An Optimization Algorithm Based on GA for Multicast Network

Abstract

In the traditional wireless sensor network (WSN), the multicast router uses the store-and-forward mode to transmit data, which limits the throughput of the wireless sensor network. In 2000, the network coding is proposed by Rudolf Ahlswede, Li Shuoyan et al. Therefore, the wireless sensor network can reach the theoretical maximum throughput, save energy and improve the security of data transmission. However, network coding operations involve complex data operations. Excessive coding consumes a large amount of computer CPU and memory resources. Therefore, how to reduce the number of network coding to reduce the computational cost is a prerequisite academic problem on the premise of reaching rate of multicast. An extremely important academic research issue is called Network Coding Resource Minimization (NCRM). Aiming at the NCRM problem in static wireless sensor networks, this paper proposes an improved path-relinking optimization algorithm based on genetic algorithm, which can locate the initialization parameters to the feasible solution region and adopt local search method to search optimal solution. The strategy further enhances the search ability of chromosomes in optimization algorithm. Experiments show that this algorithm spends less coding times and calculation time than the traditional simple genetic algorithm when achieving the same network throughput.