## 4 Survey of Existing Works
### PSO in WSNs
#### 4.1.3 PSO in Energy Aware Clustering  
WSNs are mainly characterized by their limited energy supply. Hence, the need for energy efficient infrastructure is becoming increasingly more important since it impacts the network operational lifetime, so balanced usage of energy is a critical issue in WSNs. Typically communication is the most energy-expensive act that nodes perform. Energy required to transmit \(l\) bits of data varies exponentially with transmission distance \(d\), so it is common to use multi-hop communication. Routing in WSN refers to the selection of a definite path for a packet to go from a source node to a sink. The hierarchical routing has its all nodes clustered into groups. A cluster-head (CH) acts as the main node in a particular cluster that collects all the data from other non cluster head nodes. A node that acts as a CH for a long duration loses its energy prematurely, so an optimal cluster-head election mechanism is essential. Again, proper CH assignment influences network performance and longevity. [PERSON] _et al._ proposed low energy aware clustering hierarchy (LEACH) which is a simple and efficient algorithm [58]. As we already know from previous discussion that clustering is an NP-hard problem, which bio mimetic optimization methods like PSO can handle efficiently. The first PSO approaches in selecting CH efficiently can be found in [10]. [PERSON] _et al._ proposed a method using PSO that tries to equalize the number of nodes and candidate CH in every cluster of a network, with the target of minimizing the energy spent by the nodes while maximizing the data transmission. However, no comparison with other benchmark clustering strategies has been addressed. In [11] the authors consider both available energy in nodes and physical distances between them and their CHs. They defined a new cost function, with the purpose of minimizing the intra-cluster distance and optimizing the energy consumption of the network at the same time. Proposed protocol selects a high-energy node as a CH and produces clusters that are equally placed throughout the entire WSN field. The performance of the protocol is later compared with the well known cluster-basedprotocols like LEACH and LEACH-C (an improved version of LEACH) and simulation results demonstrated better network lifetime and data delivery at the BS. The fitness function for the centralized PSO (PSO-C) is defined as \(cost=\beta\ \times f_{1}+(1-\beta)\ \times f_{2}\), where \(f_{1}\) is the maximum average Euclidean distance of nodes to their associated cluster heads and \(f_{2}\) is the ratio of total initial energy of all nodes to the total energy of the cluster-head candidates in current round. The key difference between the works [10] and [11] is the application of PSO to choose the optimal nodes as cluster heads to extend the network lifetime. In [59] authors [PERSON] _et al._ proposed a revised PSO to one clustering algorithm named Weighted Clustering Algorithm (WCA), in sensor networks. WCA is a recent clustering algorithm, which was revised to be suitable for dense mobile nodes distribution here. Then, Divided Range Particle Swarm Optimization (DRFSO) algorithm was applied to this revised WCA optimization. The particles were divided into groups running in four neighbourhood nodes simultaneously. The approach restricts the number of nodes to be catered by a CH to ensure efficient medium access control (MAC) functioning. It has also the flexibility of assigning different weights and takes into account a combined effect of the ideal degree, transmission power, mobility, and battery power of the nodes. Simulation study showed competent and effective results over other methods, especially when the distribution of mobile nodes is dense. Four variants of PSO were proposed by [PERSON] _et al._ in [60] for energy aware clustering, namely PSO with time varying inertia weight, PSO with time varying acceleration constants, hierarchical PSO with time varying acceleration constants, and PSO with supervisor student mode.