# Optimization of Clustering in Wireless Sensor Networks: Techniques and Protocols
## 4 The Fundamentals of Clustering
### Solution Scope of Clustering  
The clustering of nodes in a WSN is usually carried out with different purposes and objectives, but the commonest objective is energy conservation. These objectives can be categorized into primary and secondary categories; primary objectives are considered the most substantial and essential during the clustering process, while secondary objectives are considered less consequential but can be indirectly achieved through clustering the network nodes. An overview of the common objectives of clustering is presented in Figure 4. Some of the objectives of WSN clustering are briefly explained below.  
1. Load balancing: Clustering is implemented to achieve low-energy intra-node communication and data processing [35]. Within the clustering architecture, the CHs perform the duty of data gathering and aggregation, long-range communication, and data forwarding. As such, the energy of the CHs deteriorates more quickly; this is why it is important to rotate these roles among all the network nodes using load balancing schemes to ensure energy efficiency;  
Figure 4: WSN clustering objectives.  
2. Fault-tolerance: The deployment of WSN is usually in areas not easily accessible to human beings; therefore, such networks should have fault tolerance and be able to self-reconfigure in such deployment areas. The network must be designed such that the failure of one node cannot affect the general performance of the network [36]. According to Ref. [37], node clustering remains an effective way of making WSNs fault-tolerant and secure. The adaptive clustering method addresses faults in CHs through readjustments at the beginnings of pre-determined periods [14];
3. Scalability: The application area determines the number of SNs deployed in a sensor network [38]. The scalability of large networks can be increased by using hierarchical architectures where the network is divided first into virtual layers and subsequently into clusters [39]. In cases when a node in one cluster establishes a connection with another node outside its cluster, that node must have some information regarding the CH of the cluster of the node that intends to communicate with it; this increases network scalability and reduces the size of the routing table;
4. Network topology: The clustering of nodes into clusters makes it easy for CHs to manage location changes among the nodes within their clusters. Thus, it is more convenient for managing changes in network topology than flat architecture where there are numerous mobile nodes. Each CH in a clustered WSN is aware of its members' locations and levels of energy; therefore, the death of a node or its movement to another cluster is registered and reported instantly by the CHs;
5. Lifetime: The greatest challenge in WSNs, as mentioned earlier, is the extension of the network lifespan for as long as possible. It is believed that this objective can be achieved by deploying clustering mechanisms that meet all the highlighted characteristics. For instance, the positioning of CHs at the node center will ensure rotation of the CH role among all the nodes in the network and the effective utilization of sleeping schemes to improve the network's lifetime;
6. Data aggregation: Due to most data's uniformity in WSNs, data aggregation is important to prevent the transmission of similar packets through the network. Most data aggregation methods are signal processing-based; in WSNs, a standard data aggregation method combines all the incoming packets into one output packet [40]. All nodes must transmit their data to the BS in flat architectures via either a direct approach or a multi-hop one; however, some data aggregation methods can only be used in flat architectures that use data-centric applications [41]. Clustering allows data aggregation in the CHs, improving energy efficiency by reducing the total network load.