{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:49:39Z","timestamp":1760150979386,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T00:00:00Z","timestamp":1643587200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The COVID-19 pandemic has affected the world socially and economically changing behaviors towards medical facilities, public gatherings, workplaces, and education. Educational institutes have been shutdown sporadically across the globe forcing teachers and students to adopt distance learning techniques. Due to the closure of educational institutes, work and learn from home methods have burdened the network resources and considerably decreased a viewer\u2019s Quality of Experience (QoE). The situation calls for innovative techniques to handle the surging load of video traffic on cellular networks. In the scenario of distance learning, there is ample opportunity to realize multi-cast delivery instead of a conventional unicast. However, the existing 5G architecture does not support service-less multi-cast. In this article, we advance the case of Virtual Network Function (VNF) based service-less architecture for video multicast. Multicasting a video session for distance learning significantly lowers the burden on core and Radio Access Networks (RAN) as demonstrated by evaluation over a real-world dataset. We debate the role of Edge Intelligence (EI) for enabling multicast and edge caching for distance learning to complement the performance of the proposed VNF architecture. EI offers the determination of users that are part of a multicast session based on location, session, and cell information. Moreover, user preferences and network\u2019s contextual information can differentiate between live and cached access patterns optimizing edge caching decisions. While exploring the opportunities of EI-enabled distance learning, we demonstrate a significant reduction in network operator resource utilization and an increase in user QoE for VNF based multicast transmission.<\/jats:p>","DOI":"10.3390\/s22031092","type":"journal-article","created":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T08:20:29Z","timestamp":1643617229000},"page":"1092","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Addressing Challenges of Distance Learning in the Pandemic with Edge Intelligence Enabled Multicast and Caching Solution"],"prefix":"10.3390","volume":"22","author":[{"given":"Kashif","family":"Bilal","sequence":"first","affiliation":[{"name":"Department of Computer Science, Abbottabad Campus, COMSATS University Islamabad, Abbottabad 22060, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0726-5311","authenticated-orcid":false,"given":"Junaid","family":"Shuja","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Abbottabad Campus, COMSATS University Islamabad, Abbottabad 22060, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7565-5253","authenticated-orcid":false,"given":"Aiman","family":"Erbad","sequence":"additional","affiliation":[{"name":"College of Science and Engineering, Hamad Bin Khalifa University, Doha 5825, Qatar"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4349-144X","authenticated-orcid":false,"given":"Waleed","family":"Alasmary","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, College of Computer and Information Systems, Umm Al-Qura University, Makkah 21955, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5560-1116","authenticated-orcid":false,"given":"Eisa","family":"Alanazi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Umm Al-Qura University, Makkah 21955, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdullah","family":"Alourani","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information, College of Science in Zulfi, Majmaah University, Al-Majmaah 11952, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1296","DOI":"10.1007\/s10489-020-01862-6","article-title":"Covid-19 open source data sets: A comprehensive survey","volume":"51","author":"Shuja","year":"2021","journal-title":"Appl. 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