. https://discovery.dundee.ac.uk/en/studentTheses/86f0873d-7eea-4377-960b-249c9171574e.

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SpaceWire-D is an extension to the SpaceWire protocol that adds deterministic capabilities over existing equipment. It does this by using time-division multiplexing, controlled by the sequential broadcasting of time-codes by a network manager. A virtual bus abstraction is then used to divide the network architecture into segments in which all traffic is controlled by a single Remote Memory Access Protocol (RMAP) transaction initiator. Virtual buses are then allocated a number of time-slots in which they are allowed to operate, forming the SpaceWire-D schedule. This research starts by contributing an efficient embedded SpaceWire-D software layer, running on top of the RTEMS real-time operating system, for use in the initiators of a SpaceWire-D network. Next, the SpaceWire-D software layer was used in two LEON2-FT processor boards in combination with multiple other RMAP target boards, routers, a network manager, and a host PC running a suite of applications to create a SpaceWire-D Demonstrator. The SpaceWire-D software layer and SpaceWire-D Demonstrator were used to verify and demonstrate the SpaceWire-D protocol during the ESA SpaceWire-D project and resulted in multiple deliverables to ESA. Finally, this research contributes a novel SpaceWire-D scheduling strategy using a combination of path selection and transaction allocation algorithms. This strategy allows for a SpaceWire-D network to be defined as a list of periodic, aperiodic and payload data bandwidth requirements and outputs a list of paths and an allocation of transactions to time-slots which satisfy the networking requirements of a mission.
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Sansavini, Giovanni. "Network Modeling Stochastic and Deterministic Approaches." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/28857.

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Stochastic and deterministic approaches for modeling complex networks are presented. The methodology combines analysis of the structure formed by the interconnections among the elements of a network with an assessment of the vulnerability towards the propagation of cascading failures. The goal is to understand the mutual interplay between the structure of the network connections and the propagation of cascading failures. Two fundamental issues related to the optimal design and operation of complex networks are addressed. The first concerns the impact that cascading failures have on networks due to the connectivity pattern linking their components. If the state of load on the network components is high, the risk of cascade spreadings becomes significant. In this case, the needed reduction of the connectivity efficiency to prevent the propagation of failures affecting the entire system is quantified. The second issue concerns the realization of the most efficient connectivity in a network that minimizes the propagations of cascading failures. It is found that a system that routinely approaches the critical load for the onset of cascading failures during its operation should have a larger efficiency value. This allows for a smoother transition to the cascade region and for a reasonable reaction time to counteract the onset of significant cascading failures. The interplay between the structure of the network connections and the propagation of cascading failures is assessed also in interdependent networks. In these systems, the linking among several network infrastructures is necessary for their optimal and economical operation. Yet, the interdependencies introduce weaknesses due to the fact that failures may cascade from one system to other interdependent systems, possibly affecting their overall functioning. Inspired by the global efficiency, a measure of the communication capabilities among interdependent systems, i.e. the interdependency efficiency, is defined. The relations between the structural parameters, i.e. the system links and the interdependency links, and the interdependency efficiency, are also quantified, as well as the relations between the structural parameters and the vulnerability towards the propagation of cascading failures. Resorting to this knowledge, the optimal interdependency connectivity is identified. Similar to the spreading of failures, the formation of a giant component is a critical phenomenon emerging as a result of the connectivity pattern in a network. This structural transition is exploited to identify the formation of macrometastases in the developed model for metastatic colonization in tumor growth. The methods of network theory proves particularly suitable to reproduce the local interactions among tumor cells that lead to the emergent global behavior of the metastasis as a community. This model for intercellular sensing reproduces the stepwise behavior characteristic of metastatic colonization. Moreover, it prompts the consideration of a curative intervention that hinders intercellular communication, even in the presence of a significant tumor cell population.
Ph. D.
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Schrammar, Nicolas. "On Deterministic Models for Wireless Networks." Licentiate thesis, KTH, Kommunikationsteori, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-32116.

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Wireless communication is commonly modeled as a stochastic system. This is justified by the fact that the wireless channel incorporates a number of stochastic effects including fading, interference and thermal noise.One example for a stochastic model is the additive white Gaussian noise (AWGN) model, which has been successfully used to analyze the capacity of the point-to-point channel and some multi-terminal networks. However, the AWGN capacity of most networks is still an open problem. This includes small examples like the relay channel, which consists of just three terminals.In order to progress, it was suggested to investigate deterministic channel models as an approximation of the AWGN model. The objective is to find a deterministic model, which is accessible to capacity analysis. Furthermore, this analysis should provide insights on the capacity of the AWGN model.In this thesis we consider two deterministic models, the linear finite-field model (LFFM) by Avestimehr et at. and the discrete superposition model (DSM) by Anand and Kumar.It has been shown that the capacity of the DSM is a constant gap approximation of the AWGN capacity for some networks including the parallel relay network (PRN). We find upper and lower bounds on the DSM capacity of the point-to-point channel, the multiple-access channel, the broadcast channel and the PRN. Our bounds are within a constant gap, hence, they yield a constant gap approximation to the AWGN capacity of the PRN.We also show how the LFFM can be utilized to design transmission strategies for AWGN relay networks. A transmission strategy in the LFFM can be translated into a transmission strategy in the AWGN model if it fulfills certain constraints. We consider two sets of constraints, and we show that in both cases the rate in the AWGN model is at most a constant below the rate in the corresponding LFFM.
QC 20110407
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Schrammar, Nicolas. "On Deterministic Models for Gaussian Networks." Doctoral thesis, KTH, Kommunikationsteori, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-122275.

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In this thesis we study wireless networks modeled by the additive white Gaussian noise (AWGN) model. The AWGN capacity region of most network topologies is unknown, which means that the optimal transmission scheme is unknown as well. This motivates the search for capacity approximations and for approximately optimal schemes. Deterministic channel models have been proposed as means to approximate the AWGN model within a constant additive gap. We consider two particular models, the linear finite-field model (LFFM) and the discrete superposi- tion model (DSM). In the first part of the thesis we utilize the LFFM to design transmission schemes for layered relay networks in the AWGN model. We show that if a transmission scheme in the LFFM satisfies a certain set of coordination constraints, it can be translated to the AWGN model. A form of hierarchical modulation is used to build multiple transmission layers. By analyzing the performance in the AWGN model, we show that the AWGN rate is at most a constant gap below the LFFM rate. In the second part, we use the DSM to approximate the capacity and secrecy capacity of AWGN networks. First, we prove that the DSM capacity of some topologies is within a constant gap to the corresponding AWGN capacity. The topologies are given by the partially cognitive interference channel (PCIFC), a class of multiple-unicast networks, and a class of relay networks with secrecy con- straints, respectively. Then, we approximate the capacity in the DSM. We bound the capacity of the point-to-point channel, the capacity regions of the multiple- access channel and the broadcast channel, as well as the secrecy capacity of parallel relay networks (PRN) with an orthogonal eavesdropper and conventional relays. Furthermore, we find inner bounds on the capacity region of the PCIFC. This approach yields achievable rate regions for the PCIFC in the AWGN model and the AWGN secrecy capacity of the PRN within a constant gap.

QC 20130516

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SOUZA, MARCELO GOMES DE. "DETERMINISTIC ACOUSTIC SEISMIC INVERSION USING ARTIFICIAL NEURAL NETWORKS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2018. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34647@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
A inversão sísmica é o processo de transformar dados de Sísmica de Reflexão em valores quantitativos de propriedades petroelásticas das rochas. Esses valores, por sua vez, podem ser correlacionados com outras propriedades ajudando os geocientistas a fazer uma melhor interpretação que resulta numa boa caracterização de um reservatório de petróleo. Existem vários algoritmos tradicionais para Inversão Sísmica. Neste trabalho revisitamos a Inversão Colorida (Impedância Relativa), a Inversão Recursiva, a Inversão Limitada em Banda e a Inversão Baseada em Modelos. Todos esses quatro algoritmos são baseados em processamento digital de sinais e otimização. O presente trabalho busca reproduzir os resultados desses algoritmos através de uma metodologia simples e eficiente baseada em Redes Neurais e na pseudo-impedância. Este trabalho apresenta uma implementação dos algoritmos propostos na metodologia e testa sua validade num dado sísmico público que tem uma inversão feita pelos métodos tradicionais.
Seismic inversion is the process of transforming Reflection Seismic data into quantitative values of petroleum rock properties. These values, in turn, can be correlated with other properties helping geoscientists to make a better interpretation that results in a good characterization of an oil reservoir.There are several traditional algorithms for Seismic Inversion. In this work we revise Color Inversion (Relative Impedance), Recursive Inversion, Bandwidth Inversion and Model-Based Inversion. All four of these algorithms are based on digital signal processing and optimization. The present work seeks to reproduce the results of these algorithms through a simple and efficient methodology based on Neural Networks and pseudo-impedance. This work presents an implementation of the algorithms proposed in the methodology and tests its validity in a public seismic data that has an inversion made by the traditional methods.
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Thubert, Pascal. "Converging over deterministic networks for an Industrial Internet." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2017. http://www.theses.fr/2017IMTA0011/document.

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En s'appuyant sur une connaissance précise du temps, sur la réservation de ressources et l'application distribuée de règles d'admission strictes, un réseau déterministe permet de transporter des flux pré-spécifiés avec un taux de perte extrêmement bas et une latence maximale majorée, ouvrant la voie au support d'applications critiques et/ou temps-réel sur une infrastructure de réseau convergée. De nos jours, la Technologie Opérationnelle (OT) s'appuie sur des réseaux déterministes mais conçus à façon, en général propriétaires, utilisant typiquement des liens série spécifiques, et opérés en isolation les uns des autres, ce qui multiplie la complexité physique et les coûts d'achat et de déploiement (CAPEX), ainsi que d'opération et maintenance (OPEX), et empêche l'utilisation agile des ressources. En apportant le déterminisme dans les réseaux des Technologies de l'Information (IT), une nouvelle génération de réseaux commutés de l'IT va permettre l'émulation de ces liens série et la convergence de réseaux autrefois dédiés sur une infrastructure commune à base d'IP. En retour, la convergence de l'IT et de l'OT permettra de nouvelles optimisations industrielles, en introduisant des technologies héritées de l'IT, comme le BigData et la virtualisation des fonctions du réseau (NFV), en support des opérations de l'OT, améliorant les rendements tout en apportant une réduction supplémentaire des coûts. Les solutions de réseaux déterministes réclament des possibilités nouvelles de la part des équipements, possibilités qui vont bien au-delà de celles demandées pour les besoins classiques de la QoS. Les attributs-clé sont : - la synchronisation précise de tous les n'uds, en incluant souvent la source et la destination des flux- le calcul centralisé de chemins de bout en bout à l'échelle du réseau- de nouveaux filtres de mise en forme du trafic à l'intérieur comme à l'entrée du réseau afin de le protéger en tous points- des moyens matériels permettant l'accès au medium à des échéances précises. Au travers de multiples papiers, de contributions à des standards, et de publication de propriété industrielle, le travail présenté ici repousse les limites des réseaux industriels sans fils en offrant : 1. Le calcul centralisé de chemin complexes basé sur une technologie innovante appelée ARC 2. La signalisation de ces chemins complexes et la traçabilité des paquets par une extension de la technologie BIER-TE 3. Réplication, Renvoi et Elimination des doublons le long de ces chemins complexes 4. Un temps-réel basé sur un échéancier qui assure un haut taux de délivrance et garantit une latence bornée 5. La capacité de transporter à la fois des flux déterministes et du trafic IPv6 à multiplexage statistique sur un maillage 6TiSCH partagéCe manuscrit rapporte des améliorations apportées aux techniques existantes des réseaux sans fils à basse puissance (LoWPAN) comme Zigbee, WirelessHART'et ISA100.11a, afin d'amener ces nouveaux bénéfices jusqu'aux réseaux opérationnels sans fil. Elle a été implémentée en programme et sur du matériel open-source, et évaluée face à du IEEE Std. 802.15.4 classique ainsi que du 802.15.4 TSCH, utilisés en topologie maillée. L'expérience menée montre que notre nouvelle proposition permet d'éviter les à-coups et de garantir des taux élevés de délivrance, même face à des évènements exceptionnels comme la perte d'un relais ou la dégradation temporaire d'un lien radio
Based on time, resource reservation, and policy enforcement by distributed shapers, Deterministic Networking provides the capability to carry specified unicast or multicast data streams for real-time applications with extremely low data loss rates and bounded latency, so as to support time-sensitive and mission-critical applications on a converged enterprise infrastructure.As of today, deterministic Operational Technology (OT) networks are purpose-built, mostly proprietary, typically using serial point-to-point wires, and operated as physically separate networks, which multiplies the complexity of the physical layout and the operational (OPEX) and capital (CAPEX) expenditures, while preventing the agile reuse of the compute and network resources.Bringing determinism in Information Technology (IT) networks will enable the emulation of those legacy serial wires over IT fabrics and the convergence of mission-specific OT networks onto IP. The IT/OT convergence onto Deterministic Networks will in turn enable new process optimization by introducing IT capabilities, such as the Big Data and the network functions virtualization (NFV), improving OT processes while further reducing the associated OPEX.Deterministic Networking Solutions and application use-cases require capabilities of the converged network that is beyond existing QOS mechanisms.Key attributes of Deterministic Networking are: - Time synchronization on all the nodes, often including source and destination - The centralized computation of network-wide deterministic paths - New traffic shapers within and at the edge to protect the network- Hardware for scheduled access to the media.Through multiple papers, standard contribution and Intellectual Property publication, the presented work pushes the limits of wireless industrial standards by providing: 1. Complex Track computation based on a novel ARC technology 2. Complex Track signaling and traceability, extending the IETF BIER-TE technology 3. Replication, Retry and Duplicate Elimination along the Track 4. Scheduled runtime enabling highly reliable delivery within bounded time 5. Mix of IPv6 best effort traffic and deterministic flows within a shared 6TiSCH mesh structureThis manuscript presents enhancements to existing low power wireless networks (LoWPAN) such as Zigbee, WirelessHART¿and ISA100.11a to provide those new benefits to wireless OT networks. It was implemented on open-source software and hardware, and evaluated against classical IEEE Std. 802.15.4 and 802.15.4 TSCH radio meshes. This manuscript presents and discusses the experimental results; the experiments show that the proposed technology can guarantee continuous high levels of timely delivery in the face of adverse events such as device loss and transient radio link down
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Morrison, Erin Seidler, and Erin Seidler Morrison. "Exploring the Deterministic Landscape of Evolution: An Example with Carotenoid Diversification in Birds." Diss., The University of Arizona, 2017. http://hdl.handle.net/10150/624290.

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Establishing metrics of diversification can calibrate the observed scope of diversity within a lineage and the potential for further phenotypic diversification. There are two potential ways to calibrate differences between phenotypes. The first metric is based on the structure of the network of direct and indirect connections between elements, such as the genes, proteins, enzymes and metabolites that underlie a phenotype. The second metric characterizes the dynamic properties that determine the strength of the interactions among elements, and influence which elements are the most likely to interact. Determining how the connectivity and strength of interactions between elements lead to specific phenotypic variations provides insight into the tempo and mode of observed evolutionary changes. In this dissertation, I proposed and tested hypotheses for how the structure and metabolic flux of a biochemical network delineate patterns of phenotypic variation. I first examined the role of structural properties in shaping observed patterns of carotenoid diversification in avian plumage. I found that the diversification of species-specific carotenoid networks was predictable from the connectivity of the underlying metabolic network. The compounds with the most enzymatic reactions, that were part of the greatest number of distinct pathways, were more conserved across species’ networks than compounds associated with the fewest enzymatic reactions. These results established that compounds with the greatest connectivity act as hotspots for the diversification of pathways between species. Next, I investigated how dynamic properties of biochemical networks influence patterns of phenotypic variation in the concentration and occurrence of compounds. Specifically, I examined if the rate of compound production, known as metabolic flux, is coordinated among compounds in relation to their structural properties. I developed predictions for how different distributions of flux could cause distinct diversification patterns in the concentrations and presence of compounds in a biochemical network. I then tested the effect of metabolic network structure on the concentrations of carotenoids in the plumage of male house finches (Haemorhous mexicanus) from the same population. I assessed whether the structure of a network corresponds to a specific distribution of flux among compounds, or if flux is independent of network structure. I found that flux coevolves with network structure; concentrations of metabolically derived compounds depended on the number of reactions per compound. There were strong correlations between compound concentrations within a network structure, and the strengths of these correlations varied among structures. These findings suggest that changes in network structure, and not independent changes in flux, influence local adaptations in the concentrations of compounds. Lastly, the influence of carotenoid network structure in the evolutionary diversification of compounds across species of birds depends on how the structure of the network itself evolves. To test whether the carotenoid metabolic network structure evolves in birds, I examined the patterns of carotenoid co-occurrence across ancestral and extant species. I found that the same groups of compounds are always gained or lost together even as lineages diverge further from each other. These findings establish that the diversification of carotenoids in birds is constrained by the structure of an ancestral network, and does not evolve independently within a lineage. Taken together, the results of this dissertation establish that local adaptations and the evolutionary diversification of carotenoid metabolism are qualitatively predictable from the structure of an ancestral enzymatic network, and this suggests there is significant structural determinism in phenotypic evolution.
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Medlej, Sara, and Sara Medlej. "Scalable Trajectory Approach for ensuring deterministic guarantees in large networks." Phd thesis, Université Paris Sud - Paris XI, 2013. http://tel.archives-ouvertes.fr/tel-00998249.

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In critical real-time systems, any faulty behavior may endanger lives. Hence, system verification and validation is essential before their deployment. In fact, safety authorities ask to ensure deterministic guarantees. In this thesis, we are interested in offering temporal guarantees; in particular we need to prove that the end-to-end response time of every flow present in the network is bounded. This subject has been addressed for many years and several approaches have been developed. After a brief comparison between the existing approaches, the Trajectory Approach sounded like a good candidate due to the tightness of its offered bound. This method uses results established by the scheduling theory to derive an upper bound. The reasons leading to a pessimistic upper bound are investigated. Moreover, since the method must be applied on large networks, it is important to be able to give results in an acceptable time frame. Hence, a study of the method's scalability was carried out. Analysis shows that the complexity of the computation is due to a recursive and iterative processes. As the number of flows and switches increase, the total runtime required to compute the upper bound of every flow present in the network understudy grows rapidly. While based on the concept of the Trajectory Approach, we propose to compute an upper bound in a reduced time frame and without significant loss in its precision. It is called the Scalable Trajectory Approach. After applying it to a network, simulation results show that the total runtime was reduced from several days to a dozen seconds.
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Neely, Michael J. (Michael James) 1975. "Queue occupancy in single-server deterministic service time tree networks." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/9318.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
Includes bibliographical references (p. 167).
Tree networks of single server, deterministic service time queues are often used as models for packet flow in systems with ATM traffic. In this thesis, we present methods of analyzing packet occupancy in these systems. We develop general theorems which enable the analysis of individual nodes within a multi-stage system to be reduced to the analysis of a simpler single-stage or 2- stage equivalent model. In these theorems, we make very few assumptions about the nature of the exogenous input processes themselves, and hence our results apply to a variety of input sources. In particular, we treat three input source cases: bursty on/off inputs, periodic continuous bit rate (CBR) inputs, and discrete time Generalized Independent (GI) inputs. For each of these input sources, we derive mean queue lengths for individual nodes and aggregate occupancy distribution functions for multi-stage systems. For GI-type inputs (which includes memoryless inputs), we derive explicit expressions for the means and variances of packet occupancy in any node of a multi-stage, deterministic service time tree network. We also create a general definition of a "distributable input," which includes any collection of M sources which run independently and are identically distributed (iid) according to some arbitrary type of arrival process (in particular, this includes periodic CBR sources). We demonstrate that the expected occupancy of a single-stage system is a convex, monotonic function of the distributable input loading. Furthermore, the expected occupancy of any node within a multi-stage tree network is a concave function of the multiple exogenous input loadings at the upstream nodes.
by Michael J. Neely.
S.M.
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Medlej, Sara. "Scalable Trajectory Approach for ensuring deterministic guarantees in large networks." Thesis, Paris 11, 2013. http://www.theses.fr/2013PA112168/document.

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Tout comportement défectueux d’un système temps-réel critique, comme celui utilisé dans le réseau avionique ou le secteur nucléaire, peut mettre en danger des vies. Par conséquent, la vérification et validation de ces systèmes est indispensable avant leurs déploiements. En fait, les autorités de sécurité demandent d’assurer des garanties déterministes. Dans cette thèse, nous nous intéressons à obtenir des garanties temporelles, en particulier nous avons besoin de prouver que le temps de réponse de bout-en-bout de chaque flux présent dans le réseau est borné. Ce sujet a été abordé durant de nombreuses années et plusieurs approches ont été développées. Après une brève comparaison entre les différentes approches existantes, une semble être un bon candidat. Elle s’appelle l’approche par trajectoire; cette méthode utilise les résultats établis par la théorie de l'ordonnancement afin de calculer une limite supérieure. En réalité, la surestimation de la borne calculée peut entrainer la rejection de certification du réseau. Ainsi une première partie du travail consiste à détecter les sources de pessimisme de l’approche adoptée. Dans le cadre d’un ordonnancement FIFO, les termes ajoutant du pessimisme à la borne calculée ont été identifiés. Cependant, comme les autres méthodes, l’approche par trajectoire souffre du problème de passage à l’échelle. En fait, l’approche doit être appliquée sur un réseau composé d’une centaine de commutateur et d’un nombre de flux qui dépasse les milliers. Ainsi, il est important qu’elle soit en mesure d'offrir des résultats dans un délai acceptable. La première étape consiste à identifier, dans le cas d’un ordonnancement FIFO, les termes conduisant à un temps de calcul important. L'analyse montre que la complexité du calcul est due à un processus récursif et itératif. Ensuite, en se basant toujours sur l’approche par trajectoire, nous proposons de calculer une limite supérieure dans un intervalle de temps réduit et sans perte significative de précision. C'est ce qu'on appelle l'approche par trajectoire scalable. Un outil a été développé permettant de comparer les résultats obtenus par l’approche par trajectoire et notre proposition. Après application sur un réseau de taille réduite (composé de 10 commutateurs), les résultats de simulations montrent que la durée totale nécessaire pour calculer les bornes des milles flux a été réduite de plusieurs jours à une dizaine de secondes
In critical real-time systems, any faulty behavior may endanger lives. Hence, system verification and validation is essential before their deployment. In fact, safety authorities ask to ensure deterministic guarantees. In this thesis, we are interested in offering temporal guarantees; in particular we need to prove that the end-to-end response time of every flow present in the network is bounded. This subject has been addressed for many years and several approaches have been developed. After a brief comparison between the existing approaches, the Trajectory Approach sounded like a good candidate due to the tightness of its offered bound. This method uses results established by the scheduling theory to derive an upper bound. The reasons leading to a pessimistic upper bound are investigated. Moreover, since the method must be applied on large networks, it is important to be able to give results in an acceptable time frame. Hence, a study of the method’s scalability was carried out. Analysis shows that the complexity of the computation is due to a recursive and iterative processes. As the number of flows and switches increase, the total runtime required to compute the upper bound of every flow present in the network understudy grows rapidly. While based on the concept of the Trajectory Approach, we propose to compute an upper bound in a reduced time frame and without significant loss in its precision. It is called the Scalable Trajectory Approach. After applying it to a network, simulation results show that the total runtime was reduced from several days to a dozen seconds
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Books on the topic "Deterministic networks"

1

Kumar, Bose Deb, ed. Neural networks: Deterministic methods of analysis. London: International Thomson Computer Press, 1996.

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Moore, Kevin L. Iterative learning control for deterministic systems. London: Springer-Verlag, 1993.

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Wang, Cong. Deterministic learning theory for identification, control, and recognition. Boca Raton: CRC Press, 2009.

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Bitran, Gabriel R. Multiproduct queueing networks with deterministic routing: Decomposition approach and the notion of interference. Cambridge, Mass: Sloan School of Management, Massachusetts Institute of Technology, 1986.

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Wang, Jun. A Bayesian classifier based on a deterministic annealing neural network for aircraft fault classification. Wright-Patterson AFB, OH: Human Resources Directorate, Logistics Research Division, U.S. Air Force Armstrong Laboratory, 1997.

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Bouillard, Anne, Marc Boyer, and Euriell Le Corronc. Deterministic Network Calculus. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119440284.

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Ahsen, Mehmet Eren, Hitay Özbay, and Silviu-Iulian Niculescu. Analysis of Deterministic Cyclic Gene Regulatory Network Models with Delays. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15606-4.

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Galland, Conrad. Learning in deterministic Boltzmann machine networks. 1992.

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Boyer, Marc, Anne Bouillard, and Euriell Le Corronc. Deterministic Network Calculus: From Theory to Practical Implementation. Wiley & Sons, Incorporated, John, 2018.

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Lente, Gábor. Deterministic Kinetics in Chemistry and Systems Biology: The Dynamics of Complex Reaction Networks. Springer, 2015.

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Book chapters on the topic "Deterministic networks"

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Gotzhein, Reinhard. "Deterministic Arbitration." In Computer Communications and Networks, 125–48. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33319-5_6.

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Rüger, Stefan M. "Making stochastic networks deterministic." In Lecture Notes in Computer Science, 355–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0020180.

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Roy, Radhika Ranjan. "Deterministic Mobility." In Handbook of Mobile Ad Hoc Networks for Mobility Models, 245–63. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-6050-4_8.

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Laurenti, Nicola, and Tomaso Erseghe. "Deterministic and Random Signals." In Principles of Communications Networks and Systems, 27–136. Chichester, UK: John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9781119978589.ch2.

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Dieudonné, Yoann, and Franck Petit. "Self-stabilizing Deterministic Gathering." In Algorithmic Aspects of Wireless Sensor Networks, 230–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-05434-1_23.

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Doty, David, and Monir Hajiaghayi. "Leaderless Deterministic Chemical Reaction Networks." In Lecture Notes in Computer Science, 46–60. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01928-4_4.

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Stelling, Jörg, and Hans-Michael Kaltenbach. "Deterministic Description of Biochemical Networks." In Encyclopedia of Systems and Control, 264–68. London: Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-5058-9_87.

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Stelling, Jörg, and Hans-Michael Kaltenbach. "Deterministic Description of Biochemical Networks." In Encyclopedia of Systems and Control, 1–6. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5102-9_87-1.

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Gąsieniec, Leszek. "Deterministic Broadcasting in Radio Networks." In Encyclopedia of Algorithms, 233–35. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-30162-4_105.

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Gąsieniec, Leszek. "Deterministic Broadcasting in Radio Networks." In Encyclopedia of Algorithms, 529–30. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-2864-4_105.

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Conference papers on the topic "Deterministic networks"

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Benzaoui, N., M. Szczerban Gonzalez, J. M. Estarán, H. Mardoyan, W. Lautenschlaeger, U. Gebhard, L. Dembeck, S. Bigo, and Y. Pointurier. "Latency control in Deterministic and Dynamic Networks." In Photonic Networks and Devices. Washington, D.C.: OSA, 2019. http://dx.doi.org/10.1364/networks.2019.net3d.4.

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W.-S. Tseng, Vincent, Sourav Bhattacharya, Javier Fernández Marqués, Milad Alizadeh, Catherine Tong, and Nicholas D. Lane. "Deterministic Binary Filters for Convolutional Neural Networks." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/380.

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We propose Deterministic Binary Filters, an approach to Convolutional Neural Networks that learns weighting coefficients of predefined orthogonal binary basis instead of the conventional approach of learning directly the convolutional filters. This approach results in model architectures with significantly fewer parameters (4x to 16x) and smaller model sizes (32x due to the use of binary rather than floating point precision). We show our deterministic filter design can be integrated into well-known network architectures (such as ResNet and SqueezeNet) with as little as 2% loss of accuracy (under datasets like CIFAR-10). Under ImageNet, they result in 3x model size reduction compared to sub-megabyte binary networks while reaching comparable accuracy levels.
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Host-Madsen, Anders. "Deterministic Capacity of Networks." In 2007 IEEE Information Theory Workshop. IEEE, 2007. http://dx.doi.org/10.1109/itw.2007.4313142.

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Liotta, Antonio. "Farewell to deterministic networks." In 2012 IEEE 19th Symposium on Communications and Vehicular Technology in the Benelux (SCVT). IEEE, 2012. http://dx.doi.org/10.1109/scvt.2012.6399413.

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Benzaoui, Nihel, Mijail Szczerban Gonzalez, Maria V. Rivera, Jose M. Estaran, Haik Mardoyan, Wolfram Lautenschlaeger, Ulrich Gebhard, Lars Dembeck, Yvan Pointurier, and Sebastien Bigo. "DDN: Deterministic Dynamic Networks." In 2018 European Conference on Optical Communication (ECOC). IEEE, 2018. http://dx.doi.org/10.1109/ecoc.2018.8535191.

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Graur, Oana, and Werner Henkel. "Towards Deterministic Network Coding in Hierarchical Networks." In 2014 2nd International Conference on Artificial Intelligence, Modelling & Simulation (AIMS). IEEE, 2014. http://dx.doi.org/10.1109/aims.2014.43.

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Pointurier, Yvan, Nihel Benzaoui, Wolfram Lautenschlaeger, Ulrich Gebhard, Lars Dembeck, and Sébastien Bigo. "Slot switching for deterministic dynamic edge cloud networks." In Photonic Networks and Devices. Washington, D.C.: OSA, 2018. http://dx.doi.org/10.1364/networks.2018.netu4f.4.

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Bartram, Gregory W., and Sankaran Mahadevan. "Probabilistic Prognosis Using Dynamic Bayesian Networks." In 16th AIAA Non-Deterministic Approaches Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2014. http://dx.doi.org/10.2514/6.2014-0483.

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Ebrahimi, Javad, and Christina Fragouli. "Multicasting algorithms for deterministic networks." In 2010 IEEE Information Theory Workshop on Information Theory (ITW). IEEE, 2010. http://dx.doi.org/10.1109/itwksps.2010.5503221.

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Pajic, Miroslav, Shreyas Sundaram, and George J. Pappas. "Stabilizability over deterministic relay networks." In 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). IEEE, 2013. http://dx.doi.org/10.1109/cdc.2013.6760504.

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Reports on the topic "Deterministic networks"

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Arumugam, Mahesh, and Sandeep S. Kulkarni. Self-Stabilizing Deterministic TDMA for Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada455715.

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