Localization for Wireless Sensor Networks Assisted by Two Mobile Anchors with Improved Grey Wolf Optimizer

Localization is crucial to wireless sensor networks. Among the recently proposed localization algorithms, mobile anchor-assisted (MAL) algorithm seems promising. A MAL using a single anchor has low energy consumption but high error. Conversely, with three or more anchors minor errors consumption. By balancing and accuracy, our study developed assisted by two anchors. traverses network along double SCAN (DASCAN) path, which divides deployment region into grids requires traverse different horizontal lines in zigzag pattern. Sensor nodes estimate their locations multiple-disturbance strategy grey wolf optimization (MDS-GWO) algorithm, improves introducing nonlinearly decreasing weight, random perturbation of wolves mirror wolf. Using MATLAB, DASCAN was compared GTURN, GSCAN, PP-MMAN, H-Curves, M-Curves, paths rates. The error MDS-GWO trilateration, PSO, WOA, GWO. impacts radio irregularity, radius, fading effect on were also analyzed. simulation results showed that was, average, 30.1% less than they had almost same accuracy. an average 18.67% SCAN, 32.3% M-Curves. 25.5% Moreover, performance affected setups methods.