This paper presents an improvement of the flower pollination algorithm (FPA) for optimization localization issues in wireless sensor networks (WSN). A novel probabilistic is used to generate a new candidate of competition for simulation optimization operations. The actual population of tentative solutions does not employ, but a unique representative probabilistic of them accumulate over generations. Evaluating this proposed method, we firstly used six selected benchmark functions to experiment and then we applied the proposal to solve the optimization problem of localization in WSN to confirm its performance further. The testing results compared with the original version of FPA show that the proposed method produces considerable improvements of reducing variable storing memory and running time consumption. Compared with the other approaches in the literature, the localization obtained from the proposed method is more accuracy and convergence rate indicate that the proposed method provides the effective way of using a limited memory.
|Number of pages||14|
|Journal||Journal of Information Hiding and Multimedia Signal Processing|
|Publication status||Published - 2017|
- Compact flower pollination algorithm
- Optimization localization problems
- Probabilistic model
- Wireless sensor network