Personality-Aware VNF Deployment for Profit Maximization

Ruiming Yang, Kun Cao, Peijin Cong, Junlong Zhou, Mingsong Chen, Tongquan Wei

Abstract: Virtual Network Function (VNF) providers aim to maximize their profits while satisfying diverse users' requirements. However, existing research does not take user personality into account when optimizing the profit of VNF providers, where user personality has a great influence on the VNF providers' profit. In this paper, we investigate personality-aware VNF deployment to maximize the VNF provider's profit. First, we model personalized service chain requests to capture the different requirements of users with different personalities for service requests. We further propose a user satisfaction prediction model according to questionnaires to obtain the attribute values of the above personalized service chain request. Subsequently, we propose a genetic algorithm based personality-aware VNF deployment scheme to maximize the VNF provider's profit while considering diverse personalities of individual users. Simulation results show that our proposed approach can increase the profit of the VNF provider by 9.19% and the request acceptance rate by 20.70%, respectively.