# A Survey on Node Clustering in Cognitive Radio Wireless Sensor Networks
## 2 Clustering in Conventional WSNs  
Because wireless sensor nodes are battery-operated tiny devices, energy conservation has significant importance when designing the physical layer for WSNs. They are deployed in harsh environmental conditions, and the sensor devices are inaccessible after deployment. Therefore, it is not always possible to replace the sensors' batteries. Valid, accurate, and reliable data collection basically depends on the sensors' lifetime, which is determined by residual energy of the system. Hence, the most important challenge in WSNs is the efficient use of energy resources.  
In WSNs, energy consumed for sensing and computation is much lower than for communications [29]. Therefore, a majority of the total energy consumed in WSNs is transmission power, and the required transmission power grows exponentially with an increase in transmission distance. In general, the minimum output power required to transmit a signal over distance \(d\) is proportional to \(d^{n}\), where \(2\leq n<4\). The exponent \(n\) is closer to 4 for low-lying antennae and near-ground channels, as is typical in wireless sensor network communications [30]. Therefore, routes that have more hops with shorter hop distances can be more power-efficient than those with fewer hops but longer hop distances. Clustering encourages sensor nodes to communicate in multihop fashion, which extends the lifetime of WS networks. If the node density is high enough, it can also effectively overcome shadowing and path loss effects.  
There are several strategies in the literature to conserve energy and extend WSN lifetime, such as data reduction [31], protocol overhead reduction [7], reducing the duty cycle [32], energy-efficient routing design [33], energy-efficient MAC design [10; 34], and energy harvesting [35; 36]. These strategiesreduce energy consumption by controlling and mitigating the sensing process, the communications process, collisions, overhearing, control packets, idle listening, and interference [7; 31; 32; 33; 34]. Among these strategies, the ability to harvest energy from the environment is highly dependent on many environmental factors. The current state of technology in energy harvesting is still unable to provide a sustained energy supply to enable WSNs to operate continuously [35; 36].  
Clustering has the advantages of load balancing and scalability, and can extend WSN lifetime when the network size grows. In clustering, wireless sensor nodes are usually grouped into physically disjointed, and often non-overlapped, clusters. All the contiguous nodes are in one or more clusters according to a cluster formation algorithm. Based on the clustering schemes, there is a leader in each cluster, often called a cluster head (CH). The CH is responsible for data aggregation, information dissemination, and network management, and the cluster members (CMs), i.e. non-cluster head nodes, are responsible for event sensing and information collection from their surroundings.  
CHs perform the task of intra- and inter-cluster management and data processing. Some of the responsibilities of CHs include coordination between inter-clusters and intra-clusters, such as cluster formation, data aggregation, and communications with the base station (BS). Each WSN consists of one or more sinks or base stations collecting information from sensor nodes. Figure 1 shows a conventional clustering structure of a typical WSN. As shown in Figure 1, sensor nodes are divided into a number of virtual groups (dotted lines) based on predefined clustering schemes. Inside a cluster, a sensor node may have a different status or function, such as a CH, or a CM. Several types of clustering exist, such as static, dynamic, single-hop and multihop, homogeneous and heterogeneous.