## 1 Introduction
Although the choice of the first criteria has the capability of assuring node-to-node quality links, it cannot be classified as an efficient solution for resource-constrained CRSN, because, this means a greater number of hops will be required to transmit a packet to the sink. The implications of this choice include amplified end-to-end delays and additional energy incurred for the multiple hop-to-hop communication to the sink. On the other hand, if the closest node to the sink criterion is made, which is the typical greedy forwarding scenario, the existence of unreliable links, which is referred to as the weakest link problem, is encountered. For this strategy, at each hop, the neighbors that are closest to the destination (also likely to be farthest from the forwarding node) may have poor links with the current node. These \"weak links\" will usually result in a high rate of packet drops, resulting in drastic reduction of the delivery rate or increased energy wastage if re-transmissions are employed. Thus, the question arises: what is an efficient and reliable way of implementing geographical forwarding for CRSNs? While reliability via instantaneous channel quality assessment can easily be implemented in traditional WSN [14, 15, 16], the contrary is usually the case for CRSN. This is because instantaneous quality can easily be determined in traditional WSN, since both the next hop decision and packet transfer are done on the same channel. Thus, a transmitting node can decide which among its neighbors have the best channel quality at the point of packet transmission. This, in turn, greatly improves the reliability of such a network. Given the rapid dynamic nature of channel quality variation with time, added with primary user (PU) activity, as is the case of CRSN and CR _ad hoc_ networks generally, the issue of the instantaneous confirmation of channel quality becomes very challenging for AODV-modeled protocols, because both the channel decision and next hop decision is usually concluded via a separate channel, referred to as the control channel, which is different from the data channel. As a result of these issues, recent studies have indicated the need for research efforts to incorporate reactive energy-efficient data-transfer components into AODV strategy-based protocols [8]. In line with this need, we have proposed a virtual cluster-based reliable opportunistic routing (ROR) approach to routing in CRSN. Typical to all on-demand routing protocols, where a path is only sought when it is required, and the same is maintained to the end of the transmission process, ROR provides a very robust routing framework that fuses a reactive geographical forwarding scheme into AODV to create a robust scheme that considers the link quality of communicating nodes for data forwarding. Our strategy disconnects between the joint channel and next hop assignment process, which is a prevalent approach in most routing in CR-based _ad hoc_ networks [17]. In ROR, all control signaling is done through CC, and the route request phase is used to search for all possible routes from the source node to the sink. The sink selects the best route that offers certain quality of service (QoS) guarantee levels, basically based on bandwidth and delay. At this point, since ROR seeks to integrate a dynamic reactive forwarding process into the AODV anchor-based forwarding scheme, all next hop nodes along the chosen path are regarded as local minimum resolution (LMR) nodes. The route reply process is used to group the surrounding nodes of each LMR node into virtual contention (VC) groups based on the correlation of spectrum opportunities. In the data forwarding phase, a VC group (VCG) receiver-based contention forwarding scheme is implemented. This scheme fundamentally reduces the contention among participating nodes, thereby increasing the chances of successful data transfer across the VCGs to the sink.