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Most existing CDN-based works upload the content generated by mobile users to the cloud data center firstly. Then, the cloud data center delivers the content to the proxy server. Finally, the mobile users request the required content from the proxy server. However, uploading all the collected content to the cloud data center increases the pressure on the core network. In addition, it also wastes a lot of bandwidth resources because most of the content does not have to be uploaded. To make up for the shortcomings of existing CDN-based works, this article proposes an edge content delivery and update (ECDU) framework based on mobile edge computing architecture. In the ECDU framework, we deploy a number of content servers to store raw content collected from mobile users, and cache pools to store content that frequently requested at the edge of the network. Thus, it is not necessary to upload all content collected by mobile users to the cloud data center, thereby alleviating the pressure of the core network. Based on content popularity and cache pool ranking, we also propose edge content delivery (ECD) and edge content update (ECU) schemes. The ECD scheme is to deliver content from cloud data center to cache pool, and the ECU scheme is to mitigate the content to appropriate cache pools in terms of its request frequency and cache pool ranking. Finally, a representative case study is provided and several open research issues are discussed.<\/jats:p>","DOI":"10.1186\/s13638-019-1590-2","type":"journal-article","created":{"date-parts":[[2019,12,13]],"date-time":"2019-12-13T09:04:20Z","timestamp":1576227860000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["ECDU: an edge content delivery and update framework in Mobile edge computing"],"prefix":"10.1186","volume":"2019","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8362-8407","authenticated-orcid":false,"given":"Chuntao","family":"Ding","sequence":"first","affiliation":[]},{"given":"Ao","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Jie","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Ying","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Shangguang","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,12,12]]},"reference":[{"key":"1590_CR1","unstructured":"Cisco, Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update 2017-2022. https:\/\/learningnetwork.cisco.com\/community\/learning_center\/white-papers."},{"key":"1590_CR2","unstructured":"A. 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