Abstract
A great deal of information and traffic circulate over the complex and largescale networks. Such examples abound in an airline route or road map, and the Internet web[1]. These are important social infrastructures and hence desired to possess sufficient resilience against an unpredictable breakdown in order to maintain the expected function. Including redundant nodes and links to the network is expected to allow more robust systems, however it would make the system more expensive and less efficient in the ordinary situations. Therefore, a well-balanced network topology taking into account both optimality and resilience is of great importance[2]. Recently, it has come to be known that a number of real world networks are scale-free network (SFN), as seen in the airline route map, electrical power network, and the Internet web[3, 4, 5]. One of the main features in SFN is that the network topology exhibits a power-law degree distribution: P(k) ~k − γ, where k is the number of link attached to a randomly chosen node in the network and γ is the scaling exponent. SFN is named for the fact that the power-law distributions do not have a median thad implies a typical size of the system[6]. It is also known that the average path length between the nodes are surprisingly small in SFN[7], hence the efficient transport is expected over the network.
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Sekiyama, K., Araki, H. (2009). Network Topology Reconfiguration Based on Risk Management. In: Asama, H., Kurokawa, H., Ota, J., Sekiyama, K. (eds) Distributed Autonomous Robotic Systems 8. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00644-9_3
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DOI: https://doi.org/10.1007/978-3-642-00644-9_3
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