Localization based on Mobility Model in Wireless Sensor Networks
Keywords:
Localization, Mobility Model, SFLA, BFO, Estimation error.Abstract
In implementing functions such as routing, load balancing, and data sharing, the localization of sensor nodes in wireless sensor networks (WSN) is important. Several localization techniques have been used to locate nodes relative to reference nodes in a static environment based on time of arrival (ToA), time difference of arrival (TDoA), angle of arrival (AoA) and received signal strength(RSSI). Although mobility would seem to make localization more difficult, a hybrid algorithm (SFLA-BFO) that is a combination of Shuffle leap frog algorithm (SFLA) and bacterial foraging optimization (BFO) algorithm was introduced in this suggested algorithm to analyze Estimation error based on different mobility models such as Random Walk Mobility (RWM), Reference Point Group Mobility Mode (RPGM), Random Way Point Mobility Mode (RPGM), Random Way Point Model(RWP). The proposed algorithm was simulated using the NS-2 simulator and the findings indicate that the proposed hybrid model performs well.
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