Journal articles: 'Multiple network'

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Šubrt, T. "Multiple criteria network models for project management." Agricultural Economics (Zemědělská ekonomika) 50, No. 2 (February 24, 2012): 71–76. http://dx.doi.org/10.17221/5169-agricecon.

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The aim of the paper is to present one possibility of how to model and solve a resource oriented critical path problem. As a starting point, a single criteria model for critical path finding is shortly mentioned. Lately, more criteria functions for this model are defined. If any project task uses more resources for its completion, its duration usually depends on only one of them – other resources are not fully used. In here defined multiple criteria approach, these dependencies are not assumed. Each criteria function is derived from a theoretical task duration based on a number of units of only one resource and on its importance. Using either linear programming model with aggregated criteria function or simple Excel calculation with Microsoft Project software support, a so-called compromise critical path can be found. On this path, some resources are overallocated and some are underallocated but the total sum of all underallocations and all overallocations is minimized. All resources are used as effectively as possible and the project is as short as possible too.

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Li, Xianyong, Ying Tang, Yajun Du, and Yanjie Li. "Key Node Discovery Algorithm Based on Multiple Relationships and Multiple Features in Social Networks." Mathematical Problems in Engineering 2021 (October 12, 2021): 1–12. http://dx.doi.org/10.1155/2021/1956356.

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The key nodes play important roles in the processes of information propagation and opinion evolution in social networks. Previous work rarely considered multiple relationships and features into key node discovery algorithms at the same time. Based on the relational networks including the forwarding network, replying network, and mentioning network in a social network, this paper first proposes an algorithm of the overlapping user relational network to extract different relational networks with same nodes. Integrated with these relational networks, a multirelationship network is established. Subsequently, a key node discovery (KND) algorithm is presented on the basis of the shortest path, degree centrality, and random walk features in the multirelationship network. The advantages of the proposed KND algorithm are proved by the SIR propagation model and the normalized discounted cumulative gain on the multirelationship networks and single-relation networks. The experiment’s results show that the proposed KND method for finding the key nodes is superior to other baseline methods on different networks.

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Houidi, Ines, Wajdi Louati, Walid Ben Ameur, and Djamal Zeghlache. "Virtual network provisioning across multiple substrate networks." Computer Networks 55, no. 4 (March 2011): 1011–23. http://dx.doi.org/10.1016/j.comnet.2010.12.011.

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Xiao, Ming, Jorg Kliewer, and Mikael Skoglund. "Design of Network Codes for Multiple-User Multiple-Relay Wireless Networks." IEEE Transactions on Communications 60, no. 12 (December 2012): 3755–66. http://dx.doi.org/10.1109/tcomm.2012.091012.110121.

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Chen, Gui Mei, Zhong Gui Ma, Sha Ban, and Narwani Kamleshd. "Network Coding Based Multiple-Hop Efficient Transmission Method for Multiple-User Multiple-Relay Networks." Advanced Materials Research 998-999 (July 2014): 1161–64. http://dx.doi.org/10.4028/www.scientific.net/amr.998-999.1161.

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A transmission method , combining both the bit error diversity and joint network-channel coding, was proposed for multiple-user multiple-hop multiple-relay networks. In the poposed method, an interleaver was designed for the bit error diversity and a novel protocol was devised for random linear network coding. The proposed method as well as other two methods—Method I without channel code and protection and Method II only with protection, was analyzed by deriving performance expressions in terms of packet error rate (PER) and throughput. Moreover, simulations further prove the superiority of the proposed method. Numerical results show that the proposed method gains an improvement in PER compared with Method I & II and keeps highest throughput within certain range of SNR.

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Duckro, Donald E., Dennis W. Quinn, and Samuel J. Gardner. "Neural Network Pruning with Tukey-Kramer Multiple Comparison Procedure." Neural Computation 14, no. 5 (May 1, 2002): 1149–68. http://dx.doi.org/10.1162/089976602753633420.

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Reducing a neural network's complexity improves the ability of the network to generalize future examples. Like an overfitted regression function, neural networks may miss their target because of the excessive degrees of freedom stored up in unnecessary parameters. Over the past decade, the subject of pruning networks produced nonstatistical algorithms like Skeletonization, Optimal Brain Damage, and Optimal Brain Surgeon as methods to remove connections with the least salience. The method proposed here uses the bootstrap algorithm to estimate the distribution of the model parameter saliences. Statistical multiple comparison procedures are then used to make pruning decisions. We show this method compares well with Optimal Brain Surgeon in terms of ability to prune and the resulting network performance.

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Lee, Jaekoo, MyungKeun Yoon, and Song Noh. "Advanced Network Sampling with Heterogeneous Multiple Chains." Sensors 21, no. 5 (March 9, 2021): 1905. http://dx.doi.org/10.3390/s21051905.

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Recently, researchers have paid attention to many types of huge networks such as the Internet of Things, sensor networks, social networks, and traffic networks because of their untapped potential for theoretical and practical outcomes. A major obstacle in studying large-scale networks is that their size tends to increase exponentially. In addition, access to large network databases is limited for security or physical connection reasons. In this paper, we propose a novel sampling method that works effectively for large-scale networks. The proposed approach makes multiple heterogeneous Markov chains by adjusting random-walk traits on the given network to explore the target space efficiently. This approach provides better unbiased sampling results with reduced asymptotic variance within reasonable execution time than previous random-walk-based sampling approaches. We perform various experiments on large networks databases obtained from synthesis to real–world applications. The results demonstrate that the proposed method outperforms existing network sampling methods.

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Xu, Chuanyun, Nanlan Bai, Wenjian Gao, Tian Li, Mengwei Li, Gang Li, and Yang Zhang. "Multiple-Stage Knowledge Distillation." Applied Sciences 12, no. 19 (September 21, 2022): 9453. http://dx.doi.org/10.3390/app12199453.

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Knowledge distillation (KD) is a method in which a teacher network guides the learning of a student network, thereby resulting in an improvement in the performance of the student network. Recent research in this area has concentrated on developing effective definitions of knowledge and efficient methods of knowledge transfer while ignoring the learning ability of the student network. To fully utilize this potential learning ability and improve learning efficiency, this study proposes a multiple-stage KD (MSKD) method that allows students to learn the knowledge delivered by the teacher network in multiple stages. The student network in this method consists of a multi-exit architecture, and the students imitate the output of the teacher network at each exit. The final classification by the student network is achieved through ensemble learning. However, because this results in an unreasonable gap between the number of parameters in the student branch network and those in the teacher branch network, as well as a mismatch in learning capacity between these two networks, we extend the MSKD method to a one-to-one multiple-stage KD method. The experimental results reveal that the proposed method applied to the CIFAR100 and Tiny ImageNet datasets exhibits good performance gain. The proposed method of enhancing KD by changing the style of student learning provides new insight into KD.

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Wang, Zhaocheng, and Jiaxuan Chen. "Networked multiple-input-multiple-output for optical wireless communication systems." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378, no. 2169 (March 2, 2020): 20190189. http://dx.doi.org/10.1098/rsta.2019.0189.

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With the escalation of heterogeneous data traffic, the research on optical wireless communication (OWC) has attracted much attention, owing to its advantages such as wide spectrum, low power consumption and high security. Ubiquitous optical devices, e.g. light-emitting diodes (LEDs) and cameras, are employed to support optical wireless links. Since the distribution of these optical devices is usually dense, multiple-input-multiple-output (MIMO) can be naturally adopted to attain spatial diversity gain or spatial multiplexing gain. As the scale of OWC networks enlarges, optical MIMO can also collaborate with network-level operations, like user/AP grouping, to enhance the network throughput. Since OWC is preferred for short-range communications and is sensitive to the directions/rotations of transceivers, optical MIMO links vary frequently and sharply in outdoor scenarios when considering the mobility of optical devices, raising new challenges to network design. In this work, we present an overview of optical MIMO techniques, as well as the cooperation of MIMO and user/AP grouping in OWC networks. In consideration of the challenges for outdoor OWC, key technologies are then proposed to facilitate the adoption of optical MIMO in outdoor scenarios, especially in vehicular ad hoc networks. Lastly, future applications of MIMO in OWC networks are discussed. This article is part of the theme issue ‘Optical wireless communication’.

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Urbanek, Carsten, Nicholetta Weinges-Evers, Judith Bellmann-Strobl, Markus Bock, Jan Dörr, Eric Hahn, Andres H. Neuhaus, et al. "Attention Network Test reveals alerting network dysfunction in multiple sclerosis." Multiple Sclerosis Journal 16, no. 1 (December 7, 2009): 93–99. http://dx.doi.org/10.1177/1352458509350308.

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Attention is one of the cognitive domains typically affected in multiple sclerosis. The Attention Network Test was developed to measure the function of the three distinct attentional networks, alerting, orienting, and executive control. The Attention Network Test has been performed in various neuropsychiatric conditions, but not in multiple sclerosis. Our objective was to investigate functions of attentional networks in multiple sclerosis by means of the Attention Network Test. Patients with relapsing—remitting multiple sclerosis (n = 57) and healthy controls (n = 57) matched for age, sex, and education performed the Attention Network Test. Significant differences between patients and controls were detected in the alerting network (p = 0.003), in contrast to the orienting (p = 0.696) and the conflict (p = 0.114) network of visual attention. Mean reaction time in the Attention Network Test was significantly longer in multiple sclerosis patients than in controls (p = 0.032), Multiple sclerosis patients benefited less from alerting cues for conflict resolution compared with healthy controls. The Attention Network Test revealed specific alterations of the attention network in multiple sclerosis patients which were not explained by an overall cognitive slowing.

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Lye, K. M. "Two-connected multiple-token multiple-ring network." IEE Proceedings - Communications 142, no. 6 (1995): 369. http://dx.doi.org/10.1049/ip-com:19952279.

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Lu, Lu, Lizhao You, and Soung Chang Liew. "Network-Coded Multiple Access." IEEE Transactions on Mobile Computing 13, no. 12 (December 1, 2014): 2853–69. http://dx.doi.org/10.1109/tmc.2014.2316804.

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Sanchis, L. A. "Multiple-way network partitioning." IEEE Transactions on Computers 38, no. 1 (1989): 62–81. http://dx.doi.org/10.1109/12.8730.

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Bianchi, Federica, Alex Stivala, and Alessandro Lomi. "Multiple clocks in network evolution." Methodological Innovations 15, no. 1 (March 2022): 29–41. http://dx.doi.org/10.1177/20597991221077877.

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Relational event models shift the analytical focus away from network ties defined in terms of transitions between mutually exclusive states of connectivity, to bonding processes emerging from observable flows linking senders and receivers of action. In this framework, the possibility to connect social mechanisms of theoretical interest to sequences of observed relational events depends on the relative speed at which these mechanisms operate. Building on established non-parametric methods in survival analysis, in this paper we introduce a new approach to the analysis of the internal time distribution of relational mechanisms of broad theoretical interest in research on the evolutionary dynamics of social and other kinds of networks. We propose general algorithms that may be adopted to study the time structure of theoretically relevant network mechanisms. We illustrate the practical value of our proposal in an analysis of a large sample of high-frequency financial transactions observed over a period of 11 years. We show how the internal time structure of the social mechanisms that control flows of market transactions is sensitive to institutional change in transaction regimes induced by successive financial crises. The results we report invite reflection on a new notion of network “structure” incorporating change as one of its constitutive elements. The study suggests a number of conjectures that provide broad conceptual bases for the development of testable hypotheses about the forces that shape the evolutionary dynamics of network structure.

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VASYLKIVSKYI, Mykola, Ganna VARGATYUK, and Olha BOLDYREVA. "INTELLIGENT OPTIMIZATION OF MULTIPLE ACCESS INFOCOMMUNICATION NETWORKS." Herald of Khmelnytskyi National University. Technical sciences 315, no. 6 (December 29, 2022): 32–39. http://dx.doi.org/10.31891/2307-5732-2022-315-6(2)-32-39.

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The methods of multiple access with multiplexing of resources are studied and the advantages and disadvantages of orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) are considered. A comparative analysis of data transmission schemes in the radio network was also performed, taking into account resource planning, in particular: transmission with service information and transmission without service information. The structure of the NOMA uplink receiver based on OFDM signals is proposed. The peculiarities of providing supermassive connection within limited radio resources on the basis of grantless access using NOMA have been studied. At the same time, methods of solving the problems inherent in the current application of GF-transmission and NOMA in the implementation of supermassive connection to the access network based on 6G technology were considered. Prospects for the introduction of an artificial intelligence transmitter based on a multiple access transmission scheme with low cost, low PAPR, low delay, high reliability and wide connectivity are determined. And features of artificial intelligence receiver design using artificial intelligence / machine learning techniques that can play a role in facilitating MUD design for NOMA are also considered.

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O’Brien, Liam, and Szeto Wai Yuen. "Designing Reliable Transport Networks: The Multiple Network Spoiler Approach." HKIE Transactions 15, no. 4 (January 2008): 2–10. http://dx.doi.org/10.1080/1023697x.2008.10668126.

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Le, Van-Vang, Toai Kim Tran, Bich-Ngan T. Nguyen, Quoc-Dung Nguyen, and Vaclav Snasel. "Network Alignment across Social Networks Using Multiple Embedding Techniques." Mathematics 10, no. 21 (October 26, 2022): 3972. http://dx.doi.org/10.3390/math10213972.

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Network alignment, which is also known as user identity linkage, is a kind of network analysis task that predicts overlapping users between two different social networks. This research direction has attracted much attention from the research community, and it is considered to be one of the most important research directions in the field of social network analysis. There are many different models for finding users that overlap between two networks, but most of these models use separate and different techniques to solve prediction problems, with very little work that has combined them. In this paper, we propose a method that combines different embedding techniques to solve the network alignment problem. Each association network alignment technique has its advantages and disadvantages, so combining them together will take full advantage and can overcome those disadvantages. Our model combines three-level embedding techniques of text-based user attributes, a graph attention network, a graph-drawing embedding technique, and fuzzy c-mean clustering to embed each piece of network information into a low-dimensional representation. We then project them into a common space by using canonical correlation analysis and compute the similarity matrix between them to make predictions. We tested our network alignment model on two real-life datasets, and the experimental results showed that our method can considerably improve the accuracy by about 10–15% compared to the baseline models. In addition, when experimenting with different ratios of training data, our proposed model could also handle the over-fitting problem effectively.

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Yuping Li, Yuping Li, Sa Meng Yuping Li, Yilin Zhang Sa Meng, Ke Li Yilin Zhang, and Zhanjie Guo Ke Li. "On the Simulation of Communication Protocols with Multiple Mobile Nodes." 網際網路技術學刊 23, no. 4 (July 2022): 771–77. http://dx.doi.org/10.53106/160792642022072304012.

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In this paper, a high-performance routing protocol with multiple mobile nodes based on reliable active nodes is put forward since network nodes are not involved in the reliability work when the existing OSPF routing protocol forwards the packet, which results in several problems such as a low rate of packet forwarding, the long average delay of end-to-end, high energy consumption of network nodes and short service lifetime of nodes. The hierarchical model of active networks with multiple-mobile nodes was built, in which, reliable active nodes were divided into forwarding nodes and reliable nodes based on the functional requirements of this model, and consideration was given both to the efficiency and reliability of packet transmission. Besides, the energy consumption of network communication was calculated on the basis of this model and the packet transmission power was controlled. A high-performance routing protocol with multiple mobile nodes was designed to estimate the packet transmission delay time, calculate the forwarding moderate index of nodes, and select neighbor nodes in the active network. The simulation results show that this routing communication protocol effectively improves the packet forwarding rate, lowers the total energy consumption, shortens the average delay of end-to-end, and extends the service life of network nodes.

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Gao, Yanli, Jun Liu, Haiwei He, Jie Zhou, and Shiming Chen. "Multiple phase transitions in ER edge-coupled interdependent networks." New Journal of Physics 24, no. 2 (February 1, 2022): 023023. http://dx.doi.org/10.1088/1367-2630/ac5055.

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Abstract Considering the real-world scenarios that there are interactions between edges in different networks and each network has different topological structure and size, we introduce a model of interdependent networks with arbitrary edge-coupling strength, in which q A and q B are used to represent the edge-coupling strength of network A and network B respectively. A mathematical framework using generating functions is developed based on self-consistent probabilities approach, which is verified by computer simulations. In particular, we carry out this mathematical framework on the Erdös–Rényi edge-coupled interdependent networks to calculate the values of phase transition thresholds and the critical coupling strengths which distinguish different types of transitions. Moreover, as contrast to the corresponding node-coupled interdependent networks, we find that for edge-coupled interdependent networks the critical coupling strengths are smaller, and the critical thresholds as well, which means the robustness of partially edge-coupled interdependent networks is better than that of partially node-coupled interdependent networks. Furthermore, we find that network A will have hybrid percolation behaviors as long as the coupling strength q A belongs to a certain range, and the range does not affected by average degree of network A. Our findings may fill the gap of understanding the robustness of edge-coupled interdependent networks with arbitrary coupling strength, and have significant meaning for network security design and optimization.

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Basavaraj, Veeresh Varad, Venkateswaran Shekar, Lance Fiondella, Ashrafur Rahman, and Nicholas Lownes. "Algorithm to prioritize the restoration of a multiple facility, multiple-hazard road network." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 231, no. 3 (March 9, 2017): 221–31. http://dx.doi.org/10.1177/1748006x17693484.

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Transportation networks are one of several critical infrastructures on which first responders rely in order to deliver emergency services. However, there is no guarantee that a transportation network will be fully operational following a regional event, such as a hurricane or earthquake. Emergency planning and response tools should explicitly integrate this possibility to ensure the completeness of the risk assessment process. This paper considers the elevated vulnerability to which a community is exposed when disruptions in a transportation network slow emergency response. An average weighted vulnerability metric is defined to favor a network restoration strategy that quickly reduces emergency response times to their nominal levels. This metric is incorporated into an algorithm to prioritize network restoration, so that individuals who might require assistance are not exposed to prolonged periods of lengthy response times. The formulation considers a number of types of emergency response facilities and different types of hazard; the hazards can require a response from more than one type of facility. The utility of the approach is illustrated through a series of examples. Our results demonstrate that the approach can offer systematic guidance to reduce emergency response times after a partial or complete outage of a transportation network.

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Liu, Kai, William K. Cheung, and Jiming Liu. "Detecting multiple stochastic network motifs in network data." Knowledge and Information Systems 42, no. 1 (August 29, 2013): 49–74. http://dx.doi.org/10.1007/s10115-013-0680-4.

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Gao, Jianxi, Daqing Li, and Shlomo Havlin. "From a single network to a network of networks." National Science Review 1, no. 3 (July 16, 2014): 346–56. http://dx.doi.org/10.1093/nsr/nwu020.

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Abstract Network science has attracted much attention in recent years due to its interdisciplinary applications. We witnessed the revolution of network science in 1998 and 1999 started with small-world and scale-free networks having now thousands of high-profile publications, and it seems that since 2010 studies of ‘network of networks’ (NON), sometimes called multilayer networks or multiplex, have attracted more and more attention. The analytic framework for NON yields a novel percolation law for n interdependent networks that shows that percolation theory of single networks studied extensively in physics and mathematics in the last 50 years is a specific limit of the rich and very different general case of n coupled networks. Since then, properties and dynamics of interdependent and interconnected networks have been studied extensively, and scientists are finding many interesting results and discovering many surprising phenomena. Because most natural and engineered systems are composed of multiple subsystems and layers of connectivity, it is important to consider these features in order to improve our understanding of such complex systems. Now the study of NON has become one of the important directions in network science. In this paper, we review recent studies on the new emerging area—NON. Due to the fast growth of this field, there are many definitions of different types of NON, such as interdependent networks, interconnected networks, multilayered networks, multiplex networks and many others. There exist many datasets that can be represented as NON, such as network of different transportation networks including flight networks, railway networks and road networks, network of ecological networks including species interacting networks and food webs, network of biological networks including gene regulation network, metabolic network and protein–protein interacting network, network of social networks and so on. Among them, many interdependent networks including critical infrastructures are embedded in space, introducing spatial constraints. Thus, we also review the progress on study of spatially embedded networks. As a result of spatial constraints, such interdependent networks exhibit extreme vulnerabilities compared with their non-embedded counterparts. Such studies help us to understand, realize and hopefully mitigate the increasing risk in NON.

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Khalil, Ahmed Salih Ahmed, and Prof Kalid Hamid B. Abdallah. "Multiple-Input Multiple-Output of Wimax Network: Review." IOSR Journal of Electronics and Communication Engineering 12, no. 02 (May 2017): 81–87. http://dx.doi.org/10.9790/2834-1202038187.

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Crivelli, Lucía, Mauricio F. Farez, Claudio D. González, Marcela Fiol, Alejandra Amengual, Ramón Leiguarda, and Jorge Correale. "Alerting Network Dysfunction in Early Multiple Sclerosis." Journal of the International Neuropsychological Society 18, no. 4 (May 24, 2012): 757–63. http://dx.doi.org/10.1017/s1355617712000410.

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AbstractThe objective of this study is to assess attention in recently diagnosed relapsing-remitting multiple sclerosis patients. Twenty-seven patients with early multiple sclerosis and low clinical disability scores (EDSS<2) and 27 sex-, age-, and education-matched healthy controls underwent attention assessment using the Attentional Network Test, a computerized task designed to measure efficiency independently in 3 attentional networks (Alerting, Orienting and Executive Control). MS patients had significantly less efficiency in the Alerting network (p = .006). In contrast, in the Orienting and Executive Control networks, they did not differ from controls. A significant interaction between Alerting and Executive Control was also found in the MS patients (p = .007). Early relapsing-remitting multiple sclerosis particularly affects the Alerting domain of attention, whereas the Orienting and Executive Control domains are not affected. (JINS, 2012, 18, 1–7)

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Lin, Yi-Kuei, and Louis Cheng-Lu Yeng. "Evaluation of Network Reliability for Computer Networks with Multiple Sources." Mathematical Problems in Engineering 2012 (2012): 1–18. http://dx.doi.org/10.1155/2012/737562.

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Evaluating the reliability of a network with multiple sources to multiple sinks is a critical issue from the perspective of quality management. Due to the unrealistic definition of paths of network models in previous literature, existing models are not appropriate for real-world computer networks such as the Taiwan Advanced Research and Education Network (TWAREN). This paper proposes a modified stochastic-flow network model to evaluate the network reliability of a practical computer network with multiple sources where data is transmitted through several light paths (LPs). Network reliability is defined as being the probability of delivering a specified amount of data from the sources to the sink. It is taken as a performance index to measure the service level of TWAREN. This paper studies the network reliability of the international portion of TWAREN from two sources (Taipei and Hsinchu) to one sink (New York) that goes through a submarine and land surface cable between Taiwan and the United States.

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ARBESMAN, SAMUEL, STEVEN H. STROGATZ, and MICHAEL S. VITEVITCH. "THE STRUCTURE OF PHONOLOGICAL NETWORKS ACROSS MULTIPLE LANGUAGES." International Journal of Bifurcation and Chaos 20, no. 03 (March 2010): 679–85. http://dx.doi.org/10.1142/s021812741002596x.

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The network characteristics based on the phonological similarities in the lexicons of several languages were examined. These languages differed widely in their history and linguistic structure, but commonalities in the network characteristics were observed. These networks were also found to be different from other networks studied in the literature. The properties of these networks suggest explanations for various aspects of linguistic processing and hint at deeper organization within the human language.

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Laishram, Ricky, Jeremy D. Wendt, and Sucheta Soundarajan. "Crawling the Community Structure of Multiplex Networks." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 168–75. http://dx.doi.org/10.1609/aaai.v33i01.3301168.

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We examine the problem of crawling the community structure of a multiplex network containing multiple layers of edge relationships. While there has been a great deal of work examining community structure in general, and some work on the problem of sampling a network to preserve its community structure, to the best of our knowledge, this is the first work to consider this problem on multiplex networks. We consider the specific case in which the layers of a multiplex network have different query (collection) costs and reliabilities; and a data collector is interested in identifying the community structure of the most expensive layer. We propose MultiComSample (MCS), a novel algorithm for crawling a multiplex network. MCS uses multiple levels of multi-armed bandits to determine the best layers, communities and node roles for selecting nodes to query. We test MCS against six baseline algorithms on real-world multiplex networks, and achieved large gains in performance. For example, after consuming a budget equivalent to sampling 20% of the nodes in the expensive layer, we observe that MCS outperforms the best baseline by up to 49%.

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Han, Siyao, and Yan Xu. "Link Prediction in Microblog Network Using Supervised Learning with Multiple Features." Journal of Computers 11, no. 1 (January 2016): 72–82. http://dx.doi.org/10.17706/jcp.11.1.72-82.

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Rajan, C. Sakthi Gokul, and Ravi K. "Optimal Allocation of Multiple DSTATCOM in Distribution Network Using Chaotic WOA." Journal of Advanced Research in Dynamical and Control Systems 11, no. 11-SPECIAL ISSUE (February 20, 2019): 569–76. http://dx.doi.org/10.5373/jardcs/v11sp11/20193068.

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Trojano, M., D. Paolicelli, V. Lepore, A. Fuiani, E. Di Monte, F. Pellegrini, P. Russo, P. Livrea, and G. Comi. "Italian Multiple Sclerosis Database Network." Neurological Sciences 27, S5 (September 2006): s358—s361. http://dx.doi.org/10.1007/s10072-006-0694-8.

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Ho, W. Wilson, and Biswanath Mukherjee. "Multiple-partition token ring network." Computer Communications 14, no. 3 (April 1991): 133–42. http://dx.doi.org/10.1016/0140-3664(91)90065-9.

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Gupta, A. K., and S. E. Hambrusch. "Multiple Network Embeddings into Hypercubes." Journal of Parallel and Distributed Computing 19, no. 2 (October 1993): 73–82. http://dx.doi.org/10.1006/jpdc.1993.1092.

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Fleischer, Vinzenz, Nabin Koirala, Amgad Droby, René-Maxime Gracien, Ralf Deichmann, Ulf Ziemann, Sven G. Meuth, Muthuraman Muthuraman, Frauke Zipp, and Sergiu Groppa. "Longitudinal cortical network reorganization in early relapsing–remitting multiple sclerosis." Therapeutic Advances in Neurological Disorders 12 (January 2019): 175628641983867. http://dx.doi.org/10.1177/1756286419838673.

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Background: Network science provides powerful access to essential organizational principles of the brain. The aim of this study was to investigate longitudinal evolution of gray matter networks in early relapsing–remitting MS (RRMS) compared with healthy controls (HCs) and contrast network dynamics with conventional atrophy measurements. Methods: For our longitudinal study, we investigated structural cortical networks over 1 year derived from 3T MRI in 203 individuals (92 early RRMS patients with mean disease duration of 12.1 ± 14.5 months and 101 HCs). Brain networks were computed based on cortical thickness inter-regional correlations and fed into graph theoretical analysis. Network connectivity measures (modularity, clustering coefficient, local efficiency, and transitivity) were compared between patients and HCs, and between patients with and without disease activity. Moreover, we calculated longitudinal brain volume changes and cortical atrophy patterns. Results: Our analyses revealed strengthening of local network properties shown by increased modularity, clustering coefficient, local efficiency, and transitivity over time. These network dynamics were not detectable in the cortex of HCs over the same period and occurred independently of patients’ disease activity. Most notably, the described network reorganization was evident beyond detectable atrophy as characterized by conventional morphometric methods. Conclusion: In conclusion, our findings provide evidence for gray matter network reorganization subsequent to clinical disease manifestation in patients with early RRMS. An adaptive cortical response with increased local network characteristics favoring network segregation could play a primordial role for maintaining brain function in response to neuroinflammation.

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Xiao, Yunpeng, Li Zhang, Qian Li, and Ling Liu. "MM-SIS: Model for multiple information spreading in multiplex network." Physica A: Statistical Mechanics and its Applications 513 (January 2019): 135–46. http://dx.doi.org/10.1016/j.physa.2018.08.169.

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Ugare, Shubham, Gagandeep Singh, and Sasa Misailovic. "Proof transfer for fast certification of multiple approximate neural networks." Proceedings of the ACM on Programming Languages 6, OOPSLA1 (December 8, 2022): 1–29. http://dx.doi.org/10.1145/3527319.

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Developers of machine learning applications often apply post-training neural network optimizations, such as quantization and pruning, that approximate a neural network to speed up inference and reduce energy consumption, while maintaining high accuracy and robustness. Despite a recent surge in techniques for the robustness verification of neural networks, a major limitation of almost all state-of-the-art approaches is that the verification needs to be run from scratch every time the network is even slightly modified. Running precise end-to-end verification from scratch for every new network is expensive and impractical in many scenarios that use or compare multiple approximate network versions, and the robustness of all the networks needs to be verified efficiently. We present FANC, the first general technique for transferring proofs between a given network and its multiple approximate versions without compromising verifier precision. To reuse the proofs obtained when verifying the original network, FANC generates a set of templates – connected symbolic shapes at intermediate layers of the original network – that capture the proof of the property to be verified. We present novel algorithms for generating and transforming templates that generalize to a broad range of approximate networks and reduce the verification cost. We present a comprehensive evaluation demonstrating the effectiveness of our approach. We consider a diverse set of networks obtained by applying popular approximation techniques such as quantization and pruning on fully-connected and convolutional architectures and verify their robustness against different adversarial attacks such as adversarial patches, L 0 , rotation and brightening. Our results indicate that FANC can significantly speed up verification with state-of-the-art verifier, DeepZ by up to 4.1x.

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Xie, Jing, Binggeng Xie, Kaichun Zhou, Junhan Li, Jianyong Xiao, Changchang Liu, and Xuemao Zhang. "Multiple Probability Ecological Network and County-Scale Management." Land 12, no. 8 (August 14, 2023): 1600. http://dx.doi.org/10.3390/land12081600.

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Ecological networks are threatened by rapid urbanization; the implementation of ecological network management and maintenance strategies is essential in the county units of urban agglomerations. This study focused on the Changsha–Zhuzhou–Xiangtan urban agglomeration (CZXUA) and objectively identified and evaluated the regional ecological networks. Connectivity distance thresholds were determined using goodness-of-fit experiments. The Probability of becoming an Ecological Source (PES) was constructed to investigate the ecological networks at different probabilities, and the network weight in each county was analyzed based on the gravity model. The results show that: (1) The distance thresholds were 2500, 2700, and 2300 m in 2000, 2010, and 2020, respectively. Source degradation and corridor disconnection were most significant at a PES > 50%. (2) At a PES > 50%, the high gravitational value increased from 39,972 to 31,4642, owing to fragmentation. Fourteen counties received weights, and fluctuations were most significant at a PES > 90%. (3) The trends in the PES and gravitational value were not always synergistic, and the negative impact of source degradation on the gravitational value was significantly less than the positive impact of the reduced distance between sources. The gravity center movement under the high PES determined the ecological network status of neighboring counties. The findings can quantify ecological information flow and provide a basis for county ecological management and restoration.

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Tu, Xiao, Guo-Ping Jiang, Yurong Song, and Xiaoling Wang. "Control of Multiple Viruses Interacting and Propagating in Multilayer Networks." Mathematical Problems in Engineering 2020 (July 10, 2020): 1–14. http://dx.doi.org/10.1155/2020/9014353.

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Experimental studies involving control against virus propagation have attracted the interest of scientists. However, most accomplishments have been constrained by the simple assumption of a single virus in various networks, but this assumption apparently conflicts with recent developments in complex network theory, which details that each node might play multiple roles in different topological connections. Multiple viruses propagate through individuals via different routes, and thus, each individual component could be located in various positions of differing importance in each virus propagation process in each network. Therefore, we propose several control strategies for establishing a multiple-virus interaction and propagation model involving multiplex networks, including a novel Multiplex PageRank target control model and a multiplex random control model. Using computer experiments and simulations derived from actual examples, we exploit several actual cases to determine the relationship of the relative infection probability with the immunization probability. The results demonstrate the differences between our multiple-virus interaction and propagation model and the single-virus propagation model and verify the effectiveness of our novel Multiplex PageRank target control strategy. Moreover, we use parallel computing for simulating and identifying the relationships of the immunization thresholds with both interaction coefficients, which is beneficial for further practical applications because it can reduce the multiple interactions between viruses and allows achieving a greater effect through the immunization of fewer nodes in the multilayer networks.

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Al-sharoa, Esraa, Mohammad Al-wardat, Mahmood Al-khassaweneh, and Ali Al Bataineh. "Discovering Community Structure in Multiplex Networks via a Co-Regularized Robust Tensor-Based Spectral Approach." Applied Sciences 13, no. 4 (February 15, 2023): 2514. http://dx.doi.org/10.3390/app13042514.

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Complex networks arise in various fields, such as biology, sociology and communication, to model interactions among entities. Entities in many real-world systems exhibit different types of interactions, which requires modeling these type of systems properly. Multiplex networks are used to model these systems, as they can reflect the nodes’ pair-wise interactions as multiple distinct types of links across layers. Community detection is a widely studied application in network analysis as it provides insights into the structure and organization of the network. Even though multiple algorithms have been developed in the community detection field, many of them have a limited performance in the presence of noise. In this article, we develop a novel algorithm that combines tensor low-rank representation, spectral clustering and distance regularization to improve the accuracy in discovering communities in multiplex networks. The low-rank representation leads to reducing the noise and errors existing in the network and the optimization of an accurate consensus set of eigenvectors that reveals the communities in the network. Moreover, the proposed approach balances the agreement between the eigenvectors of each layer, i.e., individual subspaces, and the consensus set of eigenvectors, i.e., common subspaces, by minimizing the projection distance between them. The common and individual subspaces are computed efficiently through Tucker decomposition and modified spectral clustering, respectively. Finally, multiple experiments are conducted on real and simulated networks to evaluate the proposed approach and compare it to state-of-the-art algorithms. The proposed approach shows its robustness and efficiency in discovering the communities in multiplex networks.

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Huang, Zongwen, Lingyu Xu, Lei Wang, Gaowei Zhang, and Yaya Liu. "Construction of Complex Network with Multiple Time Series Relevance." Information 9, no. 8 (August 7, 2018): 202. http://dx.doi.org/10.3390/info9080202.

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Multivariate time series data, which comprise a set of ordered observations for multiple variables, are pervasively generated in weather conditions, traffic, financial stocks, etc. Therefore, it is of great significance to analyze the correlation between multiple time series. Financial stocks generate a significant amount of multivariate time series data that can be used to build networks that reflect market behavior. However, traditional commercial complex networks cannot fully utilize the multiple attributes of stocks and redundant filter relationships and reveal a more authentic financial stock market. We propose a fusion similarity of multiple time series and construct a threshold network with similarity. Furthermore, we define the connectivity efficiency to choose the best threshold, establishing a high connectivity efficiency network with the optimal network threshold. By searching the central node in the threshold network, we have found that the network center nodes constructed by our proposed method have a more comprehensive industry coverage than the traditional techniques to build the systems, and this also proves the superiority of this method.

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Annavajjala, Ramesh, Amine Maaref, and Jinyun Zhang. "Multiantenna Analog Network Coding for Multihop Wireless Networks." International Journal of Digital Multimedia Broadcasting 2010 (2010): 1–10. http://dx.doi.org/10.1155/2010/368562.

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This paper proposes a two-phase minimum mean-square-error bidirectional amplify-and forward (MMSE-BAF) relaying protocol to allow two sources exchange independent messages via a relay node equipped with multiple antennas. MMSE-BAF performs a joint linear MMSE filtering of the received signal after the multiple access phase before amplifying and forwarding the filtered signal using a single transmit antenna, possibly through a specific antenna selection procedure, during the broadcast phase. The proposed protocol extends upon the so-called analog network coding schemes in the literature in that it inherently exploits the multiple antennas at the relay station to reduce the noise enhancement typical of an AF protocol, and can also compensate for link imbalances between the relay and the sources and is agnostic to sources' modulation and coding schemes. We derive the instantaneous signal-to-noise ratio expressions for the received signal by the sources in the downlink and provide extensive link-level simulations for the MMSE-BAF protocol subject to both frequency flat and selective fading. Furthermore, we pinpoint the modifications to be incorporated into the IEEE 802.16e orthogonal-frequency-division multiple access (OFDMA) cellular standard (mobile WiMax) to enable support of multiantenna bidirectional communications and show that MMSE-BAF is a viable solution within that framework.

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Melamud, Mark M., Evgeny A. Ermakov, Anastasiia S. Boiko, Daria A. Kamaeva, Alexey E. Sizikov, Svetlana A. Ivanova, Natalia M. Baulina, Olga O. Favorova, Georgy A. Nevinsky, and Valentina N. Buneva. "Multiplex Analysis of Serum Cytokine Profiles in Systemic Lupus Erythematosus and Multiple Sclerosis." International Journal of Molecular Sciences 23, no. 22 (November 10, 2022): 13829. http://dx.doi.org/10.3390/ijms232213829.

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Changes in cytokine profiles and cytokine networks are known to be a hallmark of autoimmune diseases, including systemic lupus erythematosus (SLE) and multiple sclerosis (MS). However, cytokine profiles research studies are usually based on the analysis of a small number of cytokines and give conflicting results. In this work, we analyzed cytokine profiles of 41 analytes in patients with SLE and MS compared with healthy donors using multiplex immunoassay. The SLE group included treated patients, while the MS patients were drug-free. Levels of 11 cytokines, IL-1b, IL-1RA, IL-6, IL-9, IL-10, IL-15, MCP-1/CCL2, Fractalkine/CX3CL1, MIP-1a/CCL3, MIP-1b/CCL4, and TNFa, were increased, but sCD40L, PDGF-AA, and MDC/CCL22 levels were decreased in SLE patients. Thus, changes in the cytokine profile in SLE have been associated with the dysregulation of interleukins, TNF superfamily members, and chemokines. In the case of MS, levels of 10 cytokines, sCD40L, CCL2, CCL3, CCL22, PDGF-AA, PDGF-AB/BB, EGF, IL-8, TGF-a, and VEGF, decreased significantly compared to the control group. Therefore, cytokine network dysregulation in MS is characterized by abnormal levels of growth factors and chemokines. Cross-disorder analysis of cytokine levels in MS and SLE showed significant differences between 22 cytokines. Protein interaction network analysis showed that all significantly altered cytokines in both SLE and MS are functionally interconnected. Thus, MS and SLE may be associated with impaired functional relationships in the cytokine network. A cytokine correlation networks analysis revealed changes in correlation clusters in SLE and MS. These data expand the understanding of abnormal regulatory interactions in cytokine profiles associated with autoimmune diseases.

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Iedema, Rick, Raj Verma, Sonia Wutzke, Nigel Lyons, and Brian McCaughan. "A network of networks." Journal of Health Organization and Management 31, no. 2 (April 10, 2017): 223–36. http://dx.doi.org/10.1108/jhom-07-2016-0146.

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Purpose To further our insight into the role of networks in health system reform, the purpose of this paper is to investigate how one agency, the NSW Agency for Clinical Innovation (ACI), and the multiple networks and enabling resources that it encompasses, govern, manage and extend the potential of networks for healthcare practice improvement. Design/methodology/approach This is a case study investigation which took place over ten months through the first author’s participation in network activities and discussions with the agency’s staff about their main objectives, challenges and achievements, and with selected services around the state of New South Wales to understand the agency’s implementation and large system transformation activities. Findings The paper demonstrates that ACI accommodates multiple networks whose oversight structures, self-organisation and systems change approaches combined in dynamic ways, effectively yield a diversity of network governances. Further, ACI bears out a paradox of “centralised decentralisation”, co-locating agents of innovation with networks of implementation and evaluation expertise. This arrangement strengthens and legitimates the role of the strategic hybrid – the healthcare professional in pursuit of change and improvement, and enhances their influence and impact on the wider system. Research limitations/implications While focussing the case study on one agency only, this study is unique as it highlights inter-network connections. Contributing to the literature on network governance, this paper identifies ACI as a “network of networks” through which resources, expectations and stakeholder dynamics are dynamically and flexibly mediated and enhanced. Practical implications The co-location of and dynamic interaction among clinical networks may create synergies among networks, nurture “strategic hybrids”, and enhance the impact of network activities on health system reform. Social implications Network governance requires more from network members than participation in a single network, as it involves health service professionals and consumers in a multi-network dynamic. This dynamic requires deliberations and collaborations to be flexible, and it increasingly positions members as “strategic hybrids” – people who have moved on from singular taken-as-given stances and identities, towards hybrid positionings and flexible perspectives. Originality/value This paper is novel in that it identifies a critical feature of health service reform and large system transformation: network governance is empowered through the dynamic co-location of and collaboration among healthcare networks, particularly when complemented with “enabler” teams of people specialising in programme implementation and evaluation.

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Mancuso, Christopher A., Kayla A. Johnson, Renming Liu, and Arjun Krishnan. "Joint representation of molecular networks from multiple species improves gene classification." PLOS Computational Biology 20, no. 1 (January 10, 2024): e1011773. http://dx.doi.org/10.1371/journal.pcbi.1011773.

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Network-based machine learning (ML) has the potential for predicting novel genes associated with nearly any health and disease context. However, this approach often uses network information from only the single species under consideration even though networks for most species are noisy and incomplete. While some recent methods have begun addressing this shortcoming by using networks from more than one species, they lack one or more key desirable properties: handling networks from more than two species simultaneously, incorporating many-to-many orthology information, or generating a network representation that is reusable across different types of and newly-defined prediction tasks. Here, we present GenePlexusZoo, a framework that casts molecular networks from multiple species into a single reusable feature space for network-based ML. We demonstrate that this multi-species network representation improves both gene classification within a single species and knowledge-transfer across species, even in cases where the inter-species correspondence is undetectable based on shared orthologous genes. Thus, GenePlexusZoo enables effectively leveraging the high evolutionary molecular, functional, and phenotypic conservation across species to discover novel genes associated with diverse biological contexts.

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Luo, Chunbo, Yu Gong, Sally McClean, Peng Ren, and Gerard Parr. "Multiple-source multiple-destinations relay channels with network coding." IET Communications 7, no. 17 (November 26, 2013): 1958–68. http://dx.doi.org/10.1049/iet-com.2012.0828.

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Belavagi, Manjula C., and Balachandra Muniyal. "Multiple intrusion detection in RPL based networks." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 1 (February 1, 2020): 467. http://dx.doi.org/10.11591/ijece.v10i1.pp467-476.

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Routing Protocol for Low Power and Lossy Networks based networks consists of large number of tiny sensor nodes with limited resources. These nodes are directly connected to the Internet through the border router. Hence these nodes are susceptible to different types of attacks. The possible attacks are rank attack, selective forwarding, worm hole and Denial of service attack. These attacks can be effectively identified by intrusion detection system model. The paper focuses on identification of multiple intrusions by considering the network size as 10, 40 and 100 nodes and adding 10%, 20% and 30% of malicious nodes to the considered network. Experiments are simulated using Cooja simulator on Contiki operating system. Behavior of the network is observed based on the percentage of inconsistency achieved, energy consumption, accuracy and false positive rate. Experimental results show that multiple intrusions can be detected effectively by machine learning techniques.

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Didier, Gilles, Christine Brun, and Anaïs Baudot. "Identifying communities from multiplex biological networks." PeerJ 3 (December 22, 2015): e1525. http://dx.doi.org/10.7717/peerj.1525.

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Various biological networks can be constructed, each featuring gene/protein relationships of different meanings (e.g., protein interactions or gene co-expression). However, this diversity is classically not considered and the different interaction categories are usually aggregated in a single network. The multiplex framework, where biological relationships are represented by different network layers reflecting the various nature of interactions, is expected to retain more information. Here we assessed aggregation, consensus and multiplex-modularity approaches to detect communities from multiple network sources. By simulating random networks, we demonstrated that the multiplex-modularity method outperforms the aggregation and consensus approaches when network layers are incomplete or heterogeneous in density. Application to a multiplex biological network containing 4 layers of physical or functional interactions allowed recovering communities more accurately annotated than their aggregated counterparts. Overall, taking into account the multiplexity of biological networks leads to better-defined functional modules. A user-friendly graphical software to detect communities from multiplex networks, and corresponding C source codes, are available at GitHub (https://github.com/gilles-didier/MolTi).

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Bouregaa, Mouweffeq, Mohammed El Kebir Chikh-Bled, Mohammed Debbal, Mohammed Chamse Eddine Ouadah, and Hicham Chikh-Bled. "Optical Code Division Multiple Access for FTTH system." Photonics Letters of Poland 10, no. 4 (December 31, 2018): 121. http://dx.doi.org/10.4302/plp.v10i4.861.

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Many multiple access techniques have been proposed and demonstrated to provide flexible solutions for FTTH network configurations. The performance of this system suffers because of the correlation properties that contribute to a high level of Multiple Access Interference (MAI), low system capacity (users), and lower transmission rate. In this paper, we have proposed Optical CDMA (OCDMA) as a configuration solution for FTTH networks to improve the performance of this type of network. Full Text: PDF References. Z. Mateusz, M. Mariusz, On cost of the uniformity in FTTH network design, Conference on Transparent Optical Networks (2017), 87-90 CrossRef CEDRIC F. LAM, Passive Optical Networks- Principles and Practice, first ed., British Library, USA, 2007. DirectLink M.K. Abdullah, W.T. P'ng, P.W. Lau, E.R. Tee, FTTH access network protection using a switch, Asia Pacific Conference on Communications (APCC), 3(2003) 1219–1222. CrossRef J. Ronnakorn, S. Napat, L. Somkiat, Design and implement of GPON-FTTH network for residential condominium, Conference on Computer Science and Software Engineering, (2017), 333-339. CrossRef M. BOUREGAA, M. CHIKH-BLED, Comparative Study of Optical Unipolar Codes for Incoherent DS-OCDMA system, International Journal of Hybrid Information Technology, 6 (2013) 225-236. CrossRef M. BOUREGAA, M. CHIKH-BLED, The performance of a DS-OCDMA system using Orthogonal Optical Codes (OOC), European Scientific Journal, 9 (2013), 322-335 CrossRef M. Iwase, Y. Ishikawa, T. Komatsu, J. Kasahara, N. Hattori, M. Miura, N. Nakamura, K. Odaka, Optical transceiver modules for gigabit Ethernet PON FTTH systems, Furukawa Review, 28 (2005) 8-10. DirectLink

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Deng, Shuguang, Buwen Cao, Xiang Xiao, Hua Qin, and Bing Yang. "Cognitive routing optimization protocol based on multiple channels in wireless sensor networks." International Journal of Distributed Sensor Networks 16, no. 4 (April 2020): 155014772091451. http://dx.doi.org/10.1177/1550147720914511.

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With the development of modern communication, available spectrum resources are becoming increasingly scarce, which reduce network throughput. Moreover, the mobility of nodes results in the changes of network topological structure. Hence, a considerable amount of control information is consumed, which causes a corresponding increase in network power consumption and exerts a substantial impact on network lifetime. To solve the real-time transmission problem in large-scale wireless mobile sensor networks, opportunistic spectrum access is applied to adjust the transmission power of sensor nodes and the transmission velocity of data. A cognitive routing and optimization protocol based on multiple channels with a cross-layer design is proposed to study joint optimal cognitive routing with maximizing network throughput and network lifetime. Experimental results show that the cognitive routing and optimization protocol based on multiple channels achieves low computational complexity, which maximizes network throughput and network lifetime. This protocol can be also effectively applied to large-scale wireless mobile sensor networks.

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Shimada, Yukiyasu, and Kazuhiko Suzuki. "Feasibility Study of Fault Diagnostics Using Multiple Neural Networks." Journal of Robotics and Mechatronics 11, no. 4 (August 20, 1999): 326–30. http://dx.doi.org/10.20965/jrm.1999.p0326.

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This paper presents a fault diagnostic system (FDS) using multiple neural networks for chemical plants. The fault propagation in progress is modeled by causal relationships between a fault tree (FT) and its minimal cut sets (MCSa). The measurement patterns required for training neural networks (NNs) are obtained from fault propagation model. The FDS has a circuit network and component networks. The circuit network can identify circuit malfunctions that include disturbances. The component networks can identify component malfunctions as root causes of process malfunction. We have constructed an on-line FDS by making use of proposed method and verified the effectiveness of it experimentally.

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Kamal Bashah, Nor Shahniza, Nor Haizon Husin, Syaripah Ruzaini Syed Aris, Norjansalika Janom, and Noor Habibah Arshad. "The optimization of leased line distribution at the EDGE of local access network via WAN convergence network." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 1 (October 1, 2019): 333. http://dx.doi.org/10.11591/ijeecs.v16.i1.pp333-341.

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Managing the multiple services of the leased line at the same location is quite critical especially when the resource become highly utilized. Bundling the several network resource components into a one box by simplifying the multiple networks to a single network can help to reduce the utilization of network resources. This paper presents a study on optimiziation of leased line distribution at the EDGE of Local Access Network via WAN convergence network. In this study, a WAN Convergence Network is designed which intends to use only a single leased line network in a location rather than multiple leased lines. It is using a simple concept of SDH structured which channelized the time slots and control the transmission line. The time slots will be relocated from the multiple leased lines into a WAN Convergence Network and it will be de-multiplexed through the Data Circuit Terminating Equipment (DCE) at the customer premises. The WAN Convergence Network design starts from the Digital Data Network (DDN) until the DCE which includes the Local Access Network. This approach will be able to save the network resource especially the time slots, cable port, DCE and consequently avoid adding new network infrastructure. This research will result to the new network design which offer multiple leased line networks at the customer end by using only one dedicated leased line network namely WAN Convergence Network.

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Journal articles on the topic 'Multiple network'

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