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The remarkable developments in wireless communication technologies in recent years along with the anticipation of further advances in these technologies have stimulated the efforts to investigate vehicle to everything (V2X) communication to increase road safety, improve traffic management, and facilitate infotainment applications. V2X communication is based either on cellular infrastructures such as 4G and 5G, or wireless LAN technologies such as the IEEE 802 protocol family. Several challenges, however, face the deployment of V2X. Examples of these challenges are routing, security, and analysis of collected data. Several research efforts have investigated computational intelligence methods to tackle these issues. In this paper, we review recent advances in computational intelligence in V2X communications. First, we provide preliminaries of V2X communication. Second, we discuss classical and computational intelligence solutions in V2X communication. Last, we present open problems and research challenges that need to be addressed to realize the full potential of V2X systems.

Mobile Ad hoc Network (MANET) is the cornerstone for the Internet of Things (IoT) and Vehicle to Everything (V2X) networks, its devices are remarkable of lightweight to be portable and free to join or disjoined the network. Therefore, one of the MANET routing types is reactive routing protocols. Reactive routing protocols set up the connection between devices either on-demand such as Ad Hoc On-demand Distance Vector (AODV) protocol or source routing such as Dynamic Source Routing (DSR) protocol. Reactive routing protocols increase routing overhead on discovering new routes. Thus routing overhead, and delay will increase. In this paper, the method of generating a fuzzy model is presented. Also, a tuned fuzzy stability model is introduced to handle the imprecision of routing decisions by the Fuzzy Stability model for Ad Hoc On-demand Distance Vector (FSAODV) and Fuzzy Stability model for Dynamic Source Routing (FSDSR). The results showed that FSAODV and FSDSR have outperformed the state of art protocols AODV and DSR respectively.

Nowadays, the use of Mobile Ad-Hoc Network (MANET) devices increases extremely. Dynamic Source Routing protocol (DSR) is a reactive routing protocol designated for MANET, whenever a route is demanded, DSR checks route cache, if no route exists; it floods the network with Route Request packets (RREQ). Route discovery process may result in multiple RREQ packets traversing the network until a Route Reply packet (RREP) is sent back. However, the discovered route may contain nodes with no backup routes to the next hop then path failure may occur. Moreover, due to users’ mobility and limited transmission ranges, the routing protocol should consider routes stability. Therefore, improving routing will enhance the whole network performance. In this paper, two fuzzy models were proposed to enhance routing decisions by Fuzzy Stability models (FSDSR1 & FSDSR2). The proposed models consider the following parameter: route discovery time, total route replies, delivery ratio, and the number of retransmission attempts, MANET delay, and throughput. The results showed that FSDSR2outperformed the state of art protocol DSR and FSDSR1.

Today’s wide spread use of mobile devices such as: mobile phones, tablets, laptops and many others had driven the wireless Mobile Network growth especially the Mobile Ad hoc Networks commonly referred to as MANETs. Since the routing process is regarded as the core of communication and is associated with the network performance metrics, then its improvement will be revealed in the whole network performance improvement. Due to users’ mobility, limited battery power, and limited transmission ranges, the current routing protocols should consider the stability of routes. Hence, the lack of resources of MANETs may result in imprecise routing decisions. In this paper, the proposed fuzzy model is used to handle imprecision of routing decisions by Fuzzy stability model for Dynamic Source Routing (FSDSR). Regarding the number of hops per route, cache size, end-to-end delay and route discovery time, the results showed that FSDSR has outperformed the state of art protocol Dynamic Source Routing protocol (DSR).