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Sen. Netw."],"published-print":{"date-parts":[[2021,8,31]]},"abstract":"<jats:p>Internet of Vehicles (IoV) enables numerous in-vehicle applications for smart cities, driving increasing service demands for processing various contents (e.g., videos). Generally, for efficient service delivery, the contents from the service providers are processed on the edge servers (ESs), as edge computing offers vehicular applications low-latency services. However, due to the reusability of the same contents required by different distributed vehicular users, processing the copies of the same contents repeatedly in an edge server leads to a waste of resources (e.g., storage, computation, and bandwidth) in ESs. Therefore, it is a challenge to provide high-quality services while guaranteeing the resource efficiency with edge content caching. To address the challenge, an edge content caching method for smart cities with service requirement prediction, named E-Cache, is proposed. First, the future service requirements from the vehicles are predicted based on the deep spatiotemporal residual network (ST-ResNet). Then, preliminary content caching schemes are elaborated based on the predicted service requirements, which are further adjusted by a many-objective optimization aiming at minimizing the execution time and the energy consumption of the vehicular services. Eventually, experimental evaluations prove the efficiency and effectiveness of E-Cache with spatiotemporal traffic trajectory big data.<\/jats:p>","DOI":"10.1145\/3447032","type":"journal-article","created":{"date-parts":[[2021,6,21]],"date-time":"2021-06-21T20:19:31Z","timestamp":1624306771000},"page":"1-33","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":99,"title":["Edge Content Caching with Deep Spatiotemporal Residual Network for IoV in Smart City"],"prefix":"10.1145","volume":"17","author":[{"given":"Xiaolong","family":"Xu","sequence":"first","affiliation":[{"name":"School of Computer and Software, Nanjing University of Information Science and Technology, China and Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science and Technology, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zijie","family":"Fang","sequence":"additional","affiliation":[{"name":"School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"He","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, Swinburne University of Technology, Melbourne, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongxiao","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Shandong University, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lianyong","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Qufu Normal University, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wanchun","family":"Dou","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,6,21]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2016.2532458"},{"key":"e_1_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Ejaz Ahmed and Mubashir Husain Rehmani. 2017. 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