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Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2026,3,31]]},"abstract":"\n Recent advances in omnidirectional cameras and AR\/VR headsets have spurred the adoption of 360\n \n \\(^{\\circ}\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n videos, which are widely believed to be the future of online video streaming. 360\n \n \\(^{\\circ}\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n videos allow users to wear a head-mounted display (HMD) and experience the video as if they are physically present in the scene. Streaming high-quality 360\n \n \\(^{\\circ}\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n videos at scale is an unsolved problem that is more challenging than traditional (2D) video delivery. The data rate required to stream 360\n \n \\(^{\\circ}\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n videos is an order of magnitude more than traditional videos. Further, the penalty for rebuffering events where the video freezes or displays a blank screen is more severe as it may cause cybersickness. We propose an online adaptive bitrate (ABR) algorithm for 360\n \n \\(^{\\circ}\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n videos called\n BOLA360<\/jats:monospace>\n that runs inside the client\u2019s video player and orchestrates the download of video tiles from the server to maximize the quality-of-experience (QoE) of the user.\n BOLA360<\/jats:monospace>\n conserves bandwidth by downloading only those video tiles that are likely to fall within the field-of-view (FOV) of the user. In addition,\n BOLA360<\/jats:monospace>\n continually adapts the bitrate of the downloaded video tiles so as to enable a smooth playback without rebuffering. We prove that\n BOLA360<\/jats:monospace>\n is near-optimal with respect to an optimal offline algorithm that maximizes QoE. Further, we evaluate\n BOLA360<\/jats:monospace>\n on a wide range of network and user head movement profiles and show that it provides\n \n \\(6\\%\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n to\n \n \\(110\\%\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n improvements to the QoE of state-of-the-art algorithms. While ABR algorithms for traditional (2D) videos have been well-studied over the last decade, our work is the first ABR algorithm for 360\n \n \\(^{\\circ}\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n videos with\n both<\/jats:italic>\n theoretical and empirical guarantees on its performance.\n <\/jats:p>","DOI":"10.1145\/3785137","type":"journal-article","created":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T18:28:28Z","timestamp":1765823308000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["BOLA360<\/tt>\n : Near-optimal View and Bitrate Adaptation for 360-degree Video Streaming"],"prefix":"10.1145","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9008-4400","authenticated-orcid":false,"given":"Ali","family":"Zeynali","sequence":"first","affiliation":[{"name":"University of Massachusetts Amherst, Amherst, Massachusetts, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8931-859X","authenticated-orcid":false,"given":"Mahsa","family":"Sahebdel","sequence":"additional","affiliation":[{"name":"University of Massachusetts Amherst, Amherst, Massachusetts, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9278-2254","authenticated-orcid":false,"given":"Mohammad H.","family":"Hajiesmaili","sequence":"additional","affiliation":[{"name":"University of Massachusetts Amherst, Amherst, Massachusetts, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0558-6875","authenticated-orcid":false,"given":"Ramesh K.","family":"Sitaraman","sequence":"additional","affiliation":[{"name":"University of Massachusetts Amherst, Amherst, Massachusetts, USA and Akamai Technologies, Amherst, Massachusetts, USA"}]}],"member":"320","published-online":{"date-parts":[[2026,2,27]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"Akamai. 2017. 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