# Adaptive QoS-Aware Multi-Metrics Gateway Selection Scheme for Heterogenous Vehicular Network +
## 2 Related Work
Applications are grouped into three classes, voice, streaming, and data, and the MGW is selected to satisfy the QoS requirement of the given traffic class. Three parameters are used in selecting the best MGW, RSS, load, and link connectivity duration. However, this algorithm only considers non-safety applications, leaving out safety and cooperative traffic performance. Furthermore, the proposed algorithm is unable to distinguish between regular and high-quality video. Since voice traffic is often delay-aware, higher qualities require a high QoS. Moreover, [25] proposed an efficient gateway discovery protocol based on a fuzzy system. The proposed protocol is named DRIVE (DiscoveRy of Internet gateways from Vehicles), which focuses on the discovery and selection of the best MGWs based on the vehicle QoS application requirements. DRIVE uses a proactive gateway discovery mechanism, whereby the Internet gateways geocast themselves to all vehicles within its coverage zone. Four criteria are used in MGW selection. These criteria are: (1) the number of connections to each gateway, (2) available bandwidth, (3) gateway position, and (4) market information. When this information is available, the DRIVE uses fuzzy logic to optimize the MGW selection process. However, the DRIVE protocol results in higher overhead, especially when the number of Internet gateways is high. This is due to the number of advertisement packets that are normally geocast by each gateway. In general, it can be noted that the cluster-based MGW selection mechanisms are efficient in coordinating the vehicles and reducing intervehicle interference. The main challenge, however, is retaining cluster stability. Frequent clustering can occur as a result of poor cluster stability, lowering the overall network efficiency. This issue was addressed in [26; 27; 28], where the authors proposed a non-cluster-based MGW selection scheme that eradicated cluster formation for the MGW discovery and selection processes. The source vehicles either proactively or reactively discover the MGW by broadcasting gateway solicitation messages to all of its neighbors and select the best gateway candidate depending on several parameters. In [12], the authors proposed a non-cluster adept algorithm for selecting the best gateway and base station (BS) in a cloud vehicular mesh (V-Mesh) network. To optimize the gateway and BS collection, a fitness value feature was proposed. The ingress vehicles should consult with the neighbor vehicles (NV) to see whether the gateway is available before communicating with the BS. This is accomplished by sending out a gateway advertising message to all of its neighbors. The NV then sends back a replay message with the following parameters: signal strength of neighboring vehicles, the number of packets in the NV, and the distance between the ingress vehicle and gateway candidates (i.e., the NVs). The gateway is determined by the NV with the highest fitness values. The BS selection process was also explored in this work. The best BS for the chosen MGW vehicle is determined by the number of packets in the BS's buffer and the distance between the MGW and the BS. The best BS is selected as the one with the lowest fitness value. The authors in [27] proposed a location-aided and prompt gateway discovery mechanism (LAPGD). The machine used a hybrid mechanism for gateway discovery. The LAPGD chose the best gateway based on velocity and intervehicle distance to accommodate a large number of vehicles in its region. Owing to the small number of open gateways, the proposed mechanism causes a significant load to be placed on the chosen gateway. Furthermore, the chosen vehicle's ability to serve as a gateway requires further investigation. In [26], the authors suggested a mechanism that allows vehicles to discover neighboring fixed gateways and choose the best one based on a variety of efficiency metrics. The number of hops to the gateway, gateway throughput, traffic load, and path expiration time are all considered for GWS.