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An efficient routing algorithm based on ant colony optimisation for VANETs

机译：一种基于蚁群优化的VANET高效路由算法

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摘要

The Vehicular Ad Hoc Networks (VANET), which are essentially the subset of Mobile Ad Hoc Networks (MANET) have been focused in the recent years mainly for the research and development of the Intelligent Transport Systems having the ability for both self-management and also self-organization, making them reliable as a highly mobile network system Also, the disconnection of such high mobile nodes will be a problem in VANET structure, where the loss of information will be critical because the vehiclesodes in a VANET can move at a speed of 300 km/h or 186.41 miles/h. The protocols suggested earlier used a fixed topology for the mobile nodes in VANET. Even though the scientists had proposed different algorithms like beaconing, greedy or moving directional approach, the environmental changes were ignored which usually play an important criterion in regulation of information. In this paper, we propose a bio-inspired meta-heuristic and mathematically probabilistic technique of the Ant Colony Optimization (ACO) where efficient path establishment and information transfer can be achieved. Path availability and the delay time have been used for the evaluation of discovered paths. But, here the real time environmental changes were taken into account and the performance was measured in accordance with ACO. The technical software for VANET implementation using modifications in the ACO was implemented in the Matrix Laboratory (MATLAB)-2015b simulator along with the different randomized changes in environmental conditions. The random movements of the ants have displayed an efficient means for the delivery of packets to the maximum number of available nodes/vehicles in the network with very low latency. So that even if accidental failure of any node occurs, the surrounding ant neighbors will carry the required information to the desired nodes resulting in improvement of the throughput. Thus, the results obtained through various environmental modifications indicated that the use of randomized ACO algorithm for a highly mobile VANET system offers a much higher performance as compared to other earlier suggested on demand methods and can be realized commercially. Hence, this project tries to become a state of art technology for the benefit of society and the country.
机译：车载自组织网络（VANET）本质上是移动自组织网络（MANET）的子集，近年来主要集中在研究和开发具有自我管理能力和智能能力的智能运输系统。自组织，使其成为高度移动网络系统时的可靠性同样，在VANET结构中，如此高的移动节点的断开连接也是个问题，因为VANET中的车辆/节点可以以一定的速度移动，因此信息的丢失至关重要。时速300 km / h或186.41英里/ h。先前建议的协议为VANET中的移动节点使用了固定的拓扑。即使科学家们提出了诸如信标，贪婪或移动方向方法之类的不同算法，但环境变化却被忽略了，而环境变化通常在信息调节中起着重要的标准。在本文中，我们提出了一种生物启发式的元启发式和数学概率化的蚁群优化（ACO）技术，可以实现有效的路径建立和信息传递。路径可用性和延迟时间已用于评估发现的路径。但是，此处考虑了实时环境变化，并根据ACO对性能进行了测量。通过在矩阵实验室（MATLAB）-2015b模拟器中实现了使用ACO中的修改来实施VANET的技术软件，以及环境条件的不同随机变化。蚂蚁的随机移动显示了一种有效的方式，可以将数据包以极低的延迟传递到网络中最大数量的可用节点/车辆。这样，即使发生任何节点的意外故障，周围的蚂蚁邻居也会将所需的信息携带到所需的节点，从而提高吞吐量。因此，通过各种环境修改获得的结果表明，与其他早期建议的按需方法相比，将随机ACO算法用于高度移动的VANET系统可提供更高的性能，并且可以在商业上实现。因此，该项目试图成为一种先进的技术，以造福社会和国家。

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