Smart Objects Localization by Improved IDVHOP Algorithm and the WOA Optimization Algorithm
Sensors of the Internet of Things and wireless sensor networks need accurate localization to provide information, such as road information. Installing a locator on all the nodes and sensors is very expensive, and, for this reason, indirect localization is done. One of the low-cost localization methods is DVHop algorithm. Due to the simplicity of DVHop algorithm, its execution time is not long; for this reason, it does not impose much energy consumption, and it is considered a low-cost algorithm. One of the challenges of the DVHop method is its significant error in localization. To solve this problem, in the present paper, a smart locator system is presented using the DVHop algorithm and improved Whale optimization algorithm to estimate the location of objects and sensors. The proposed method has three main steps for smart localization. Experiments showed that the proposed method has less localization error than PSO, WOA, GWO, and HHO algorithms and has high stability due to less standard deviation in localizing the error. Compared to the DVHop, PSODVHop, GSODVHop, and DEIDVHop, the proposed method reduces errors by 1.73, 1.60, 1.28, and 1.13 times, respectively.