Swarm Intelligence Optimization Algorithms for Localization in Underwater Wireless Sensor Networks

Underwater Wireless Sensor Networks (UWSNs) are the unmanned sensor networks deployed in the marine environment. They are application specific. Basic requirement is to sense and communicate the sensed data to the offshore workstation for further processing. Accuracy of the data depends on the location of the sensor which has sensed it. Hence the distributed sensors have to continuously update the location information to the sink node which is responsible for data aggregation. Localization algorithms are used for this purpose. Mathematical optimization algorithms are found to be energy hunger. Hence in recent years, the researchers got attracted by the implication of Swarm Intelligence (SI) based optimization techniques for localization. There are many localization algorithms got implemented in couple of decades. No single SI algorithm has found the solution for all the problems like energy preservation, network life time extension, increase in performance, scalability of the network, error tolerance level etc. In this paper, we tried to present a brief summary of different SI based algorithms and their suitability for localization in UWSNs.