TY - GEN
T1 - Personality-aware vnf deployment for profit maximization
AU - Yang, Ruiming
AU - Cao, Kun
AU - Cong, Peijin
AU - Zhou, Junlong
AU - Chen, Mingsong
AU - Wei, Tongquan
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - 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.
AB - 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.
KW - Deployment
KW - Genetic algorithm
KW - Network function virtualization
KW - Personality
KW - Profit
UR - https://www.scopus.com/pages/publications/85085529441
U2 - 10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00062
DO - 10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00062
M3 - 会议稿件
AN - SCOPUS:85085529441
T3 - Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019
SP - 380
EP - 387
BT - Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE International Conference on Parallel and Distributed Processing with Applications, 9th IEEE International Conference on Big Data and Cloud Computing, 9th IEEE International Conference on Sustainable Computing and Communications, 12th IEEE International Conference on Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom 2019
Y2 - 16 December 2019 through 18 December 2019
ER -
