# Optimization of Clustering in Wireless Sensor Networks: Techniques and Protocols
## 3 Existing Literature Reviews on Clustering Based on Optimization  
Previous scholars have extensively reviewed and surveyed clustering techniques in WSNs. Table 1 summarizes these studies based on their contributions. Ref. [9] was the first attempt to survey swarm intelligence-based routing techniques by considering their application areas and simulation platforms. However, only swarm intelligence-based protocols were considered in this survey, while other promising swarm-based protocols were not considered. The cluster-based routing techniques for homogeneous SNs were comprehensively reviewed in Ref. [10] by classifying them based on their objectives and clustering methods; the considered parameters of the review were CH selection, data aggregation, cluster formation, and data communication. In each phase, detailed classifications of the clustering techniques for homogeneous networks were also provided with reference to existing studies since 2011. The reviewed CH selection methods were classified into assisted, multi-factor, and self-organized evaluation schemes. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Ref** & **Year** & **Area of Study** & **Contribution** \\ \hline
[9] & 2011 & Swarm Intelligence & Categorized WSN routing protocols based on the concept of SI and its importance in routing \\
[10] & 2012 & Classical and Fuzzy-logic & Provided a classification of cluster-based methods based on their strategies and goals \\
[11] & 2012 & Classical & Review and summarized the goals of different clustering routing protocols. Provided a classification of WSN clustering techniques based on their cluster attributes \\
[12] & 2014 & Classical & Reviewed different clustering approaches by comparing their cluster size, complexity, algorithmic complexity, and cluster count \\
[13] & 2015 & Classical and heuristic & Reviewed the existing clustering methods in terms of their advantages and challenges, and classified the cluster-based routing methods into block, grid, and chain-based clustering \\
[14] & 2016 & Classical & Analyzed the popular clustering schemes quantitatively and qualitatively using performance metrics, such as cluster formation, communication, management, and complexity \\
[9] & 2018 & Classical, Swarm Intelligence & Compared existing homogeneous and heterogeneous clustering methods, as well as distributed and centralized clustering methods \\
[15] & 2019 & Classical, Fuzzy and Heuristic-based & Some unequal clustering methods. The approaches were also classified and compared based on cluster properties, clustering process, and \\
[16] & 2019 & Classical, Fuzzy and Heuristic-based & CH attributes \\
[17] & 2019 & Classical, Fuzzy and Heuristic-based & Considered classification criteria and parameters to evaluate some existing clustering methods. Four categories of clustering techniques were recognized in this work, which were classical, fuzzy-based, meta-heuristics-based, and hybrid meta-heuristics-based schemes \\  & & Review of machine learning-based hierarchical clustering techniques and classification of the algorithms based on their computational intelligence into swarm intelligence, fuzzy logic, neural network, genetic algorithm, and reinforcement learning \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Literature reviews of clustering protocols. Ref. [11] reviewed the existing clustering routing protocols by classifying clustering algorithms into two categories (data-transmission and cluster-construction routing techniques). Sixteen popular and important clustering methods were considered in this review, while other new approaches, such as fuzzy and evolutionary-based methods, were not considered. Fuzzy modeling-based node clustering methods in WSNs were reviewed in this work, focusing on their advantages and limitations. A classification of fuzzy and hybrid fuzzy-based clustering methods was also presented. Ref. [12] focused on cluster-based routing techniques based on various methodologies.