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Appl."],"published-print":{"date-parts":[[2019,4,30]]},"abstract":"<jats:p>\n            The dramatic growth of HTTP adaptive streaming (HAS) traffic represents a practical challenge for service providers in satisfying the demand from their customers. Achieving this in a network where multiple players share the network capacity has so far proved hard because of the bandwidth competition among the HAS players. This competition is exacerbated by the\n            <jats:italic>bandwidth overestimation<\/jats:italic>\n            that is introduced due to the\n            <jats:italic>isolated<\/jats:italic>\n            and\n            <jats:italic>selfish<\/jats:italic>\n            behavior of the HAS players. Each player strives individually to select the maximum bitrate without considering the co-existing players or network resource dynamics. As a result, the HAS players suffer from video quality instability, quality unfairness, and network underutilization or oversubscription, and the players observe a poor quality of experience (QoE). To address this issue, we propose a fully distributed game theory and consensus-based collaborative adaptive bitrate solution for shared network environments, termed Game Theory and consensus-based Approach for Cooperative HAS delivery systems (GTAC). Our solution consists of two-stage games that run in parallel during a streaming session. We extensively evaluate GTAC on a broad set of trace-driven and real-world experiments. Results show that GTAC enhances the viewer QoE by up to 22%, presentation quality stability by up to 24%, fairness by at least 31%, and network utilization by 28% compared to the well-known schemes.\n          <\/jats:p>","DOI":"10.1145\/3336496","type":"journal-article","created":{"date-parts":[[2019,7,19]],"date-time":"2019-07-19T13:17:14Z","timestamp":1563542234000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Game of Streaming Players"],"prefix":"10.1145","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5382-6530","authenticated-orcid":false,"given":"Abdelhak","family":"Bentaleb","sequence":"first","affiliation":[{"name":"School of Computing, National University of Singapore, Singapore"}]},{"given":"Ali C.","family":"Begen","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Ozyegin University 8 Networked Media, Istanbul, Turkey"}]},{"given":"Saad","family":"Harous","sequence":"additional","affiliation":[{"name":"College of Information Technology, UAE University, Istanbul, UAE"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7410-2590","authenticated-orcid":false,"given":"Roger","family":"Zimmermann","sequence":"additional","affiliation":[{"name":"School of Computing, National University of Singapore, Singapore"}]}],"member":"320","published-online":{"date-parts":[[2019,7,19]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","unstructured":"Saamer Akhshabi Lakshmi Anantakrishnan Ali C. 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