In recent years, various researches have been conducted in order to find ways to cover a target or groups of targets with priority-based target coverage and sensor deployment mechanisms taking the front seats. However, with these researches, effective target coverage has been a recurrent issue due to various factors like conflict between sensors and excessive waiting time for targets to be covered. In this paper, we proposed an algorithm based on queuing theory in tandem with mobile crowd sensing to tackle these issues. To do this, first, we develop some models which are based on the birth-and-death mechanism (one of the tools in queuing theory) to determine how long a target has to wait, the mean busy period of sensors and mean idle period of sensors. While developing these models, we consider cases where there exist a single sensor and $n$ -sensors in the system. Based on these models, we develop the required algorithm. The simulation result shows that as the number of sensors increases relative to the number of targets, an average time before a target gets discovered is 0.2 s and sensor utilization decreasing toward zero as the number of sensors increases.

Queuing Algorithm for Effective Target Coverage in Mobile Crowd Sensing

With the continuous breakthroughs of unmanned vehicle technology, a increasing number of unmanned vehicles will be added to the current traffic system. How will the above situation influence the traffic, and how will we change the existing traffic system design program to help unmanned technology to improve people's travel efficiency in a better way, have become urgent problems to be solved. In this paper, the model of Queuing Theory is applied to simulate and calculate the number of lanes of different toll stations, on which basis, the optimal proportional adjustment model of ETC (Electronic Toll Collection) is obtained. Finally, the results of sensitivity analysis of the model show that it has an excellent robustness and reliability.

ETC proportional adjustment model based on queuing theory in the case of unmanned vehicles

In view of traffic queuing question, this article has established the dynamic queuing theory model, considered the waiting the traffic flow magnitude and the vehicles density. On this basis, through computer random simulations,we found that traffic conditions can be divided into three statuses,and found out the key conditions of formation for each status. The results can be widely promoted, and can provide advice to government

The Study of Traffic Queuing Based on Computer Simulations and Queuing Theory

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The Study of Traffic Queuing Based on Computer Simulations and Queuing Theory