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Intell. Syst. Technol."],"published-print":{"date-parts":[[2022,10,31]]},"abstract":"<jats:p>Through the collaboration of cloud and edge, cloud-edge computing allows the edge that approximates end-users undertakes those non-computationally intensive service processing of the cloud, reducing the communication overhead and satisfying the low latency requirement of Internet of Vehicle (IoV). With cloud-edge computing, the computing tasks in IoV is able to be delivered to the edge servers (ESs) instead of the cloud and rely on the deployed services of ESs for a series of processing. Due to the storage and computing resource limits of ESs, how to dynamically deploy partial services to the edge is still a puzzle. Moreover, the decision of service deployment often requires the transmission of local service requests from ESs to the cloud, which increases the risk of privacy leakage. In this article, a method for privacy-aware IoV service deployment with federated learning in cloud-edge computing, named PSDF, is proposed. Technically, federated learning secures the distributed training of deployment decision network on each ES by the exchange and aggregation of model weights, avoiding the original data transmission. Meanwhile, homomorphic encryption is adopted for the uploaded weights before the model aggregation on the cloud. Besides, a service deployment scheme based on deep deterministic policy gradient is proposed. Eventually, the performance of PSDF is evaluated by massive experiments.<\/jats:p>","DOI":"10.1145\/3501810","type":"journal-article","created":{"date-parts":[[2022,8,17]],"date-time":"2022-08-17T12:06:57Z","timestamp":1660738017000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":56,"title":["PSDF: Privacy-aware IoV Service Deployment with Federated Learning in Cloud-Edge Computing"],"prefix":"10.1145","volume":"13","author":[{"given":"Xiaolong","family":"Xu","sequence":"first","affiliation":[{"name":"School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China, Weifang Key Laboratory of Blockchain on Agricultural Vegetables, WeiFang University of Science and Technology, Shouguang, China, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science and Technology, Nanjing, China, and Provincial Key Laboratory for Computer Information Processing Technology, Soochow..."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wentao","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yulan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Weifang Key Laboratory of Blockchain on Agricultural Vegetables, WeiFang University of Science and Technology, Shouguang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuyun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Computing, Macquarie University, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wanchun","family":"Dou","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lianyong","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Qufu Normal University, Qufu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Md Zakirul Alam","family":"Bhuiyan","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Fordham University, New York, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,10,13]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/3214303"},{"key":"e_1_3_1_3_2","article-title":"Deep reinforcement learning from human preferences","volume":"30","author":"Christiano Paul F.","year":"2017","unstructured":"Paul F. 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