Relaying strategy for peer-to-peer content distribution based on genetic algorithm

Abstract This article proposes a cooperative relaying strategy to efficiently utilize the relaying resources of Internet service providers (ISPs), speedup distribution and save server bandwidth costs. ISPs cooperatively relay for each other, and peers assist in distributing and fetching the content as near as possible. Base on the fluid model, a constrained model is derived to get optimized global distribution performance in the channel-based system with limited relaying resources. The multi-objectives of the model are minimizing the average distribution time and the distribution time of the slowest channel. Genetic algorithm (GA) is designed to solve the optimization problem. The relaying strategy based on GA can be run periodically to update the allocation policy of ISPs. The distribution performance of the relaying strategy is analyzed in the experiments and results show that GA can provide proper solutions for various network topologies.