A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyberphysical systems

Wireless sensor network (WSN) is an important component of a cyberphysical 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 Lvy 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. Oriented cuckoo search algorithm is designed.Oriented cuckoo search algorithm with different distributions are investigated.CEC2013 28 benchmarks test suits are employed to test and compared with several other algorithms.Oriented cuckoo search algorithm is employed to improve the performance of DV-Hop algorithm.