Paper Info
Title
Topology Evolution Model For Ad Hoc-Cellular Hybrid Networks Based On Complex Network Theory
Abstract
Switching and routing are two important issues in the ad hoc-cellular hybrid network. Frequently switching between different network modes will lead to the increase of time delay, and unreasonable routing will reduce information transmission efficiency and shorten the network life. In order to reduce the influence of these problems to the network, in this paper, we proposed a robust and efficient ad hoc network topology evolution model, which can reduce the switching probability and establish efficient transmission paths. In this model, the mobile users' residual energy, available channel quality, and the importance are taken into account. The model is based on Barrat, Barthelemy, and Vespignani model and the triad formation mechanism, which ensures the network topology have scale-free and small-world features. The topology construction process of the ad hoc network is composed of three parts: (i) new users join the network; (ii) new users establish connections with existing users; (iii) the connections between existing users were deleted because of the network optimization and the interference of cellular network. Simulation results show that the network built by this model with small-world and scale-free features has small average shortest path length and the robustness against random nodes failure, which will significantly improve the transmission efficiency and reduce the probability of switching between different transmission model. Copyright (C) 2016 John Wiley & Sons, Ltd.
Year
DOI
Venue
2017
10.1002/dac.3119
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
Keywords
Field
DocType
topology evolution, ad hoc-cellular hybrid network, complex network theory, BBV model
Network formation,Mobile ad hoc network,Topology,Network delay,Computer science,Computer network,Network architecture,Network simulation,Network topology,Optimized Link State Routing Protocol,Wireless ad hoc network
Journal
Volume
Issue
ISSN
30
6
1074-5351
Citations 
PageRank 
References 
0
0.34
8
Authors
4
Name
Order
Citations
PageRank
Yongfu Hou100.68
Yifei Wei213618.94
Mei Song326544.50
Fei Yu45116335.58