scholarly journals A Multilevel Simplification Algorithm for Computing the Average Shortest-Path Length of Scale-Free Complex Network

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Guoyong Mao ◽  
Ning Zhang
Keyword(s):  
Complex Network ◽  
Shortest Path ◽  
Path Length ◽  
Large Scale ◽  
Computation Time ◽  
Scale Free Network ◽  
Original Network ◽  
Memory Space ◽  
Scale Free ◽  
Free Network

Computing the average shortest-path length (ASPL) of a large scale-free network needs much memory space and computation time. Based on the feature of scale-free network, we present a simplification algorithm by cutting the suspension points and the connected edges; the ASPL of the original network can be computed through that of the simplified network. We also present a multilevel simplification algorithm to get ASPL of the original network directly from that of the multisimplified network. Our experiment shows that these algorithms require less memory space and time in computing the ASPL of scale-free network, which makes it possible to analyze large networks that were previously impossible due to memory limitations.

scholarly journals Analysis of Average Shortest-Path Length of Scale-Free Network

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Guoyong Mao ◽  
Ning Zhang
Keyword(s):  
Load Balancing ◽  
Shortest Path ◽  
Path Length ◽  
Large Scale ◽  
Programming Model ◽  
Computing Time ◽  
Coarse Grained ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network

Computing the average shortest-path length of a large scale-free network needs much memory space and computation time. Hence, parallel computing must be applied. In order to solve the load-balancing problem for coarse-grained parallelization, the relationship between the computing time of a single-source shortest-path length of node and the features of node is studied. We present a dynamic programming model using the average outdegree of neighboring nodes of different levels as the variable and the minimum time difference as the target. The coefficients are determined on time measurable networks. A native array and multimap representation of network are presented to reduce the memory consumption of the network such that large networks can still be loaded into the memory of each computing core. The simplified load-balancing model is applied on a network of tens of millions of nodes. Our experiment shows that this model can solve the load-imbalance problem of large scale-free network very well. Also, the characteristic of this model can meet the requirements of networks with ever-increasing complexity and scale.

THE RELEVANCE-STRENGTH IN A SCALE-FREE NETWORK

2008 ◽  
Vol 22 (31) ◽  
pp. 3053-3059 ◽  
Author(s):  
HYUN-JOO KIM
Keyword(s):  
Network Model ◽  
Shortest Path ◽  
Power Law ◽  
Path Length ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network ◽  
The Mean

We introduce a new quantity, relevance-strength which describes the relevance of a node to the others in a scale-free network. We define a weight between two nodes i and j based on the shortest path length between them and the relevance-strength of a node is defined as the sum of the weights between it and others. For the Barabási and Albert model which is a well-known scale-free network model, we measure the relevance-strength of each node and study the correlations with other quantities, such as the degree, the mean degree of neighbors of a node, and the mean relevance-strength of neighbors. We find that the relevance-strength shows power law behaviors and the crossover behaviors for the degree and the mean relevance-strength of neighbors. Also, we study the scaling behaviors of the relevance-strength for various average relevance-strength for all nodes.

An improved global dynamic routing strategy for scale-free network with tunable clustering

2016 ◽  
Vol 30 (22) ◽  
pp. 1650302 ◽  
Author(s):  
Lina Sun ◽  
Ning Huang ◽  
Yue Zhang ◽  
Yannan Bai
Keyword(s):  
Shortest Path ◽  
Path Length ◽  
Network Capacity ◽  
Network Routing ◽  
Scale Free Network ◽  
Scale Free ◽  
Global Dynamic ◽  
Routing Strategy ◽  
Traffic Awareness ◽  
Free Network

An efficient routing strategy can deliver packets quickly to improve the network capacity. Node congestion and transmission path length are inevitable real-time factors for a good routing strategy. Existing dynamic global routing strategies only consider the congestion of neighbor nodes and the shortest path, which ignores other key nodes’ congestion on the path. With the development of detection methods and techniques, global traffic information is readily available and important for the routing choice. Reasonable use of this information can effectively improve the network routing. So, an improved global dynamic routing strategy is proposed, which considers the congestion of all nodes on the shortest path and incorporates the waiting time of the most congested node into the path. We investigate the effectiveness of the proposed routing for scale-free network with different clustering coefficients. The shortest path routing strategy and the traffic awareness routing strategy only considering the waiting time of neighbor node are analyzed comparatively. Simulation results show that network capacity is greatly enhanced compared with the shortest path; congestion state increase is relatively slow compared with the traffic awareness routing strategy. Clustering coefficient increase will not only reduce the network throughput, but also result in transmission average path length increase for scale-free network with tunable clustering. The proposed routing is favorable to ease network congestion and network routing strategy design.

On Modeling Shortest Path Length Distribution in Scale-Free Network Topologies

2018 ◽  
Vol 12 (4) ◽  
pp. 3869-3872 ◽  
Author(s):  
Agnese V. Ventrella ◽  
Giuseppe Piro ◽  
Luigi Alfredo Grieco
Keyword(s):  
Shortest Path ◽  
Path Length ◽  
Length Distribution ◽  
Scale Free Network ◽  
Scale Free ◽  
Network Topologies ◽  
Free Network

scholarly journals HIERARCHICAL AND MIXING PROPERTIES OF STATIC COMPLEX NETWORKS EMERGING FROM FLUCTUATING CLASSICAL RANDOM GRAPHS

2006 ◽  
Vol 17 (09) ◽  
pp. 1303-1311 ◽  
Author(s):  
SUMIYOSHI ABE ◽  
STEFAN THURNER
Keyword(s):  
Complex Network ◽  
Preferential Attachment ◽  
Hierarchical Organization ◽  
Scale Free Network ◽  
Mixing Properties ◽  
Scale Free ◽  
Free Network ◽  
Growing Network ◽  
Arbitrary Connectivity

The Erdös–Rényi classical random graph is characterized by a fixed linking probability for all pairs of vertices. Here, this concept is generalized by drawing the linking probability from a certain distribution. Such a procedure is found to lead to a static complex network with an arbitrary connectivity distribution. In particular, a scale-free network with the hierarchical organization is constructed without assuming any knowledge about the global linking structure, in contrast to the preferential attachment rule for a growing network. The hierarchical and mixing properties of the static scale-free network thus constructed are studied. The present approach establishes a bridge between a scalar characterization of individual vertices and topology of an emerging complex network. The result may offer a clue for understanding the origin of a few abundance of connectivity distributions in a wide variety of static real-world networks.

scholarly journals Evaluating the Impact of Name Resolution Dependence on the DNS

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Haiyan Xu ◽  
Zhaoxin Zhang ◽  
Jianen Yan ◽  
Xin Ma
Keyword(s):  
Large Scale ◽  
Scale Free Network ◽  
Security Measures ◽  
Scale Free ◽  
Domain Names ◽  
The Core ◽  
Complex Dependence ◽  
Random Failure ◽  
Free Network ◽  
The Impact

In the process of resolving domain names to IP addresses, there exist complex dependence relationships between domains and name servers. This paper studies the impact of the resolution dependence on the DNS through constructing a domain name resolution network based on large-scale actual data. The core nodes of the resolution network are mined from different perspectives by means of four methods. Then, both core attacks and random attacks on the network are simulated for further vulnerability analysis. The experimental results show that when the top 1% of the core nodes in the network are attacked, 46.19% of the domain names become unresolved, and the load of the residual network increases by nearly 195%, while only 0.01% of domain names fail to be resolved and the load increases with 18% in the same attack scale of the random mode. For these key nodes, we need to take effective security measures to prevent them from being attacked. The simulation experiment also proves that the resolution network is a scale-free network, which exhibits robustness against random failure and vulnerability against intentional attacks. These findings provide new references for the configuration of the DNS.

Random Immunization Algorithm to Energy Consumption in Optical Network

2014 ◽  
Vol 926-930 ◽  
pp. 1993-1996
Author(s):  
Dong Yan Zhao ◽  
Xiang Lou Liu ◽  
Dong Xue Wang ◽  
Hai Wei Mu ◽  
Hong Mei Song ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Complex Network ◽  
Optical Network ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network ◽  
Simulation Results ◽  
Save Energy ◽  
Node Immunization

The immunization algorithm is from the theory of complex network. The algorithm is simple, highly feasible based on scale-free network model. This paper uses random immunization algorithm to solve optical network energy issues. This paper selects the service to be the operator and to save energy through node immunization. The simulation results show the algorithm can be implemented. This paper provides another possibility to energy saving on optical network.

Toward Energy-Efficient and Robust Large-Scale WSNs: A Scale-Free Network Approach

2016 ◽  
Vol 34 (12) ◽  
pp. 4035-4047 ◽  
Author(s):  
Haixia Peng ◽  
Shuaizong Si ◽  
Mohamad Khattar Awad ◽  
Ning Zhang ◽  
Hai Zhao ◽  
...  
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Network Approach ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network
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