scholarly journals A modified optimal routing strategy based on random walk on complex networks

2011 ◽  
Vol 60 (11) ◽  
pp. 118903
Author(s):  
Wang Kai ◽  
Zhou Si-Yuan ◽  
Zhang Yi-Feng ◽  
Pei Wen-Jiang ◽  
Liu Qian
Keyword(s):  
Random Walk ◽  
Complex Networks ◽  
Optimal Routing ◽  
Routing Strategy

Information entropy of diffusion processes on complex networks

2014 ◽  
Vol 28 (17) ◽  
pp. 1450141 ◽  
Author(s):  
Zhanli Zhang
Keyword(s):  
Diffusion Process ◽  
Complex Networks ◽  
Information Entropy ◽  
Diffusion Processes ◽  
Structural Characteristics ◽  
Optimal Routing ◽  
Information Propagation ◽  
Scale Free ◽  
Routing Strategy ◽  
Computer Scientists

Diffusion processes have been widely investigated to understand some essential features of complex networks, and have attracted much attention from physicists, statisticians and computer scientists. In order to understand the evolution of the diffusion process and design the optimal routing strategy according to the maximal entropic diffusion on networks, we propose the information entropy comprehending the structural characteristics and information propagation on the network. Based on the analysis of the diffusion process, we analyze the coupling impact of the structural factor and information propagating factor on the information entropy, where the analytical results fit well with the numerical ones on scale-free complex networks. The information entropy can better characterize the complex behaviors on networks and provides a new way to deepen the understanding of the diffusion process.

Improved efficient routing strategy on two-layer complex networks

2016 ◽  
Vol 27 (04) ◽  
pp. 1650044 ◽  
Author(s):  
Jinlong Ma ◽  
Weizhan Han ◽  
Qing Guo ◽  
Shuai Zhang ◽  
Junfang Wang ◽  
...  
Keyword(s):  
Complex Networks ◽  
Research Topic ◽  
Global Awareness ◽  
Traffic Dynamics ◽  
Shortest Path Routing ◽  
Transport Efficiency ◽  
Routing Strategy ◽  
Traffic Capacity ◽  
Traffic Performance ◽  
Simulation Results

The traffic dynamics of multi-layer networks has become a hot research topic since many networks are comprised of two or more layers of subnetworks. Due to its low traffic capacity, the traditional shortest path routing (SPR) protocol is susceptible to congestion on two-layer complex networks. In this paper, we propose an efficient routing strategy named improved global awareness routing (IGAR) strategy which is based on the betweenness centrality of nodes in the two layers. With the proposed strategy, the routing paths can bypass hub nodes of both layers to enhance the transport efficiency. Simulation results show that the IGAR strategy can bring much better traffic capacity than the SPR and the global awareness routing (GAR) strategies. Because of the significantly improved traffic performance, this study is helpful to alleviate congestion of the two-layer complex networks.

scholarly journals An Efficient Multi-Vehicle Routing Strategy for Goods Delivery Services

2021 ◽  
Author(s):  
Linh Nguyen
Keyword(s):  
Autonomous Vehicles ◽  
Optimization Problem ◽  
Transportation Cost ◽  
Mixed Integer ◽  
Optimal Routing ◽  
Ground Vehicles ◽  
Routing Optimization ◽  
Routing Strategy ◽  
Delivery Services ◽  
Delivery Vehicles

<pre>The paper addresses the problem of efficiently planning routes for multiple ground vehicles used in goods delivery services. Given popularity of today's e-commerce, particularly under the COVID-19 pandemic conditions, goods delivery services have been booming than ever, dominated by small-scaled (electric) bikes and promised by autonomous vehicles. However, finding optimal routing paths for multiple delivery vehicles operating simultaneously in order to minimize transportation cost is a fundamental but challenging problem. In this paper, it is first proposed to exploit the mixed integer programming paradigm to model the delivery routing optimization problem (DROP) for multiple simultaneously-operating vehicles given their energy constraints. The routing optimization problem is then solved by the multi-chromosome genetic algorithm, where the number of delivery vehicles can be optimized. The proposed approach was evaluated in a real-world experiment in which goods were expected to be delivered from a depot to 26 suburb locations in Canberra, Australia. The obtained results demonstrate effectiveness of the proposed algorithm.</pre>

scholarly journals Efficient Routing Strategy with Memory Information for Complex Networks

2012 ◽  
Vol 02 (01) ◽  
pp. 73-81 ◽  
Author(s):  
Takayuki Kimura ◽  
Tohru Ikeguchi ◽  
Chi K. Tse
Keyword(s):  
Complex Networks ◽  
Routing Strategy ◽  
With Memory

Coupling entropy of co-processing model on social networks

2015 ◽  
Vol 29 (25) ◽  
pp. 1550149
Author(s):  
Zhanli Zhang
Keyword(s):  
Social Networks ◽  
Information Flow ◽  
Structural Characteristics ◽  
Time Lag ◽  
Optimal Routing ◽  
Information Propagation ◽  
Time Processing ◽  
Scale Free ◽  
Routing Strategy ◽  
Processing Ability

Coupling entropy of co-processing model on social networks is investigated in this paper. As one crucial factor to determine the processing ability of nodes, the information flow with potential time lag is modeled by co-processing diffusion which couples the continuous time processing and the discrete diffusing dynamics. Exact results on master equation and stationary state are achieved to disclose the formation. In order to understand the evolution of the co-processing and design the optimal routing strategy according to the maximal entropic diffusion on networks, we propose the coupling entropy comprehending the structural characteristics and information propagation on social network. Based on the analysis of the co-processing model, we analyze the coupling impact of the structural factor and information propagating factor on the coupling entropy, where the analytical results fit well with the numerical ones on scale-free social networks.

An incremental optimal routing strategy for scale-free networks

2014 ◽  
Vol 25 (09) ◽  
pp. 1450044 ◽  
Author(s):  
Zhong-Yuan Jiang
Keyword(s):  
Traffic Load ◽  
Traffic Model ◽  
Optimal Routing ◽  
Traffic Dynamics ◽  
Shortest Path Routing ◽  
Scale Free ◽  
Routing Strategy ◽  
Traffic Capacity ◽  
Real Complex ◽  
Link Congestion

The link congestion based traffic model can more accurately reveal the traffic dynamics of many real complex networks such as the Internet, and heuristically optimizing each link's weight for the shortest path routing strategy can strongly improve the traffic capacity of network. In this work, we propose an optimal routing strategy in which the weight of each link is regulated incrementally to enhance the network traffic capacity by minimizing the maximum link betweenness of any link in the network. We also estimate more suitable value of the tunable parameter β for the efficient routing strategy under the link congestion based traffic model. The traffic load of network can be significantly balanced at the expense of increasing a bit average path length or average traffic load.

Sign in / Sign up

Export Citation Format

Share Document