This paper demonstrates a recapitulated historic evolution further to a future overview of all vehicular ad-hoc network (VANET) routing problems that concern either directly related routing tasks or targeting a set of diverse routing-related techniques with the aid of the bio-inspired approaches. In this lecture, we serialize, in a synchronous observation, the evolution and tendencies of the VANET routing problem’s solving simultaneously with the emergence of different classes of nature-based meta-heuristics, by bringing a proposed taxonomy of different major VANET routing problems seen their nature, studied range and metaheuristic types used for their optimization. Then, we follow with a visionary deduction of the other appearing routing issues of VANETs that can be approached or already began to be solved by nature-inspired optimization algorithms. Noting that each spread routing problem is illustrated with notable related works, describing initially realized conventional protocols to vulgarize different routing modules, then detailing bio-inspired protocols for VANET routing to explain the utility of nature-inspired optimization techniques. The motivation of this work came from the lack of a reference classifying the VANET-related routing problems within the notion of nature-inspired optimization. That’s further to giving and up-to-date literature on the context for opening out a visionary opinion on the tendencies of either emerging recent bio-inspired optimization approaches or the different metaheuristic-based combinations on specific VANET routing problems.

中文翻译：

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仿生 VANET 路由优化：概述

本文展示了对所有车辆自组织网络 (VANET) 路由问题的未来概述的重述，这些问题涉及直接相关的路由任务或借助仿生方法针对一组不同的路由相关技术. 在本讲座中，我们通过提出不同主要 VANET 路由问题的分类法，在同步观察中序列化了 VANET 路由问题解决的演变和趋势，同时出现了不同类别的基于自然的元启发式算法。性质，研究范围和用于优化的元启发式类型。然后，我们随后对 VANET 的其他出现的路由问题进行了富有远见的推论，这些问题可以通过自然启发的优化算法来解决或已经开始解决。注意到每个传播路由问题都用显着的相关工作进行了说明，描述了最初实现的传统协议来粗化不同的路由模块，然后详细介绍 VANET 路由的生物启发协议，以解释自然启发优化技术的效用。这项工作的动机来自于缺乏参考自然启发优化的概念对与 VANET 相关的路由问题进行分类的参考。