Relevant bibliographies by topics / Networks and systems

Academic literature on the topic 'Networks and systems'

Author: Grafiati
Published: 10 December 2022
Last updated: 4 July 2023

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Journal articles on the topic "Networks and systems"

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Anno, Junpei, Leonard Barolli, Arjan Durresi, Fatos Xhafa, and Akio Koyama. "Performance Evaluation of Two Fuzzy-Based Cluster Head Selection Systems for Wireless Sensor Networks." Mobile Information Systems 4, no. 4 (2008): 297–312. http://dx.doi.org/10.1155/2008/876212.

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Sensor networks supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities are emerging as a critically important computer class that enable novel and low cost applications. There are many fundamental problems that sensor networks research will have to address in order to ensure a reasonable degree of cost and system quality. Cluster formation and cluster head selection are important problems in sensor network applications and can drastically affect the network's communication energy dissipation. However, selecting of the cluster head is not easy in different environments which may have different characteristics. In this paper, in order to deal with this problem, we propose two fuzzy-based systems for cluster head selection in sensor networks. We call these systems: FCHS System1 and FCHS System2. We evaluate the proposed systems by simulations and have shown that FCHS System2 make a good selection of the cluster head compared with FCHS System1 and another previous system.
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Best, Allan, Alex Berland, Trisha Greenhalgh, Ivy L. Bourgeault, Jessie E. Saul, and Brittany Barker. "Networks as systems." Journal of Health Organization and Management 32, no. 1 (March 19, 2018): 9–24. http://dx.doi.org/10.1108/jhom-06-2017-0129.

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Purpose The purpose of this paper is to present a case study of the World Health Organization’s Global Healthcare Workforce Alliance (GHWA). Based on a commissioned evaluation of GHWA, it applies network theory and key concepts from systems thinking to explore network emergence, effectiveness, and evolution to over a ten-year period. The research was designed to provide high-level strategic guidance for further evolution of global governance in human resources for health (HRH). Design/methodology/approach Methods included a review of published literature on HRH governance and current practice in the field and an in-depth case study whose main data sources were relevant GHWA background documents and key informant interviews with GHWA leaders, staff, and stakeholders. Sampling was purposive and at a senior level, focusing on board members, executive directors, funders, and academics. Data were analyzed thematically with reference to systems theory and Shiffman’s theory of network development. Findings Five key lessons emerged: effective management and leadership are critical; networks need to balance “tight” and “loose” approaches to their structure and processes; an active communication strategy is key to create and maintain support; the goals, priorities, and membership must be carefully focused; and the network needs to support shared measurement of progress on agreed-upon goals. Shiffman’s middle-range network theory is a useful tool when guided by the principles of complex systems that illuminate dynamic situations and shifting interests as global alliances evolve. Research limitations/implications This study was implemented at the end of the ten-year funding cycle. A more continuous evaluation throughout the term would have provided richer understanding of issues. Experience and perspectives at the country level were not assessed. Practical implications Design and management of large, complex networks requires ongoing attention to key issues like leadership, and flexible structures and processes to accommodate the dynamic reality of these networks. Originality/value This case study builds on growing interest in the role of networks to foster large-scale change. The particular value rests on the longitudinal perspective on the evolution of a large, complex global network, and the use of theory to guide understanding.
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Kurths, J., D. Maraun, C. S. Zhou, G. Zamora-Lopez, and Y. Zou. "Dynamics in Complex Systems." European Review 17, no. 2 (May 2009): 357–70. http://dx.doi.org/10.1017/s1062798709000726.

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Over the last decade, we have witnessed the birth of a new movement of interest and research in the study of complex networks. These networks often have irregular structural properties, but also encompass rich dynamics. The interplay between the network topological structure and the associated dynamics attracts a lot of interest. In this research line, we propose a network approach to dealing with complex dynamics, in particular with synchronization dynamics. From the methodological perspective, this approach requires novel ideas from nonlinear sciences, statistical physics and mathematical statistics. Furthermore, we show applications in different disciplines, from earth sciences to brain dynamics. The complex network’s approach is an interdisciplinary topic and could be promising for the understanding of complexity from a systems level.
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Veselý, A., and D. Brechlerová. "Neural networks in intrusion detection systems." Agricultural Economics (Zemědělská ekonomika) 50, No. 1 (February 24, 2012): 35–40. http://dx.doi.org/10.17221/5164-agricecon.

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Security of an information system is its very important property, especially today, when computers are interconnected via internet. Because no system can be absolutely secure, the timely and accurate detection of intrusions is necessary. For this purpose, Intrusion Detection Systems (IDS) were designed. There are two basic models of IDS: misuse IDS and anomaly IDS. Misuse systems detect intrusions by looking for activity that corresponds to the known signatures of intrusions or vulnerabilities. Anomaly systems detect intrusions by searching for an abnormal system activity. Most IDS commercial tools are misuse systems with rule-based expert system structure. However, these techniques are less successful when attack characteristics vary from built-in signatures. Artificial neural networks offer the potential to resolve these problems. As far as anomaly systems are concerned, it is very difficult to build them, because it is difficult to define the normal and abnormal behaviour of a system. Also for building anomaly system, neural networks can be used, because they can learn to discriminate the normal and abnormal behaviour of a system from examples. Therefore, they offer a promising technique for building anomaly systems. This paper presents an overview of the applicability of neural networks in building intrusion systems and discusses advantages and drawbacks of neural network technology.
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Bottoni, Paolo, Anna Labella, and Grzegorz Rozenberg. "Networks of Reaction Systems." International Journal of Foundations of Computer Science 31, no. 01 (January 2020): 53–71. http://dx.doi.org/10.1142/s0129054120400043.

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In this paper, we study the behavior (processes) of reaction systems where the context is not arbitrary, but it has its own structure. In particular, we consider a model where the context for a reaction system originates from a network of reaction systems. Such a network is formalized as a graph with reaction systems residing at its nodes, where each reaction system contributes to defining the context of all its neighbors. This paper provides a framework for investigating the behavior of reaction systems receiving contexts from networks of reaction systems, provides a characterisation of their state sequences, and considers different topologies of context networks.
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Gadasin, Denis V., Andrey V. Shvedov, and Alyona A. Yudin. "CLUSTERING METHODS IN LARGE-SCALE SYSTEMS." SYNCHROINFO JOURNAL 6, no. 5 (2020): 21–24. http://dx.doi.org/10.36724/2664-066x-2020-6-5-21-24.

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Interactions between people, groups, organizations, and biological cells have a relationship character that can be represented as a network. The system properties of such networks, regardless of their physical nature, but clearly determining the performance of networks, create the totality of the real world. Complex networks – are naturally existing networks (graphs) that have complex topological properties. The researchers who participate and also make discoveries in this field come from various Sciences such as mathematics, computer science, physics, sociology, and engineering. Therefore, the results of research carry both theoretical knowledge and practical applications in these Sciences. This paper discusses the definition of complex networks. The main characteristics of complex networks, such as clustering and congestion, are considered. A popular social network is considered as a complex network. The calculation of nodes and links of the considered social network is made. The main types of AI development and training are highlighted.
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RIDER, ANDREW K., TIJANA MILENKOVIĆ, GEOFFREY H. SIWO, RICHARD S. PINAPATI, SCOTT J. EMRICH, MICHAEL T. FERDIG, and NITESH V. CHAWLA. "Networks' characteristics are important for systems biology." Network Science 2, no. 2 (August 2014): 139–61. http://dx.doi.org/10.1017/nws.2014.13.

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AbstractA fundamental goal of systems biology is to create models that describe relationships between biological components. Networks are an increasingly popular approach to this problem. However, a scientist interested in modeling biological (e.g., gene expression) data as a network is quickly confounded by the fundamental problem: how to construct the network? It is fairly easy to construct a network, but is it the network for the problem being considered? This is an important problem with three fundamental issues: How to weight edges in the network in order to capture actual biological interactions? What is the effect of the type of biological experiment used to collect the data from which the network is constructed? How to prune the weighted edges (or what cut-off to apply)? Differences in the construction of networks could lead to different biological interpretations.Indeed, we find that there are statistically significant dissimilarities in the functional content and topology between gene co-expression networks constructed using different edge weighting methods, data types, and edge cut-offs. We show that different types of known interactions, such as those found through Affinity Capture-Luminescence or Synthetic Lethality experiments, appear in significantly varying amounts in networks constructed in different ways. Hence, we demonstrate that different biological questions may be answered by the different networks. Consequently, we posit that the approach taken to build a network can be matched to biological questions to get targeted answers. More study is required to understand the implications of different network inference approaches and to draw reliable conclusions from networks used in the field of systems biology.
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Vishvakarma, Tanmya. "A Review of Modern Computer Networks." International Journal for Research in Applied Science and Engineering Technology 10, no. 9 (September 30, 2022): 368–76. http://dx.doi.org/10.22214/ijraset.2022.46637.

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Abstract: A computer network's principal role is to facilitate the transfer of digital information between computers. An interconnected network of computer equipment is all that constitutes a computer network. Distributing tasks among different machines is frequent in a computer network. Most networks confront substantial threats from attacks on their resources. This research focuses on computer networks. It is only through the establishment of a computer network that this is made possible at all. Nodes include things like computers, cell phones, servers, and other networking gear. Computer networks enable the Internet, as well as the shared use of application and storage servers, printers, and fax machines. Through the use of computer networks, many jobs can be completed. Systems can be classified as open or closed. If you want to connect to the network, the open system is ready to go. Closed systems, on the other hand, require further authentication to connect to other networks.
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He, Liang, and Shouwei Li. "Network Entropy and Systemic Risk in Dynamic Banking Systems." Complexity 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/1852897.

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We investigate network entropy of dynamic banking systems, where interbank networks analyzed include random networks, small-world networks, and scale-free networks. We find that network entropy is positively correlated with the effect of systemic risk in the three kinds of interbank networks and that network entropy in the small-world network is the largest, followed by those in the random network and the scale-free network.
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Jalili, Mahdi. "Network biology: Describing biological systems by complex networks." Physics of Life Reviews 24 (March 2018): 159–61. http://dx.doi.org/10.1016/j.plrev.2017.12.003.

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Dissertations / Theses on the topic "Networks and systems"

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Andresen, Christian André. "Properties of fracture networks and other network systems." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for fysikk, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-5074.

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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
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 I do with all of this non-networked, legacy equipment?" Before overhauling an entire test system, one should look for a way to incorporate the legacy system components into the modern network architecture. Finding a way to integrate the two generations of systems can provide substantial savings in both cost and application development time. This paper discusses the advantages of integrating legacy equipment into a network-based architecture with examples from systems where this approach was utilized.
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Wells, Daniel David. "Network management for community networks." Thesis, Rhodes University, 2010. http://hdl.handle.net/10962/d1006587.

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Community networks (in South Africa and Africa) are often serviced by limited bandwidth network backhauls. Relative to the basic needs of the community, this is an expensive ongoing concern. In many cases the Internet connection is shared among multiple sites. Community networks may also have a lack of technical personnel to maintain a network of this nature. Hence, there is a demand for a system which will monitor and manage bandwidth use, as well as network use. The proposed solution for community networks and the focus within this dissertation, is a system of two parts. A Community Access Point (CAP) is located at each site within the community network. This provides the hosts and servers at that site with access to services on the community network and the Internet, it is the site's router. The CAP provides a web based interface (CAPgui) which allows configuration of the device and viewing of simple monitoring statistics. The Access Concentrator (AC) is the default router for the CAPs and the gateway to the Internet. It provides authenticated and encrypted communication between the network sites. The AC performs several monitoring functions, both for the individual sites and for the upstream Internet connection. The AC provides a means for centrally managing and effectively allocating Internet bandwidth by using the web based interface (ACgui). Bandwidth use can be allocated per user, per host and per site. The system is maintainable, extendable and customisable for different network architectures. The system was deployed successfully to two community networks. The Centre of Excellence (CoE) testbed network is a peri-urban network deployment whereas the Siyakhula Living Lab (SLL) network is a rural deployment. The results gathered conclude that the project was successful as the deployed system is more robust and more manageable than the previous systems.
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Yuan, Fenghua. "Lightweight network management design for wireless sensor networks." Online access for everyone, 2007. http://www.dissertations.wsu.edu/Thesis/Fall2007/F_Yuan_081307.pdf.

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Sandström, Adam, and Nico Klerks. "Evaluation of 6TiSCH network performance for SDN-enabled IoT networks." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-48819.

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Within the Internet of Things (IoT) a need for new IP-compatible communication technologies has grown stronger during the last few years as the need to connect these IoT networks to the Internet has become increasingly more important. In this report, we evaluate IPv6 over the TSCH mode of IEEE 802.15.4e (6TiSCH) with the purpose of observing how different values for the enhanced beacon (EB) period affect certain network metrics such as delay, energy consumption, join time, and throughput. The EB period is a periodic message used in the Time Slotted Channel hopping (TSCH) protocol used to advertise the network. Our goal is to evaluate the effect of different EB periods on the network and determine if there would be a benefit of integrating SDN to change the EB period dynamically. To fulfill our goal, we will evaluate the effect of the change in EB period on the network metrics. This would be an indication that the 6TiSCH network benefits from an integration with SDN. The reason that we would draw this conclusion is because SDN would be capable of predicting the state of the network and from that update the EB period for the 6TiSCH network. Our results indicate that a lower EB period has a positive effect on join times in the network while a longer EB period has a positive effect on the end-to-end delay. Our results display a promising future for future research on the integration of SDN and 6TiSCH.
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Lissai, Gidon. "Assisted GPS solution in cellular networks /." Online version of thesis, 2007. http://hdl.handle.net/1850/3671.

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Kulkarni, Rohan A. "Coolhunting and Coolfarming : harnessing the power of collaborative innovation networks using social network analysis." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90713.

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Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 71-73).
Email, Instant Messaging, Voice Over IP (VOIP) and other means of online communication have become so ubiquitous today that we rarely take a moment to acknowledge how the internet has changed and redefined the ways in which we communicate and collaborate with fellow human beings. The internet has empowered us to collaborate with others in ways that were not possible till just a few years ago. As we communicate and interact with each other and form relationships, we weave intricate Social Networks that can be analyzed and exhibit communication patterns that can be quantified. In this thesis I have applied Social Network Analysis based techniques that constitute Coolhunting (Gloor & Cooper, 2007) to analyze E-Mail and WebEx communications of sales professionals of a large technology company. I have quantified communication patterns and computed metrics of social network prominence such as degree and betweenness centralities using Condor, a Social Network Analysis and Coolhunting software. Several significant correlations between the success of sales professionals and these quantified communication patterns and centrality measures were found. The communication patterns and centralities of the sales professionals exhibited several traits of Collaborative Innovation Networks or COINs (Gloor, 2006). I have assessed the implications of these communication patterns and correlations and applied the concept of Coolfarming (Gloor, 2011 a) to make recommendations to the technology company on how it could leverage the power of these COINs to their advantage. Key Terms: Collaborative Innovation Networks (COINs), Coolhunting, Coolfarming, Social Network Analysis, Condor, E-Mail, WebEx
by Rohan Kulkarni.
S.M. in Engineering and Management
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Woodbury, Nathan Scott. "Network Reconstruction and Vulnerability Analysis of Financial Networks." BYU ScholarsArchive, 2017. https://scholarsarchive.byu.edu/etd/6370.

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Passive network reconstruction is the process of learning a structured (networked) representation of a dynamic system through the use of known information about the structure of the system as well as data collected by observing the inputs into a system along with the resultant outputs. This work demonstrates an improvement on an existing network reconstruction algorithm so that the algorithm is capable of consistently and perfectly reconstructing a network when system inputs and outputs are measured without error. This work then extends the improved network reconstruction algorithm so that it functions even in the presence of noise as well as the situation where inputs into the system are unknown. Furthermore, this work demonstrates the capability of the new extended algorithms by reconstructing financial networks from stock market data, and then performing an analysis to understand the vulnerabilities of the reconstructed network to destabilization through localized attacks. The creation of these improved and extended algorithms has opened many theoretical questions, paving the way for future research into network reconstruction.
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Chung, Haera. "Optimal Network Topologies and Resource Mappings for Heterogeneous Networks-on-Chip." PDXScholar, 2013. https://pdxscholar.library.pdx.edu/open_access_etds/997.

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Communication has become a bottleneck for modern microprocessors and multi-core chips because metal wires don't scale. The problem becomes worse as the number of components increases and chips become bigger. Traditional Systems-on-Chips (SoCs) interconnect architectures are based on shared-bus communication, which can carry only one communication transaction at a time. This limits the communication bandwidth and scalability. Networks-on-Chip (NoC) were proposed as a promising solution for designing large and complex SoCs. The NoC paradigm provides better scalability and reusability for future SoCs, however, long-distance multi-hop communication through traditional metal wires suffers from both high latency and power consumption. A radical solution to address this challenge is to add long-range, low power, and high-bandwidth single-hop links between distant cores. The use of optical or on-chip RF wireless links has been explored in this context. However, all previous work has focused on regular mesh-based metal wire fabrics that were expanded with one or two additional link types only for long-distance communication. In this thesis we address the following main research questions to address the above-mentioned challenges: (1) What library of different link types would represent an optimum in the design space? (2) How would these links be used to design an application-specific NoC architecture? (3) How would applications use the resulting NoC architecture efficiently? We hypothesize that networks with a higher degree of heterogeneity, i.e., three or more link types, will improve the network throughput and consume less energy compared to traditional NoC architectures. In order to verify our hypothesis and to address the research challenges, we design and analyze optimal heterogeneous networks under different realistic traffic models by considering different cost and performance trade-offs in a comprehensive technology-agnostic simulation framework that uses metaheuristic optimization techniques. As opposed to related work, our heterogeneous links can be placed anywhere in the network, which allows to explore the entire search space. The resulting application-specific networks are then analyzed by using complex network techniques, such as community detection and small-worldness, to understand how heterogeneous link types are used to improve the NoCs performance and cost. Next, we use the application-specific networks as a target architecture for other applications. The goal is to evaluate the performance of our new NoCs for applications they have not been designed for by finding optimal resource allocations. Our results show that there is an optimal number of heterogeneous link types for each set of constraints and that networks with three or more heterogeneous link types provide significantly higher throughput along with lower energy consumption compared to both homogeneous link type and regular 2D mesh networks under three different traffic scenarios. Our evolved networks with three different technology-driven link types, namely metal wires, wireless, and optical links, provide 15% more throughput and fourteen times less energy consumption compared to homogeneous link type network. When ten different abstract link types are used in the design, 12% more throughput and 52% less energy consumption are obtained compared to networks with three different technology-driven link types. This shows that heterogeneous NoC designs based on traditional metal wires, wireless, and optical links, occupy a non-optimal spot in the entire design space. Our results further show that heterogeneous NoCs scale up significantly better in terms of performance and cost compared to mesh networks. We uncovered that network communities evolve robustly and that heterogeneous link types are efficiently establishing inter- and intra-subnet connections depending on their link type properties. We also show that mapping an application on our application-specific NoC architecture provides on average 45% more throughput at 70% less energy consumption compared to regular 2D mesh networks. The NoCs are therefore not only good for the application they were designed for, but for a broad range of other applications as well.
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Cheng, King-yip, and 鄭勁業. "Localization in wireless sensor networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B38700189.

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Books on the topic "Networks and systems"

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R, Coover Edwin, ed. Systems network architecture (SNA) networks. Los Alamitos, Calif: IEEE Computer Society Press, 1992.

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Coover, Edwin R. Systems network architecture (SNA) networks. Los Alamitos, Calif: IEEE Computer Society Press, 1992.

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D, Roy Choudhury. Networks and systems. New York: J. Wiley, 1988.

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Newman, M. E. J. Networks: An introduction. Oxford: Oxford University Press, 2010.

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Fodor, György. Signals, systems, and networks. Budapest: Akadémiai Kiadó, 2003.

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Tekinay, Sirin. Next generation wireless networks. New York: Kluwer Academic Publishers, 2002.

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1967-, Tekinay Sirin, ed. Next generation wireless networks. Boston: Kluwer Academic Publishers, 2001.

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Abdelfatteh, Haidine, and Lehnert R, eds. Broadband powerline communications networks: Network design. Chichester, England: Wiley, 2004.

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Tran, Duc-Tan, Gwanggil Jeon, Thi Dieu Linh Nguyen, Joan Lu, and Thu-Do Xuan, eds. Intelligent Systems and Networks. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2094-2.

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Anh, Ngoc Le, Seok-Joo Koh, Thi Dieu Linh Nguyen, Jaime Lloret, and Thanh Tung Nguyen, eds. Intelligent Systems and Networks. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3394-3.

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Book chapters on the topic "Networks and systems"

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Hardy, Daniel, Guy Malléus, and Jean-Noël Méreur. "Information Systems." In Networks, 409–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-55498-8_13.

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Ivanov, Plamen Ch, and Ronny P. Bartsch. "Network Physiology: Mapping Interactions Between Networks of Physiologic Networks." In Understanding Complex Systems, 203–22. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03518-5_10.

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Hardy, Daniel, Guy Malléus, and Jean-Noël Méreur. "Information Systems and NGN." In Networks, 665–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-55498-8_27.

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Bouyssounouse, Bruno, and Joseph Sifakis. "Networks." In Embedded Systems Design, 316–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31973-3_24.

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Danziger, Michael M., Louis M. Shekhtman, Amir Bashan, Yehiel Berezin, and Shlomo Havlin. "Vulnerability of Interdependent Networks and Networks of Networks." In Understanding Complex Systems, 79–99. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23947-7_5.

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Triviño-Cabrera, Alicia, José M. González-González, and José A. Aguado. "Compensation Networks." In Power Systems, 69–100. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26706-3_4.

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Mallach, Efrem G. "Information Networks." In Information Systems, 149–86. Second edition. | Boca Raton, FL : CRC Press, [2020] |: CRC Press, 2020. http://dx.doi.org/10.1201/9780429061011-6.

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Nagurney, Anna, and Stavros Siokos. "Projected Dynamical Systems." In Financial Networks, 74–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59066-5_4.

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Rathore, Heena. "Computer Networks." In Mapping Biological Systems to Network Systems, 11–25. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-29782-8_2.

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Zweig, Katharina Anna. "Are Word-Adjacency Networks Networks?" In Understanding Complex Systems, 153–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-47238-5_7.

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Conference papers on the topic "Networks and systems"

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Lian, F. L., J. R. Moyne, and D. M. Tilbury. "Performance Evaluation of Control Networks for Manufacturing Systems." In ASME 1999 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/imece1999-0116.

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Abstract There are many different networks which have been promoted for use in manufacturing control systems. In this paper, we discuss the features of three candidates: Ethernet (CSMA/CD), ControlNet (Token Bus) and DeviceNet (CAN Bus). We consider how each of these control networks could be used as a communication backbone for a networked control system. A detailed discussion of the medium access control protocol for each network is provided. The medium access control protocol is responsible for providing both the satisfaction of the time-critical/real-time response requirement over the network and the quality and reliability of the communication between devices on the network. For each protocol, we derive the key parameters of the corresponding network when used in a control situation, including bandwidth, magnitude of the expected time delay, and variation in time delays. Simulation results are presented for several different scenarios, and the advantages and disadvantages of each network are summarized.
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Geoghegan, Sean J., Grady McCorkle, Chris Robinson, Gregory Fundyler, Srini Ramaswamy, Mihail Tudoreanu, Remzi Seker, Jamelle Brown, and Mhamed Itmi. "A multi-agent system architecture for cooperative maritime networks." In 2009 3rd Annual IEEE Systems Conference. IEEE, 2009. http://dx.doi.org/10.1109/systems.2009.4815762.

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Jha, Devesh K., Thomas A. Wettergren, and Asok Ray. "Adaptive Optimal Power Trade-Off in Underwater Sensor Networks." In ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-3717.

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Abstract:
In general, sensor networks have two competing objectives: (i) maximization of network performance with respect to the probability of successful search with a specified false alarm rate for a given coverage area, and (ii) maximization of the network’s operational life. In this context, battery-powered sensing systems are operable as long as they can communicate sensed data to the processing nodes. Since both operations of sensing and communication consume energy, judicious use of these operations could effectively improve the sensor network’s lifetime. From these perspectives, the paper presents an adaptive energy management policy that will optimally allocate the available energy between sensing and communication operations at each node to maximize the network performance under specified constraints. With the assumption of fixed total energy for a sensor network operating over a time period, the problem is reduced to identification of a network topology that maximizes the probability of successful detection of targets over a surveillance region. In a two-stage optimization, a genetic algorithm-based meta-heuristic search is first used to efficiently explore the global design space, and then a local pattern search algorithm is used for convergence to an optimal solution. The results of performance evaluation are presented to validate the proposed concept.
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Babiceanu, Radu F. "Systems engineering life-cycle modeling approach to wireless sensor networks." In 2010 4th Annual IEEE Systems Conference. IEEE, 2010. http://dx.doi.org/10.1109/systems.2010.5482330.

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Sirdhar, Prasanna, Asad M. Madni, and Mo Jamshidi. "Multi-Criteria Decision Making and Behavior Assignment in Sensor Networks." In 2007 1st Annual IEEE Systems Conference. IEEE, 2007. http://dx.doi.org/10.1109/systems.2007.374686.

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Barritt, Brian, Kul Bhasin, Wesley Eddy, and Seth Matthews. "Unified approach to modeling & simulation of space communication networks and systems." In 2010 4th Annual IEEE Systems Conference. IEEE, 2010. http://dx.doi.org/10.1109/systems.2010.5482493.

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Anguswamy, Reghu, Maheswaran Thiagarajan, and Cihan H. Dagli. "Systems Methodology and Framework for problem definition in Mobile ad hoc networks." In 2008 2nd Annual IEEE Systems Conference. IEEE, 2008. http://dx.doi.org/10.1109/systems.2008.4519047.

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Black, Jennifer, and Philip Koopman. "System safety as an emergent property in composite systems." In Networks (DSN). IEEE, 2009. http://dx.doi.org/10.1109/dsn.2009.5270316.

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Napoli, Antonio, Nelson Costa, Johannes K. Fischer, João Pedro, Silvio Abrate, Nicola Calabretta, Wladek Forysiak, et al. "Towards multiband optical systems." In Photonic Networks and Devices. Washington, D.C.: OSA, 2018. http://dx.doi.org/10.1364/networks.2018.netu3e.1.

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Ferent, Cristian, Michael Gilberti, and Alex Doboli. "Real-time gas cloud detection by data aggregation in networks of embedded sensors." In 2010 4th Annual IEEE Systems Conference. IEEE, 2010. http://dx.doi.org/10.1109/systems.2010.5482472.

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Reports on the topic "Networks and systems"

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Perdigão, Rui A. P., and Julia Hall. Conceptualizing System-of-Systems for Water Intelligence Networks (SoS4WIN). Meteoceanics, July 2021. http://dx.doi.org/10.46337/210726.

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Nadeau, Joseph H. Pathways, Networks and Systems Medicine Conferences. Office of Scientific and Technical Information (OSTI), November 2013. http://dx.doi.org/10.2172/1107799.

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Plott, Charles R. Experimental Study of Interdependent Systems: Markets and Networks. Fort Belvoir, VA: Defense Technical Information Center, September 2002. http://dx.doi.org/10.21236/ada408933.

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Priebe, C. E., and D. J. Marchette. Experience with Neural Networks at Naval Ocean Systems Center. Fort Belvoir, VA: Defense Technical Information Center, August 1988. http://dx.doi.org/10.21236/ada198923.

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Hirsch, Morris W., Bill Baird, Walter Freeman, and Bernice Gangale. Dynamical Systems, Neural Networks and Cortical Models ASSERT 93. Fort Belvoir, VA: Defense Technical Information Center, November 1994. http://dx.doi.org/10.21236/ada295495.

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Morgan, Nelson, Jerome Feldman, and John Wawrzynek. Accelerator Systems for Neural Networks, Speech, and Related Applications. Fort Belvoir, VA: Defense Technical Information Center, April 1995. http://dx.doi.org/10.21236/ada298954.

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Perdigão, Rui A. P., and Julia Hall. Coevolutionary System-of-Systems ESDI platform and holistic Multi-Hazard Risk Intelligence Networks: Unveiling Next-Generation Systems Intelligence. Synergistic Manifolds, June 2023. http://dx.doi.org/10.46337/230627.

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Loncaric, J. On Statics of Elastic Systems and Networks of Rigid Bodies. Fort Belvoir, VA: Defense Technical Information Center, October 1987. http://dx.doi.org/10.21236/ada452381.

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Zhuang, Y., and J. S. Baras. Identification of Infinite Dimensional Systems via Adaptive Wavelet Neural Networks. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada454923.

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Arcak, Murat. Structure and Input-Output Properties in Networks of Nonlinear Systems. Fort Belvoir, VA: Defense Technical Information Center, August 2014. http://dx.doi.org/10.21236/ada609701.

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