Multistrategy Integrated Marine Predator Algorithm Applied to 3D Surface WSN Coverage Optimization

Achieving maximum network coverage with a limited number of sensor nodes is key to node deployment wireless (WSN). This paper proposes an improved marine predator algorithm (IMPA) for 3D surface deployment. A population evolution strategy based on random opposition-based learning and differential operator proposed enrich the diversity improve global search capability algorithm. The grouping idea Shuffled Frog Leaping Algorithm (SFLA) then introduced. local SFLA replace FADs effect MPA enhance ability escape from optimum. quasireflected also presented optimization accuracy, accelerate convergence speed algorithm, quality solution. Fifteen benchmark functions are selected testing. results compared seven different algorithms. show that has excellent performances. Finally, IMPA applied optimize WSN surfaces. experimental good terrain adaptation optimal capabilities. It can network, reduce cost, extend life cycle.