# A Connectivity-Based Clustering Scheme for Intelligent Vehicles
## 2 Literature Review
### Cluster-Based Routing Schemes  
[PERSON] et al. [1] presented a triple cluster-based routing protocol (TCRP), aiming to reduce the communication overhead by limiting the broadcast domain. In TCRP, CH was selected based on the vehicle position (centralized) inside the cluster and its subsequent speed variance (less variation in speed). The authors used the dynamic programming approach (i.e., Floyd-Warshall algorithm) for CH selection. From their simulation results, it was noted that TCRP significantly reduces CH reselection probability in further rounds. The TCRP performs very well in terms of CH stability and scalability. However, the pre-specified number of clusters (i.e., three clusters) is not a suitable approach in many scenarios. The three-cluster approach in highly congested traffic leads to an excessive number of route request messages (RRMs) and computational overhead. Secondly, in the sparse traffic situation (one or two vehicles), it is not suitable due to the limited number of cars.  
In [4], the authors introduced the Multi-hop Moving Zone (MMZ) scheme for Cellular-V2X (C-V2X) communication. Inspired by the prominent issues of pure V2V-based clustering (i.e., network disconnection and broadcast storm) [7], the authors disclosed the MMZ clustering scheme for reliable and low-latency communications in C-V2X. In MMZ, the zonal heads (ZHs), i.e., cluster heads (CHs), are selected through multi-metrics, i.e., relative speed, distance, and link lifetime (LLT). The primary purpose of MMZ was to form stable clusters for high packet delivery and low latency. The C-V2X communication pattern in [4] was composed of two main technologies, i.e., IEEE 802.11p and cellular networks. Firstly, V2X relied on IEEE 802.11p facing several challenges, i.e., limited-mobility support, advanced use cases compatibility issue, limited transmission range, long-delay, and reliability [9]. Secondly, the cellular technology is cost-effective in the practical implications of VANETs [6]. Apart from the technological challenges, the selected metrics ignore the effect of density and transmission ranges. Thus, in this paper, we use link connectivity as a metric for optimum cluster formation and CH selection.  
The authors suggested a novel routing scheme called a two-level cluster-based routing protocol [6], where the Fuzzy logic algorithm selects a stable CH with the help of well-known metrics, i.e., relative velocity factor, K-connectivity factor, and link reliability factor. The connectivity factor selects a centralized and high degree of connectivity node inside a cluster--the reliability factor chooses a robust vehicle as a CH candidate. The authors used improved Q-Learning (IQL) in second-level clustering to reduce the computational cost and to adjust the optimal number of gateways to Long Term Evolution Base Station (LTE BS). The large numbers of agents and actions in IQL cause many unnecessary iterations in gateway discovery. Additionally, the calculation of temporal connectivity and link reliability consumes a considerable amount of time. Our suggested connectivity-based clustering scheme considers the connectivity metric solely for cluster formation and CH selection, aiming to cope with two-level cluster-based routing protocol problems [6].