Computational intelligence based optimization in wireless sensor network

There are only two ways to live your life. One is as though nothing is a miracle. The other is as though everything is a miracle and so the technology advancement which proved to be a miracle of the miracles. Wireless Sensor Network (WSN) is one such miracle of the wireless technology which opens up the new dimensions for the researchers to write the technology of the future i.e. ubiquitous computing and intelligence. Nevertheless nature has played its ultimate role as well to give an idea of perfection in optimizing the teething issues in any field and so in WSN. Design and deployment, localization, routing and clustering, QoS management, security etc are few scenarios in WSN. The computational intelligence paradigm (CI) inspired by nature, comprising artificial neural network (ANN), artificial immune system (AIS), evolutionary algorithm (EA), swarm intelligence (SI) and fuzzy logic (FL). These are different flavors for increasing efficiency in terms of memory and computational power which alternatively affects other issues towards perfection i.e. convenience and intelligence. Hybrid and non hybrid algorithms optimizes the issues through CI paradigms, which are presented in this research article relevant to Wireless Sensor Network. Our findings strongly recommend development of hybrid CI based algorithms to address combinatorial optimizing issues in WSN.