Abstract
Sensor localization in wireless sensor networks has been addressed using mobile anchor (MA) and a metaheuristic algorithm. The path of a MA plays an important role in localizing maximum number of sensor nodes. The random and circle path planning methods have been presented. Each method has been evaluated for number of localized nodes, accuracy, and computing time in localization. The localization has been performed using trilateration method and two metaheuristic stochastic algorithms, namely invasive weed optimization (IWO) and cultural algorithm (CA). Experimental results indicate that the IWO-based localization outperforms the trilateration method and the CA-based localization in terms of accuracy but with higher computing time. However, the computing speed of trilateration localization is faster than the IWO- and CA-based localization. In the path-planning algorithms, the results show that the circular path planning algorithm localizes more nodes than the random path.
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