## 2 Related Work
Among them, the proposed scheme in Ref. [18] considers the transmission range of the destination node and the received signal strength (RSSI) to enable the construction of routing paths by self-electing the next hop at each step while performing  
Figure 1: Local-maximum problem when a packet reaches node x that is closer to its destination node D than any other node (w,y,v,z) within the range. Figure 2: Local-minimum problem when a packet reaches node A and there is no direct neighbor closer to the sink than node A itself  
data aggregation. In Ref. [19], the main idea is to exploit the Q-learning technique to estimate the distance from a node to the hole. The routing decision is then determined based on the residual energy of the nodes, their estimated distance to the holes, and their distance to the destination. The proposed geographic routing protocol, named BSMH in Ref. [20], is a load-Balanced and constant Stretch protocol for bypassing Multiple Holes in WSNs. BSMH considers three essential network lifetime impact factors: routing path length, control overhead, and load balancing. The limitation of the protocol is that it still suffers from extra costs caused by the first two phases (i.e., hole determination and hole information dissemination). On the other hand, the authors in Ref. [21] proposed an energy-aware dual-path geographic routing (EDGR) protocol for better route recovery from routing holes. EDGR adaptively utilizes the location information and residual energy to make routing decisions and dynamically exploits two node-disjoint anchor lists passing through two sides of the routing holes to shift the routing path for load balance. However, EDGR cannot guarantee the improvements in the network performance in terms of packet delivery ratio, delivery delay, and network lifetime. In Ref. [22], the authors proposed an energy-efficient routing protocol for Opportunistic Networks using Markov Chain (called ELPFR-MC) in which the next best hop selection of a message relies on the node's residual energy and location-based delivery probability for message forwarding. However, the ELPFR-MC protocol was not investigated using real-trace mobility models. Furthermore, the frequent network disconnection problem is the most critical issue in designing a hybrid network of VANET-WSN. The proposed EMHR [23] is a hybrid network of VANET-WSN that suffers from network disconnection caused by the mobility of vehicles and battery drainage of sensors. In Section 6.2.2, EMHR performance has been comparatively evaluated with CLWPR. By conducting extensive simulation experiments, EMHR demonstrates a higher Packet Delivery Ratio and Throughput and lower end-to-end delay in the hybrid network of VANET-WSN. However, CLWPR demonstrates an improvement in energy consumption using the carry-and-forward mechanism. This is the reason we have selected EMHR as the basis of our work and extended it to the SCF mechanism, as explained in Section 4. Therefore, we propose a novel routing protocol, called the Energy-Mobility-Connectivity aware routing protocol (EMCR), to disseminate messages in the hybrid network of VANET-WSN, aiming to manage network partition problems. The proposed scheme adopts a novel store/carry-forward (SCF) mechanism to overcome network partition problems. The SCF scheme is expected to distribute warning messages with low overhead and a high delivery ratio. In addition, the study in Ref. [24] claims that VANET-WSN can be improved in the future by integrating the 5G New Radio (NR) air interface, which adds expanded functions on top of the 5G NR air interface to facilitate connected and automated driving.