论文标题
GMACO-P：GPU辅助先发制人澳门算法，以实现智能运输
GMACO-P: GPU assisted Preemptive MACO algorithm for enabling Smart Transportation
论文作者
论文摘要
车辆临时网络（VANETS）正在以非常快速的速度开发，以通过减少拥塞来减少通勤者的旅行时间，从而使城市城市的智能运输能够在城市城市进行智能运输。效率低下的交通信号和路线机制是导致道路拥堵增加的主要因素。为了使交通流动更平滑并减少道路上的交通拥堵，必须减少交叉路口的等待时间，并应同时选择最佳路径。在本文中，已提出了GPU辅助的先发制人MACO（GMACO-P）算法，以最大程度地减少通勤者的总旅行时间。 GMACO-P是MACO-P算法的改进，它利用GPU的利用功率来提供更快的计算，以进一步最大程度地减少旅行时间。 MACO-P算法基于现有的MACO算法，该算法避免了拥塞的路径。 MACO-P算法通过合并预先设定的抢占量来减少交叉点的平均队列长度，从而确保较少的等待时间。在本文中，提议GMACO-P算法利用GPU提高MACO-P的力量以进一步减少旅行时间。使用C语言使用CUDA工具包7.5执行GMACO-P算法，并将获得的结果与现有的Dijkstra，ACO，MacO，MacO-P，并行实现Dijkstra，ACO和MACO算法。获得的结果表明，使用拟议的GMACO-P算法后，旅行时间的显着减少。
Vehicular Ad-hoc NETworks (VANETs) are developing at a very fast pace to enable smart transportation in urban cities, by designing some mechanisms for decreasing travel time for commuters by reducing congestion. Inefficient Traffic signals and routing mechanisms are the major factors that contribute to the increase of road congestion. For smoother traffic movement and reducing congestion on the roads, the waiting time at intersections must be reduced and an optimal path should be chosen simultaneously. In this paper, A GPU assisted Preemptive MACO (GMACO-P) algorithm has been proposed to minimize the total travel time of the commuters. GMACO-P is an improvement of MACO-P algorithm that uses the harnessing the power of the GPU to provide faster computations for further minimizing the travel time. The MACO-P algorithm is based on an existing MACO algorithm that avoid the path with the congestion. The MACO-P algorithm reduces the average queue length at intersections by incorporating preemption that ensures less waiting time. In this paper, GMACO-P algorithm is proposed harnessing the power of GPU to improve MACO-P to further reduce the travel time. The GMACO-P algorithm is executed with CUDA toolkit 7.5 using C language and the obtained results were compared with existing Dijkstra, ACO, MACO, MACO-P, parallel implementation of the Dijkstra, ACO and MACO algorithms. Obtained results show the significant reduction in the travel time after using the proposed GMACO-P algorithm.
