A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyber–physical systems

Wireless sensor network (WSN) is an important component of a cyber–physical system. Locating node information is a crucial problem for WSN. Currently, distance vector-hop method (DV-Hop), one of popular range-free algorithms, is widely deployed to estimate the location. However, the estimation precision is challenging. In this paper, a new evolutionary algorithm named oriented cuckoo search algorithm (OCS) is designed. In OCS, the global search capability is dominated by the combination of two different random distributions. To provide a deep investigation, ten different random distributions are employed and compared with CEC2013 test suits. Numerical results show the hybrid distribution combined with Lévy distribution and Cauchy distribution achieves the best performance. Furthermore, OCS with this hybrid distribution is also incorporated into the methodology of DV-Hop algorithm to improve the precision performance. Simulation results demonstrate that our modification achieves better precision performance when compared with three other DV-Hop algorithms.