Shortest Path Routing Algorithm Based on Chaotic Neural Network

A shortest path routing algorithm based on transient chaotic neural network is proposed in this paper. Gam-pared with previous models adopting Hopfield neural network, this algorithm has a higher ability to overcome the local minimum, and achieves a better performance. By introducing a special post-processing technique for the output matrixes, our algorithm can obtain an optimal solution with a high probability even for the paths that need more hops in large-size networks.

Novel Path Counting-Based Method for Fractal Dimension Estimation of the Ultra-Dense Networks

Next-generation networks,including the Internet of Things(IoT),fifth-generation cellular systems(5G),and sixth-generation cellular systems(6G),suf-fer from the dramatic increase of the number of deployed devices.This puts high constraints and challenges on the design of such networks.Structural changing of the network is one of such challenges that affect the network performance,includ-ing the required quality of service(QoS).The fractal dimension(FD)is consid-ered one of the main indicators used to represent the structure of the communication network.To this end,this work analyzes the FD of the network and its use for telecommunication networks investigation and planning.The clus-ter growing method for assessing the FD is introduced and analyzed.The article proposes a novel method for estimating the FD of a communication network,based on assessing the network’s connectivity,by searching for the shortest routes.Unlike the cluster growing method,the proposed method does not require multiple iterations,which reduces the number of calculations,and increases the stability of the results obtained.Thus,the proposed method requires less compu-tational cost than the cluster growing method and achieves higher stability.The method is quite simple to implement and can be used in the tasks of research and planning of modern and promising communication networks.The developed method is evaluated for two different network structures and compared with the cluster growing method.Results validate the developed method.

Assessing impacts to maritime shipping from marine chokepoint closures

Global supply chain disruptions caused by the six-day blockage of the Suez Canal in March 2021 and the reduction in shipping through the Bosporus Strait since the onset of the Ukraine War in February 2022 are recent demonstrations of the critical importance of marine chokepoints to international trade and thus global economic security.To better understand and anticipate effects of a chokepoint closure on global trade,we combine GIS data of international shipping lanes with 2019 bilateral trade data to estimate how the closure of each of eleven chokepoints could change trade flows through other chokepoints and between countries.Estimates from the closure scenarios reveal alternate-shipping route linkages between seven chokepoints whereby if one were closed for an extended period,trade through one or more of the others would change significantly.The estimates also underscore the economic importance of the Danish Straits,the Bosporus Strait,the Strait of Hormuz,and the South China Sea and East China Sea to those countries that must rely on these chokepoints for access to maritime trade.Moreover,the estimates project delays and shifts in coastal seaport activity that could lead to knock-on effects that disrupt global supply chains long after a chokepoint blockage is cleared.