A compact Articial bee colony optimization for topology control scheme in wireless sensor networks

In this paper, a compact Articial Bee Colony optimization method (cABC) for applying to the topology optimization of wireless sensor networks (WSNs) is presented. The purpose of compact algorithms is to address to the computational requirements in the limited resources of hardware devices such as memory size or low price. A probabilistic representation random of the collection behavior of social bee colony is inspired to employ for this proposed algorithm. The real population is replaced with the probability vector updated based on single competition. These lead to a modest memory usage when the entire algorithm is applied. Four selected test functions are used to evaluate the accuracy, computational time and memory saving of the proposed method. The experimental results show that the proposed cABC method is not only as accurate as the existing original Articial Bee Colony optimization but also requires less calculative time than the original method and uses a modest memory with only six agents needed for storing space. In addition, compared with the genetic algorithm (GA) method and the particle swarm optimization (PSO) method, the proposed cABC method can provide the highest robust structure and lowest contention topology schemes.