Efficient routing strategies in scale-free networks with limited bandwidth

Tang, Ming; Zhou, Tao

doi:10.1103/physreve.84.026116

Cited by 67 publications

(24 citation statements)

References 50 publications

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“…However, many factors, such as loading balancing and fault tolerance, may lead to some compromised strategies in which data packets are not always delivered through the shortest path in the real commercial transport network [78,79]. It has also been shown that the selection of the shortest paths between all pairs of nodes may lead to traffic congestion problem [80].…”

Section: Betweenness Centralitymentioning

confidence: 99%

Vital nodes identification in complex networks

et al. 2016

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Real networks exhibit heterogeneous nature with nodes playing far different roles in structure and function. To identify vital nodes is thus very significant, allowing us to control the outbreak of epidemics, to conduct advertisements for e-commercial products, to predict popular scientific publications, and so on. The vital nodes identification attracts increasing attentions from both computer science and physical societies, with algorithms ranging from simply counting the immediate neighbors to complicated machine learning and message passing approaches. In this review, we clarify the concepts and metrics, classify the problems and methods, as well as review the important progresses and describe the state of the art. Furthermore, we provide extensive empirical analyses to compare well-known methods on disparate real networks, and highlight the future directions. In despite of the emphasis on physics-rooted approaches, the unification of the language and comparison with cross-domain methods would trigger interdisciplinary solutions in the near future.

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Section: Betweenness Centralitymentioning

confidence: 99%

Vital nodes identification in complex networks

et al. 2016

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“…Thus, a measure w ij = (k i k j ) θ [33] was introduced as the weight of an edge. This measure has been adopted in many works for distinguishing the importance among edges in unweighted networks [34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Accurate ranking of influential spreaders in networks based on dynamically asymmetric link weights

Liu

Tang

et al. 2017

Phys. Rev. E

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We propose an efficient and accurate measure for ranking spreaders and identifying the influential ones in spreading processes in networks. While the edges determine the connections among the nodes, their specific role in spreading should be considered explicitly. An edge connecting nodes i and j may differ in its importance for spreading from i to j and from j to i. The key issue is whether node j, after infected by i through the edge, would reach out to other nodes that i itself could not reach directly. It becomes necessary to invoke two unequal weights w_{ij} and w_{ji} characterizing the importance of an edge according to the neighborhoods of nodes i and j. The total asymmetric directional weights originating from a node leads to a novel measure s_{i}, which quantifies the impact of the node in spreading processes. An s-shell decomposition scheme further assigns an s-shell index or weighted coreness to the nodes. The effectiveness and accuracy of rankings based on s_{i} and the weighted coreness are demonstrated by applying them to nine real-world networks. Results show that they generally outperform rankings based on the nodes' degree and k-shell index while maintaining a low computational complexity. Our work represents a crucial step towards understanding and controlling the spread of diseases, rumors, information, trends, and innovations in networks.

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“…Many local routing strategies are based on the random-walk process [15]. Hybrid routing strategies [16][17][18][19][20][21][22] have been based on both global information (the shortest paths from one node to all the others), and local information (the degrees or local traffic loads of the neighboring nodes) in order to enhance network performance. However, our main focus in this paper is not so much on verifying the effectiveness of a certain routing strategy; rather we concentrate on the impact of different network structures on network performance.…”

Section: Introductionmentioning

confidence: 99%

Impact of network structure on latency in complex networks

Verma

2012

2012 35th IEEE Sarnoff Symposium

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This paper investigates the impact of network structure on latency in complex networks under two different routing strategies. The performances of both scale-free networks and random networks are compared and evaluated under the shortest path routing strategy and least cost routing strategy. Our study shows that under the shortest path routing strategy, the scale-free network fares much worse compared to the random network. Conversely, under the least cost routing, the performance of the scale-free network far exceeds that of the random network because of its unique network structure.

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Efficient routing strategies in scale-free networks with limited bandwidth

Cited by 67 publications

References 50 publications

Vital nodes identification in complex networks

Vital nodes identification in complex networks

Accurate ranking of influential spreaders in networks based on dynamically asymmetric link weights

Impact of network structure on latency in complex networks

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