{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T14:19:35Z","timestamp":1761401975489,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2018,9,21]],"date-time":"2018-09-21T00:00:00Z","timestamp":1537488000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Caching close to users in a radio access network (RAN) has been identified as a promising method to reduce a backhaul traffic load and minimize latency in 5G and beyond. In this paper, we investigate a novel community detection inspired by a proactive caching scheme for device-to-device (D2D) enabled networks. The proposed scheme builds on the idea that content generated\/accessed by influential users is more probable to become popular and thus can be exploited for pro-caching. We use a Clustering Coefficient based Genetic Algorithm (CC-GA) for community detection to discover a group of cellular users present in close vicinity. We then use an Eigenvector Centrality measure to identify the influential users with respect to the community structure, and the content associated to it is then used for pro-active caching using D2D communications. The numerical results show that, compared to reactive caching, where historically popular content is cached, depending on cache size, load and number of requests, up to 30% more users can be satisfied using a proposed scheme while achieving significant reduction in backhaul traffic load.<\/jats:p>","DOI":"10.3390\/fi10100093","type":"journal-article","created":{"date-parts":[[2018,9,21]],"date-time":"2018-09-21T11:00:25Z","timestamp":1537527625000},"page":"93","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Proactive Caching at the Edge Leveraging Influential User Detection in Cellular D2D Networks"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6715-0068","authenticated-orcid":false,"given":"Anwar","family":"Said","sequence":"first","affiliation":[{"name":"Department of Computer Science and Electrical Engineering, Information Technology University (ITU), Lahore 54000, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4425-9810","authenticated-orcid":false,"given":"Syed Waqas Haider","family":"Shah","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Electrical Engineering, Information Technology University (ITU), Lahore 54000, Pakistan"}]},{"given":"Hasan","family":"Farooq","sequence":"additional","affiliation":[{"name":"BSON Lab, ECE, University of Oklahoma, Norman, OK 73019, USA"}]},{"given":"Adnan Noor","family":"Mian","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Electrical Engineering, Information Technology University (ITU), Lahore 54000, Pakistan"}]},{"given":"Ali","family":"Imran","sequence":"additional","affiliation":[{"name":"BSON Lab, ECE, University of Oklahoma, Norman, OK 73019, USA"}]},{"given":"Jon","family":"Crowcroft","sequence":"additional","affiliation":[{"name":"Computer Lab, University of Cambridge, Cambridge CB2 1TN, UK"}]}],"member":"1968","published-online":{"date-parts":[[2018,9,21]]},"reference":[{"key":"ref_1","unstructured":"OBILE, W. 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