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Sensor location for travel time estimation based on the user equilibrium principle: Application of linear equations

Cao Shuhan, Shao Hu, Shao Feng

International Journal of Applied Mathematics and Computer Science

2022

Vol. 32, no. 1

23--33

Travel time is a fundamental measure in any transportation system. With the development of technology, travel time can be automatically collected by a variety of advanced sensors. However, limited by objective conditions, it is difficult for any sensor system to cover the whole transportation network in real time. In order to estimate the travel time of the whole transportation network, this paper gives a system of linear equations which is constructed by the user equilibrium (UE) principle and observed data. The travel time of a link which is not covered by a sensor can be calculated by using the observed data collected by sensors. In a typical transportation network, the minimum number and location of sensors to estimate the travel time of the whole network are given based on the properties of the solution of a systems of linear equations. The results show that, in a typical network, the number and location of sensors follow a certain law. The results of this study can provide reference for the development of transportation and provide a scientific basis for transportation planning.

Exact and approximation algorithms for sensor placement against DDoS attacks

Junosza-Szaniawski Konstanty, Nogalski Dariusz, Wójcik Agnieszka

Annals of Computer Science and Information Systems

2020

Vol. 21

295--301

In DDoS attack (Distributed Denial of Service), an attacker gains control of many network users by a virus. Then the controlled users send many requests to a victim, leading to lack of its resources. DDoS attacks are hard to defend because of distributed nature, large scale and various attack techniques. One of possible ways of defense is to place sensors in the network that can detect and stop an unwanted request. However, such sensors are expensive so there is a natural question about a minimum number of sensors and their optimal placement to get the required level of safety. We present two mixed integer models for optimal sensor placement against DDoS attacks. Both models lead to a trade-off between the number of deployed sensors and the volume of uncontrolled flow. Since above placement problems are NP-hard, two efficient heuristics are designed, implemented and compared experimentally with exact linear programming solvers.