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Relevant bibliographies by topics / Network architectures

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Academic literature on the topic 'Network architectures'

Author: Grafiati

Published: 4 June 2021

Last updated: 2 February 2022

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Journal articles on the topic "Network architectures"

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DELGADO-FRIAS, JOSE G., STAMATIS VASSILIADIS, and JAMSHID GOSHTASBI. "SEMANTIC NETWORK ARCHITECTURES: AN EVALUATION." International Journal on Artificial Intelligence Tools 01, no. 01 (March 1992): 57–83. http://dx.doi.org/10.1142/s0218213092000132.

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Semantic networks as a means for knowledge representation and manipulation are used in many artificial intelligence applications. A number of computer architectures, that have been reported for semantic network processing, are presented in this paper. A novel set of evaluation criteria for such semantic network architectures has been developed. Semantic network processing as well as architectural issues are considered in such evaluation criteria. A study of how the reported architectures meet the requirements of each criterion is presented. This set of evaluation criteria is useful for future

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Zurn, Perry, and Danielle S. Bassett. "Network architectures supporting learnability." Philosophical Transactions of the Royal Society B: Biological Sciences 375, no. 1796 (February 24, 2020): 20190323. http://dx.doi.org/10.1098/rstb.2019.0323.

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Human learners acquire complex interconnected networks of relational knowledge. The capacity for such learning naturally depends on two factors: the architecture (or informational structure) of the knowledge network itself and the architecture of the computational unit—the brain—that encodes and processes the information. That is, learning is reliant on integrated network architectures at two levels: the epistemic and the computational, or the conceptual and the neural. Motivated by a wish to understand conventional human knowledge, here, we discuss emerging work assessing network constraints

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Dinn, Neil F. "Network architectures." Future Generation Computer Systems 7, no. 1 (October 1991): 79–89. http://dx.doi.org/10.1016/0167-739x(91)90018-s.

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Neeb, C., M. J. Thul, and N. Wehn. "Application driven evaluation of network on chip architectures forcation parallel signal processing." Advances in Radio Science 2 (May 27, 2005): 181–86. http://dx.doi.org/10.5194/ars-2-181-2004.

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Abstract. Today’s signal processing applications exhibit steadily increasing throughput requirements which can be achieved by parallel architectures. However, efficient communication is mandatory to fully exploit their parallelism. Turbo-Codes as an instance of highly efficient forward-error correction codes are a very good application to demonstrate the communication complexity in parallel architectures. We present a network-on-chip approach to derive an optimal communication architecture for a parallel Turbo-Decoder system. The performance of such a system significantly depends on the effici

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Lee, Woosik, Eun Suk Suh, Woo Young Kwak, and Hoon Han. "Comparative Analysis of 5G Mobile Communication Network Architectures." Applied Sciences 10, no. 7 (April 4, 2020): 2478. http://dx.doi.org/10.3390/app10072478.

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Mobile communication technology is evolving from 4G to 5G. Compared to previous generations, 5G has the capability to implement latency-critical services, such as autonomous driving, real-time AI on handheld devices and remote drone control. Multi-access Edge Computing is one of the key technologies of 5G in guaranteeing ultra-low latency aimed to support latency critical services by distributing centralized computing resources to networks edges closer to users. However, due to its high granularity of computing resources, Multi-access Edge Computing has an architectural vulnerability in that i

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Orhan, Orhan, and Huseyin Goren. "Largely Scalable Wireless Network Formation Architectures for Internet of Things." International Research Journal of Electronics and Computer Engineering 3, no. 4 (December 29, 2017): 17. http://dx.doi.org/10.24178/irjece.2017.3.4.17.

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As number of mobile devices increases with Internet of Things (IoT) capability and power consumption is important in multi hop communication, there is need of considering network formation architectures inIoT networks.In this work power levels of nodes, urgency of messages to be transmitted are not taken into consideration, a general approach considered with all nodes with same power levels and no priority for messages to be sent.Another assumption is all nodes are on the same 2D plane. Multi hop wireless network architectures studied and scalable, best performing architecture which is hypercu

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Fernandes, Silvio R., Ivan S. Silva, and Marcio Kreutz. "Packet-driven General Purpose Instruction Execution on Communication-based Architectures." Journal of Integrated Circuits and Systems 5, no. 1 (November 21, 2010): 53–66. http://dx.doi.org/10.29292/jics.v5i1.310.

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In the last few years, the development of Multi-Core architectures was driven by the crescent advance in integration technology. In this scenario, when the number of cores increases, problems found on shared communication media, such as busses, can be addressed by using a network approach. This paper proposes the usage of communication capabilities of Networks-on-Chip (NoCs) to execute general purpose instructions. The main idea behind this approach is to allow networks-on-chip architectures to execute general purpose instructions inside each router architecture. This paper addresses the main

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Pelt, Daniël M., and James A. Sethian. "A mixed-scale dense convolutional neural network for image analysis." Proceedings of the National Academy of Sciences 115, no. 2 (December 26, 2017): 254–59. http://dx.doi.org/10.1073/pnas.1715832114.

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Deep convolutional neural networks have been successfully applied to many image-processing problems in recent works. Popular network architectures often add additional operations and connections to the standard architecture to enable training deeper networks. To achieve accurate results in practice, a large number of trainable parameters are often required. Here, we introduce a network architecture based on using dilated convolutions to capture features at different image scales and densely connecting all feature maps with each other. The resulting architecture is able to achieve accurate resu

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Dovrolis, Constantine, and J. Todd Streelman. "Evolvable network architectures." ACM SIGCOMM Computer Communication Review 40, no. 2 (April 9, 2010): 72–77. http://dx.doi.org/10.1145/1764873.1764886.

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Littmann, Enno, and Helge Ritter. "Learning and Generalization in Cascade Network Architectures." Neural Computation 8, no. 7 (October 1996): 1521–39. http://dx.doi.org/10.1162/neco.1996.8.7.1521.

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Incrementally constructed cascade architectures are a promising alternative to networks of predefined size. This paper compares the direct cascade architecture (DCA) proposed in Littmann and Ritter (1992) to the cascade-correlation approach of Fahlman and Lebiere (1990) and to related approaches and discusses the properties on the basis of various benchmark results. One important virtue of DCA is that it allows the cascading of entire subnetworks, even if these admit no error-backpropagation. Exploiting this flexibility and using LLM networks as cascaded elements, we show that the performance

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Dissertations / Theses on the topic "Network architectures"

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Seah, Peng Leong Chung Wai Kong. "Architectures for device aware network /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Mar%5FSeah.pdf.

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Chung, Wai Kong. "Architectures for device aware network." Thesis, Monterey, California. Naval Postgraduate School, 2005. http://hdl.handle.net/10945/2306.

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In today's heterogeneous computing environment, a wide variety of computing devices with varying capabilities need to access information in the network. Existing network is not able to differentiate the different device capabilities, and indiscriminatingly send information to the end-devices, without regard to the ability of the end-devices to use the information. The goal of a device-aware network is to match the capability of the end-devices to the information delivered, thereby optimizing the network resource usage. In the battlefield, all resources - including time, network bandwidth and b

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Newton, Todd A., Myron L. Moodie, Ryan J. Thibodeaux, and Maria S. Araujo. "Network System Integration: Migrating Legacy Systems into Network-Based Architectures." International Foundation for Telemetering, 2010. http://hdl.handle.net/10150/604308.

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ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California<br>The direction of future data acquisition systems is rapidly moving toward a network-based architecture. There is a handful of these network-based flight test systems already operating, and the current trend is catching on all over the flight test community. As vendors are churning out a whole new product line for networking capabilities, system engineers are left asking, "What do

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Al-Azez, Zaineb Talib Saeed. "Optimised green IoT network architectures." Thesis, University of Leeds, 2018. http://etheses.whiterose.ac.uk/22224/.

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The work in this thesis proposes a number of energy efficient architectures of IoT networks. These proposed architectures are edge computing, Passive Optical Network (PON) and Peer to Peer (P2P) based architectures. A framework was introduced for virtualising edge computing assisted IoT. Two mixed integer linear programming (MILP) models and heuristics were developed to minimise the power consumption and to maximise the number of served IoT processing tasks. Further consideration was also given to the limited IoT processing capabilities and hence the potential of processing task blockage. Two

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Zheng, Huanyang. "SOCIAL NETWORK ARCHITECTURES AND APPLICATIONS." Diss., Temple University Libraries, 2017. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/470889.

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Computer and Information Science<br>Ph.D.<br>Rather than being randomly wired together, the components of complex network systems are recently reported to represent a scale-free architecture, in which the node degree distribution follows power-law. While social networks are scale-free, it is natural to utilize their structural properties in some social network applications. As a result, this dissertation explores social network architectures, and in turn, leverages these architectures to facilitate some influence and information propagation applications. Social network architectures are analyz

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Armstrong, James R. "Boolean weightless neural network architectures." Thesis, University of Central Lancashire, 2011. http://clok.uclan.ac.uk/5325/.

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A collection of hardware weightless Boolean elements has been developed. These form fundamental building blocks which have particular pertinence to the field of weightless neural networks. They have also been shown to have merit in their own right for the design of robust architectures. A major element of this is a collection of weightless Boolean sum and threshold techniques. These are fundamental building blocks which can be used in weightless architectures particularly within the field of weightless neural networks. Included in these is the implementation of L-max also known as N point thre

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Tham, Kevin Wen Kaye. "Developing security services for network architectures." Queensland University of Technology, 2006. http://eprints.qut.edu.au/16546/.

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In the last 15 years, the adoption of enterprise level data networks had increased dramatically. This is mainly due to reasons, such as better use of IT resources, and even better coordination between departments and business units. These great demands have fuelled the push for better and faster connectivity to and from these networks, and even within the networks. We have moved from the slow 10Mbps to 1Gbps connectivity for end-point connections and moved from copper-based ISDN to fibre-linked connections for enterprise connections to the Internet. We now even include wireless network technol

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Milosavljevic, Milos. "Integrated wireless-PON access network architectures." Thesis, University of Hertfordshire, 2011. http://hdl.handle.net/2299/6371.

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Next generation access networks should be able to cultivate the ongoing evolution in services and applications. Advancements on that front are expected to exhibit the transformation of high definition television (HDTV) and 2D services into ultra-HDTV and individual interactive 3D services. Currently deployed passive optical networks (PONs) have been certified to be able to deliver high quality video and internet services while in parallel broadband wireless standards are increasing their spectral efficiency and subscriber utilisation. Exploiting the benefits of both by providing an integrated

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Crowley, Patrick. "Design and analysis of architectures for programmable network processing systems /." Thesis, Connect to this title online; UW restricted, 2003. http://hdl.handle.net/1773/6991.

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Poluri, Pavan Kamal Sudheendra. "Fault Tolerant Network-on-Chip Router Architectures for Multi-Core Architectures." Diss., The University of Arizona, 2014. http://hdl.handle.net/10150/338752.

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As the feature size scales down to deep nanometer regimes, it has enabled the designers to fabricate chips with billions of transistors. The availability of such abundant computational resources on a single chip has made it possible to design chips with multiple computational cores, resulting in the inception of Chip Multiprocessors (CMPs). The widespread use of CMPs has resulted in a paradigm shift from computation-centric architectures to communication-centric architectures. With the continuous increase in the number of cores that can be fabricated on a single chip, communication between the

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Books on the topic "Network architectures"

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Network security architectures. Indianapolis, IN: Cisco Press, 2004.

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Tronco, Tania, ed. New Network Architectures. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13247-6.

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David, Hutchison. Local area network architectures. Wokingham, England: Addison-Wesley, 1988.

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Tom, Dell, and Heiberger E. L, eds. Designing AppleTalk network architectures. Boston: AP Professional, 1996.

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Nicopoulos, Chrysostomos, Vijaykrishnan Narayanan, and Chita R. Das. Network-on-Chip Architectures. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-3031-3.

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Bill, Hancock. Network concepts and architectures. Wellesley, Mass: QED Information Sciences, 1989.

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Danny, McPherson, and Cisco Systems Inc, eds. Internet routing architectures. 2nd ed. Indianapolis, Ind: Cisco, 2000.

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Halabi, Bassam. Internet routing architectures. Indianapolis, IN: Cisco Press, 1997.

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Advanced router architectures. Boca Raton, FL: Taylor & Francis, 2006.

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Dayhoff, Judith E. Neural network architectures: An introduction. New York, N.Y: Van Nostrand Reinhold, 1990.

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Book chapters on the topic "Network architectures"

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Ciubotaru, Bogdan, and Gabriel-Miro Muntean. "Network Architectures." In Computer Communications and Networks, 3–28. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5292-7_2.

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Pužman, Josef, and Boris Kubín. "Network Architectures." In Public Data Networks, 43–123. London: Springer London, 1992. http://dx.doi.org/10.1007/978-1-4471-1737-7_4.

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Freer, John R. "Layered network architectures." In Computer Communications and Networks, 133–70. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1041-9_5.

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Haas, Zygmunt. "Optical Network Architectures." In High Performance Networks, 85–107. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-3194-4_4.

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Goda, Kazuo. "Storage Network Architectures." In Encyclopedia of Database Systems, 3741–45. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_1327.

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Goda, Kazuo. "Storage Network Architectures." In Encyclopedia of Database Systems, 2812–15. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_1327.

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Goda, Kazuo. "Storage Network Architectures." In Encyclopedia of Database Systems, 1–5. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_1327-2.

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Wan, Peng-Jun. "WDM Network Architectures." In Network Theory and Applications, 3–30. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5317-5_1.

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Tronco, Tania Regina. "Principles of Internet Architecture." In New Network Architectures, 13–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13247-6_2.

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Tronco, Tania Regina. "A Brief History of the Internet." In New Network Architectures, 1–11. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13247-6_1.

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Conference papers on the topic "Network architectures"

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Kasiviswanathan, Shiva Prasad, Nina Narodytska, and Hongxia Jin. "Network Approximation using Tensor Sketching." 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.2018/321.

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Deep neural networks are powerful learning models that achieve state-of-the-art performance on many computer vision, speech, and language processing tasks. In this paper, we study a fundamental question that arises when designing deep network architectures: Given a target network architecture can we design a `smaller' network architecture that 'approximates' the operation of the target network? The question is, in part, motivated by the challenge of parameter reduction (compression) in modern deep neural networks, as the ever increasing storage and memory requirements of these networks pose a

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Paparistodimou, G., A. Duffy, P. Knight, I. Whitfield, M. Robb, and C. Voong. "Network-based metrics for assessment of naval distributed system architectures." In 14th International Naval Engineering Conference and Exhibition. IMarEST, 2018. http://dx.doi.org/10.24868/issn.2515-818x.2018.030.

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The architecture of a system is generally established at the end of the conceptual design phase where sixty to eighty percent of the lifetime system costs are committed. The architecture influences the system’s complexity, integrality, modularity and robustness. However, such properties of system architecture are not typically analytically evaluated early on during the conceptual process. System architectures are defined using qualitative experience, and the early stage decisions are subject to the judgement of stakeholders. This article suggests a set of network-based metrics that can potenti

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Gao, Yang, Hong Yang, Peng Zhang, Chuan Zhou, and Yue Hu. "Graph Neural Architecture Search." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/195.

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Graph neural networks (GNNs) emerged recently as a powerful tool for analyzing non-Euclidean data such as social network data. Despite their success, the design of graph neural networks requires heavy manual work and domain knowledge. In this paper, we present a graph neural architecture search method (GraphNAS) that enables automatic design of the best graph neural architecture based on reinforcement learning. Specifically, GraphNAS uses a recurrent network to generate variable-length strings that describe the architectures of graph neural networks, and trains the recurrent network with polic

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Jaeger, Monika. "Network Architectures for Future Optical Networks." In 2006 International Conference on Transparent Optical Networks. IEEE, 2006. http://dx.doi.org/10.1109/icton.2006.248262.

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Moreira, Rodrigo, Larissa Rodrigues, Pedro Rosa, and Flávio Silva. "Improving the network traffic classification using the Packet Vision approach." In Workshop de Visão Computacional. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/wvc.2020.13496.

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The network traffic classification allows improving the management, and the network services offer taking into account the kind of application. The future network architectures, mainly mobile networks, foresee intelligent mechanisms in their architectural frameworks to deliver application-aware network requirements. The potential of convolutional neural networks capabilities, widely exploited in several contexts, can be used in network traffic classification. Thus, it is necessary to develop methods based on the content of packets transforming it into a suitable input for CNN technologies. Hen

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Wosinska, Lena. "Optical Network Architectures for Datacenters." In Photonic Networks and Devices. Washington, D.C.: OSA, 2017. http://dx.doi.org/10.1364/networks.2017.new2b.1.

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Lu, Zhichao, Ian Whalen, Yashesh Dhebar, Kalyanmoy Deb, Erik Goodman, Wolfgang Banzhaf, and Vishnu Naresh Boddeti. "NSGA-Net: Neural Architecture Search using Multi-Objective Genetic Algorithm (Extended Abstract)." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/659.

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Convolutional neural networks (CNNs) are the backbones of deep learning paradigms for numerous vision tasks. Early advancements in CNN architectures are primarily driven by human expertise and elaborate design. Recently, neural architecture search (NAS) was proposed with the aim of automating the network design process and generating task-dependent architectures. This paper introduces NSGA-Net -- an evolutionary search algorithm that explores a space of potential neural network architectures in three steps, namely, a population initialization step that is based on prior-knowledge from hand-cra

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Pacharintanakul, Peera, and David Tipper. "Differentiated crosslayer network mapping in multilayered network architectures." In 2010 14th International Telecommunications Network Strategy and Planning Symposium (NETWORKS). IEEE, 2010. http://dx.doi.org/10.1109/netwks.2010.5624908.

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Suganuma, Masanori, Shinichi Shirakawa, and Tomoharu Nagao. "A Genetic Programming Approach to Designing Convolutional Neural Network Architectures." 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.2018/755.

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We propose a method for designing convolutional neural network (CNN) architectures based on Cartesian genetic programming (CGP). In the proposed method, the architectures of CNNs are represented by directed acyclic graphs, in which each node represents highly-functional modules such as convolutional blocks and tensor operations, and each edge represents the connectivity of layers. The architecture is optimized to maximize the classification accuracy for a validation dataset by an evolutionary algorithm. We show that the proposed method can find competitive CNN architectures compared with state

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Natarajan, Anirudh, Mehul Motani, Buddhika de Silva, Kok-Kiong Yap, and K. C. Chua. "Investigating network architectures for body sensor networks." In the 1st ACM SIGMOBILE international workshop. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1248054.1248061.

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Reports on the topic "Network architectures"

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Getbehead, Mark A., James B. Rosetti, Wesley E. Foor, and Samuel P. Kozaitis. Optical Neural Network Classifier Architectures. Fort Belvoir, VA: Defense Technical Information Center, April 1998. http://dx.doi.org/10.21236/ada345879.

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Arcia-Moret, A., B. Braem, E. Pietrosemoli, A. Sathiaseelan, and M. Zennaro. Alternative Network Deployments: Taxonomy, Characterization, Technologies, and Architectures. Edited by J. Saldana. RFC Editor, August 2016. http://dx.doi.org/10.17487/rfc7962.

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Srikant, R. Optimization-Based Wireless Network Architectures: Complexity, Decentralization and Performance Guarantees. Fort Belvoir, VA: Defense Technical Information Center, April 2011. http://dx.doi.org/10.21236/ada564105.

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Lenahan, Jack. Are Service Oriented Architectures the Only Valid Architectural Approach for the Transformation to Network Centric Warfare? (Briefing Charts). Fort Belvoir, VA: Defense Technical Information Center, June 2004. http://dx.doi.org/10.21236/ada462299.

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Lenahan, Jack. The Data Warehouse in Service Oriented Architectures and Network Centric Warfare (Briefing Charts). Fort Belvoir, VA: Defense Technical Information Center, June 2004. http://dx.doi.org/10.21236/ada464283.

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Kuhfeld, J., J. Johnson, and M. Thatcher. Definitions of Managed Objects for Synchronous Optical Network (SONET) Linear Automatic Protection Switching (APS) Architectures. RFC Editor, March 2003. http://dx.doi.org/10.17487/rfc3498.

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Medard, Muriel, Steven Lumetta, and Liuyang Li. A Network Management Architecture for Robust Packet Routing in Optical Access Networks. Fort Belvoir, VA: Defense Technical Information Center, March 2001. http://dx.doi.org/10.21236/ada491806.

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Barto, Andrew. Adaptive Neural Network Architecture. Fort Belvoir, VA: Defense Technical Information Center, October 1987. http://dx.doi.org/10.21236/ada190114.

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McDonnell, John R., and Don Waagen. Evolving Neural Network Architecture. Fort Belvoir, VA: Defense Technical Information Center, March 1993. http://dx.doi.org/10.21236/ada264802.

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PREDICTION SYSTEMS INC SPRING LAKE NJ. Network Simulation of Technical Architecture. Fort Belvoir, VA: Defense Technical Information Center, December 1997. http://dx.doi.org/10.21236/ada335257.

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