# A Survey on Node Clustering in Cognitive Radio Wireless Sensor Networks
## 6 Survey of Some of the Existing Node Clustering Techniques  
Many node clustering schemes have been proposed in the literature for the different objectives and goals. [PERSON] et al. [10] proposed a cluster-based MAC protocol called KoN-MAC for CR-WSNs. It is based on a clustering scheme for WSNs by [PERSON] and [PERSON] [52]. [PERSON] et al. [11] proposed a MAC protocol for cluster-based CR-WSNs, but its MAC scheme is based on the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol [53], which is specially designed for WSNs. A novel clustering-based spectrum sensing (CBSS) in CR-WSNs was proposed by [PERSON] et al. [12]. In this method, sensor nodes are grouped into different sets based on their similarity in sensing results. An objective function is proposed to identify the optimal cluster number. Details for cluster formation and CH selection were not given, and the performance was not compared with existent algorithms. [PERSON] and [PERSON] [13] proposed a clustering scheme for cooperative spectrum sensing based on other approaches [20; 23]. In the scheme, a pair of nodes in a group can alternate between sleep and wake modes during the sensing process. A spectrum-aware cluster-based energy-efficient multimedia (SCEEM) routing protocol was proposed by [PERSON] et al. [14]. In this protocol, SU nodes form a cluster with a higher number of commonly available idle channels. The CHs are selected based on energy and relative spectrum awareness, such that noncontiguous available spectrum bands are clustered and scheduled to provide continuous transmission opportunities. [PERSON] et al. [15] proposed clustering with temporary support nodes (CENTRE). This scheme has a fixed cluster formation duration. It assumes that CMs adjust transmission power based on distance to the CH. [PERSON] et al. [16] proposed an energy-efficient spectrum-aware reinforcement learning-based clustering (ESA-RLC) algorithm for CR-WSNs. In this algorithm, a member node learns the energy and cooperative sensing costs for neighboring clusters in order to achieve an optimal solution. [PERSON] and [PERSON] [17] proposed a clustering scheme called BECHR for CR-WSNs. This scheme selects a CH based on residual energy in an iterative manner. It works like conventional WSN clustering methods but with some variations. [PERSON] et al. proposed a spectrum aware clustering protocol for CR-WSNs called CogLEACH [18]. It is an extension of the LEACH protocol, and uses the number of vacant channels as a weight in the probability for each node to become a CH. This work evaluates CogLEACH in three different models. It extends the throughput and lifetime of the network, compared to the regular LEACH protocol that operates in the same settings. [PERSON] et al. [19] and [PERSON] et al. [21] proposed distributed spectrum-aware clustering (DSAC) for CR-WSNs based on group-wise constrained (GWC) agglomerative clustering (GCAC) [54]. The basic idea is to set each node as a disjoint cluster at the beginning, and to merge the two nearest clusters during each iteration until the cluster number is reduced to the optimal number. During each iteration, the inter-cluster distances are recalculated. Initially, DSAC considers each node as a CH, and then merges CHs within each iteration until the number of CHs reaches the optimum number. [PERSON] et al. [20] proposed an energy-aware clustering (EAC) algorithm. [PERSON] et al. [23] and [PERSON] and [PERSON] [55] proposed event-driven spectrum-aware clustering (ESAC) and mobility-aware Event-to-sink Spectrum-Aware Clustering (mESAC) protocols that form temporal clusters for each event in CR-WSNs. These protocols determine eligible nodes for clustering based on the local position of nodes between the event and the sink. CHs are selected from among the candidate nodes based on node degree, channel availability, and distance to the sink. Because this is event-driven clustering, the clusters are immediately dismissed after finishing data transmission. Hence, it is not suitable for other scenarios. [PERSON] et al.