Research on Data Routing Model Based on Ant Colony Algorithms

Improved traditional ant colony algorithms,a data routing model used to the data remote exchange on WAN was presented.In the model,random heuristic factors were introduced to realize multi-path search.The updating model of pheromone could adjust the pheromone concentration on the optimal path according to path load dynamically to make the system keep load balance.The simulation results show that the improved model has a higher performance on convergence and load balance.

Analysing taxi customer-search behaviour using Copula-based joint model

The drivers of vacant taxis tend to cruise the road network searching new passengers,which leads to additional traffic congestion,air pollution and other problems.This study introduces a Copula-based joint model to analyse destination selection and route choice behaviour in the customer-search process.A multinomial logit model is used to analyse the destination selection behaviour,and a path size logit model is used to explore the routes choice behaviour.Accordingly,the joint model applied Copula function is then established to analyse the correlation between these two behaviours.The destination customer generation rate,destination distance,route customer generation rate,path travel time,cumulative intersection delay,path size and route length are selected as explanatory variables.The taxis trajectory data were collected by global positioning system in Xidan District of Beijing City from September 2014 to February 2015.Using the log-likelihood,Bayesian information criterion as evaluation indexes to measure the fitting result,the joint model applied Copula function has the highest goodness-of-fit.The effect of explanatory variables on customer search behaviour is discussed based on the parameter estimation results.The results of this study are helpful to understand the customer-search behaviour of taxi drivers to reduce operating costs and improve the efficiency of the taxi operation system.

Operational Risk-averse Routing Optimization for Cyber-physical Power Systems

The extensive application of modern information and communication technology in the power system through the in-depth integration of the information system and the power system has led to the gradual development of the cyberphysical power system(CPPS).While advanced information technology increases the safety and reliability of power system operations,it also increases the risks of fault propagation.To improve the reliability of CPPS from the perspective of power communication routing,it is proposed that the CPPS model and vulnerability assessment of power node reflect the correlation between information and energy flows with the service impact on power grid operation,which is an important index for evaluating communication services.According to the distribution of services at the different important levels on the links,the importance of the cross-layer link is established as the vulnerability evaluation index of the communication network.Then,the routing optimization model is proposed in combination with the service transmission risk under cyber-attack and the operating characteristics of the information system,which is solved through an improved fast-convergent genetic algorithm.The simulation results show that the proposed method allocates the alternate route to the low-risk link without significantly increasing the delay of the main route,which effectively improves the power supply reliability of CPPS in extreme cyber-attack scenarios.