What is the name of network topology in which there are bidirectional links between each possible nodes?
Answers from top 7 papers
More filters
Papers (7) | Insight |
---|---|
15 Citations | Three primary observations resulted: (a) links are most prevalent among vertices that join a network at a similar time; (b) the rate that new vertices join a network is a central factor in molding a network's topology; and (c) the emergence of network stars (high-degree vertices) is correlated with fast-growing networks. |
17 Citations | It is shown in this paper that links connecting neighboring clusters are the most critical links of the network in comparison to links with highest congestion, flows, or betweennesses. |
23 Nov 2009 | Based on these amenities, our topology control algorithm is able of providing an “insight” of the graph structure of the network on top which control over information flow, message delivery, latency and energy dissipation among nodes can be easily deployed. |
06 Dec 1992 14 Citations | It allows the routing nodes, of a computer network or internet to maintain the correct view of the topology, even when link costs change or the topology changes due to failures or additions of nodes or links. |
03 Sep 2012 9 Citations | Unlike traditional approaches that mainly focus on the network topological structure, the originality of our solution is its ability to exploit information both on the network structure and the attributes of nodes in order to elicit specific regularities that we call “Frequent Links”. |
14 Citations | This means essentially that the issue of interconnectivity — in a broad sense the potential access to all relevant nodes in a network — is much more complicated than just the notion of physical distance friction: the quality and structure of an entire network is at stake here, so that one has to investigate the features of both nodes and their connecting links. |
148 Citations | In other words, the case where the load of the links is considered to be the product of the betweenness centrality of the end nodes is favored for the robustness of the network against cascaded failures. |
Related Questions
How do bidireccional cnn networks work?5 answersBidirectional Convolutional Neural Networks (Bi-CNNs) combine the principles of Convolutional Neural Networks (CNNs) with bidirectional processing. CNNs excel in image-related tasks by automatically detecting features, while bidirectional processing allows information to be processed in both forward and backward directions, enhancing context awareness and capturing dependencies in sequential data. By integrating these concepts, Bi-CNNs can effectively analyze and extract features from data in both directions, making them suitable for tasks like sentiment analysis in text data. Additionally, techniques like weight distribution mimicking can further enhance the performance of binary neural networks by preserving the distribution of network weights during training. Overall, Bi-CNNs leverage the strengths of CNNs and bidirectional processing to improve feature extraction and context understanding in various applications.
What is mesh topology in network?3 answersMesh topology in a network refers to the interconnection of all nodes in the network, where each node is connected to every other node. This topology is commonly used in wireless mesh networks (WMNs). WMNs consist of radio nodes arranged in a mesh topology, allowing for efficient data transmission and communication. In a WMN, mesh nodes are connected via base stations, and the network can include various devices such as nodes, clients, routers, and gateways. The mesh network architecture can be client-based, infrastructure-based, or a hybrid of both. WMNs have the advantage of being self-healable and can work with different networks and protocols. They are also flexible and versatile, making them suitable for various applications, such as smart meters. Overall, mesh topology in a network, particularly in WMNs, provides a robust and efficient communication infrastructure.
How to analyze network topologies using graph theory?5 answersNetwork topologies can be analyzed using graph theory. Graph theory concepts are used to analyze the topological properties of complex networks, such as degrees of vertices, ranking, clustering, and modularity. Graphs are used to represent networks, with vertices representing nodes and edges representing connections. Various parameters can be calculated to analyze the network as a whole, including the number of nodes, number of edges, geodetic distance between nodes, average distance between nodes, density, number of triads, and diameter of the network. Structural network analysis techniques, such as click detection, identification of network components, finding bridges, and groups of equivalent nodes, can also be applied. Visualization tools are available to analyze and visualize the structure and properties of complex networks.
What are all the studies that discuss human mobility in terms of topological network structure.?4 answersStudies by Wiedemann et al., Lamosa et al., Cao et al., and the study on Hurricane Idadiscuss human mobility in terms of topological network structure. Wiedemann et al. propose using network modeling methods to analyze the effect of spatial and context attributes on individual movement patterns, using Multiple Regression Quadratic Assignment Procedure and Stochastic Actor-Oriented Models. Lamosa et al. study topological indexes and community structure changes in a business day using a mobility database with high temporal resolution. Cao et al. present a data-driven approach for characterizing urban mobility networks based on massive-scale mobile phone tracking data, constructing global urban mobility networks and motif-dependent urban mobility subnetworks. The study on Hurricane Ida examines human mobility network resilience at macroscopic, substructure, and microscopic scales.
Is metaphorical mapping unidirection or bidirection?5 answersMetaphorical mapping is bidirectional, according to the abstracts provided. The interaction theory of metaphor emphasizes bidirectionality, which means that the mapping of information from the source domain to the target domain and vice versa occurs. This bidirectionality is also discussed in relation to blending theory. The abstracts mention the notion of bidirectionality in the context of reasoning with metaphor, exploring mapping metaphors in B2B marketing, and studying metaphorical mapping in human infants. The abstracts also discuss the relationship between bidirectionality and the concept of metaphorical match, where abstract similarities between events that are not physically similar or associated through co-occurrence are perceived. Overall, the abstracts suggest that metaphorical mapping involves bidirectional mapping of information between different domains.
What is the name of network topology in which there are bi directional link between each possible node?9 answers