Open AccessOptimization of Aviation Wireless Sensor Network based on Discrete Cuckoo Search Algorithm
Author(s) -
Rui Yang,
Min Xu,
Jie Zhou
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/926/1/012025
Subject(s) - cuckoo search , computer science , particle swarm optimization , wireless sensor network , algorithm , binary number , cuckoo , convergence (economics) , ant colony optimization algorithms , mathematical optimization , metaheuristic , jump , real time computing , mathematics , computer network , zoology , physics , arithmetic , quantum mechanics , economics , biology , economic growth
Aiming at the problems of multiple coverage blind areas, poor monitoring quality, and low utilization of sensor network nodes in aviation wireless sensor networks, a discrete cuckoo search (DCS) is proposed, and an objective coverage optimization function is established. Aiming at the fact that the previous cuckoo search is not suitable for discrete values, the binary code conversion formula is used to perform binary code conversion on the jump path of each position update of Levy flight, which makes the algorithm converge faster and avoids the limitations of local search. In the simulation, the discrete cuckoo search was compared with ant colony optimization (ACO) and particle swarm optimization (PSO). Simulation experiment results show that the proposed discrete cuckoo search (DCS) has a great advantage in convergence speed, more targets are detected, and the target coverage in the aerial wireless sensor network is effectively improved.