# Optimized Clustering Algorithms for Large Wireless Sensor Networks: A Review
## 3 Optimized Hierarchical Based Routing Protocols
### Swarm Intelligence
#### 3.5.1 Particle Swarm Intelligence  
The Particle Swarm Optimization (PSO) is an evolutionary computation technique and is related to the bird flocking, fishing schooling, and swarm theory. Like the other evolutionary computation techniques, PSO is a population-based search algorithm and is initialized with a population of random solutions, called particles. A particle will have a fitness value, which will be evaluated by a fitness function to be optimized in each generation [53; 54]. In order to increase the performances of WSNs, clustering strategies using PSO are proposed nowadays. PSO-C  
An energy-aware clustering approach for WSN using PSO is proposed in [55]. The authors presented a distance based and centralized approach which takes into account the maximum distance between the non-cluster head node and its CH, and the remaining energy of CH candidates in the CH selection. In the beginning, during the setup phase, all nodes send information about their residual energy and positions to the BS. To ensure that only nodes with a sufficient energy are selected as CHs, the nodes with an energy more than the average are eligible to be a CCH for each round. The PSO algorithms are executed at the BS to determine the best k-CHs which can minimize the cost during routing. PSO-C is compared to the traditional clustering LEACH and its amelioration version LEACH-C on two different scenarios. In the first scenario, the BS is located within the sensor field, whereas in the second scenario the BS is located outside the sensor field. The results after simulations have shown that PSO-C improves the amount of data delivered to the BS to 101%, 25% better than LEACH and LEACH-C, respectively, for the first scenario and 60%, 50% for the second scenario. PSO-C also increases the network lifetime by improving the number of alive nodes in both scenario. [PERSON] & [PERSON] [56]  
Authors propose an energy efficient clustering and routing algorithms for WSN based on the PSO paradigm. The routing algorithm is developed on an efficient particle encoding scheme with a trade-off between transmission distance and multi-objective fitness function. Meanwhile, the clustering algorithm is presented by considering energy conservation of the nodes through the load balancing strategy. At the beginning (network setup), the protocol performs three phases: bootstrapping (each gateway and node are assigned unique IDs); route setup; and the clustering phase. The gateways can collect the IDs of the sensor nodes and the other gateways that are within their communication range and finally send the information to the BS. All the CHs which are heavily used as next hop relay nodes in data forwarding are assigned a lesser number of sensor nodes. Thus the energy consumption of the CHs is significantly balanced and the lifetime of the network is improved. The algorithms are based on the derivation of efficient particle encoding scheme and fitness function for routing and clustering separately. The algorithm is evaluated using two network scenarios WSN#1 (BS is located outside the sensor field) and WSN#2 (BS is located in the center of the sensor field). The proposed algorithm is compared to GA-based approach and the two clustering strategies GLBCA and LDC. Results show that the proposed PSO-based approach increase significantly the network lifetime (First Gateway Die FGD and Last Gateway Die LGD) on both scenarios than the other three algorithms. Results have also shown that the PSO-based approach increases the data delivered to the BS and reduces the number of hops until the BS than the other strategies. PSO-HC  
The PSO-HC is a hierarchical clustering based on the PSO paradigm [57] to maximize the network lifetime by minimizing the number of active CHs and to maximize the network scalability by using two-hop communication between the sensor nodes and their respective CHs. PSO-HC has also two phases per round: the set-up and the steady phases.