Abstract
WSN has been directed from military applications to various civil applications. However, many applications are not ready for real world deployment. Most challenging issues are still unresolved. The main challenge facing the operation of WSN is saving energy to prolong the network lifetime. Clustering is an efficient technique used for managing energy consumption. However, clustering is an NP hard optimization problem that can’t be solved effectively by traditional methods. Computational Intelligence (CI) paradigms are suitable to adapt for WSN dynamic nature. This paper explores the advantages of CI techniques and how they may be used to solve varies problems associated to WSN. Finally, a short conclusion and future recommendation is being provided.
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