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Computational Resource Management for Video Coding in Mobile Environments

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datacite.subject.fosCiências Médicas::Ciências da Saúde
datacite.subject.fosCiências Naturais::Matemáticas
datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg10:Reduzir as Desigualdades
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorCorrea, Guilherme
dc.contributor.authorAssunção, Pedro
dc.contributor.authorAgostini, Luciano
dc.contributor.authorCruz, Luis A. da Silva
dc.date.accessioned2025-07-01T15:18:20Z
dc.date.available2025-07-01T15:18:20Z
dc.date.issued2014
dc.descriptionEISBN - 9783319067049
dc.descriptionModeling and Optimization in Science and Technologies, Volume 3, Pages 515 - 549
dc.description.abstractThe increase of computational resources in mobile devices and the availability of reliable communication infrastructures provide support for acquisition, display, coding/decoding and transmission of high-resolution video in a broad set of equipment such as tablets and smartphones. Nevertheless, real-time video encoding and decoding is still a challenge in such computing environments, especially when considering the amount of computational resources required by state-of-the-art video coding standards. Moreover, battery technologies did not evolve as much as desired, which makes power consumption minimization an important issue for the mobile devices industry and users. Therefore, in current mobile systems, the available computational resources along with battery-life are responsible for imposing significant limitations on mobile real-time multimedia communications. This chapter presents an overview of the state-of-the-art research on management of computational resources for video encoding systems in mobile communications equipment. A review on computational complexity analysis of both H.264/AVC and HEVC video coding standards is presented, followed by a description of current methods for modelling, reducing and controlling the expenditure of computational resources on these video codecs. Finally, future trends on computational complexity management for video codecs implemented on power-constrained devices are lined out.eng
dc.description.sponsorshipThe authors acknowledge financial support from the National Council for Scientific and Technological Development (Brazil) and the Instituto de Telecomunicações (Portugal).
dc.identifier.citationCorrea, G., Assuncao, P., Agostini, L., da Silva Cruz, L.A. (2014). Computational Resource Management for Video Coding in Mobile Environments. In: Resource Management in Mobile Computing Environments. Modeling and Optimization in Science and Technologies, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-319-06704-9_24.
dc.identifier.doi10.1007/978-3-319-06704-9_24
dc.identifier.eissn2196-7334
dc.identifier.isbn9783319067032
dc.identifier.isbn9783319067049
dc.identifier.issn2196-7326
dc.identifier.urihttp://hdl.handle.net/10400.8/13491
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-3-319-06704-9_24
dc.relation.ispartofModeling and Optimization in Science and Technologies
dc.relation.ispartofResource Management in Mobile Computing Environments
dc.rights.uriN/A
dc.subjectmobile devices
dc.subjectvideo coding
dc.subjectcomputational resources
dc.titleComputational Resource Management for Video Coding in Mobile Environmentseng
dc.typebook part
dspace.entity.typePublication
oaire.citation.endPage44
oaire.citation.startPage1
oaire.citation.titleModeling and Optimization in Science and Technologies
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa
person.familyNameAssunção
person.givenNamePedro
person.identifier.ciencia-id6811-3984-C17B
person.identifier.orcid0000-0001-9539-8311
person.identifier.ridA-4827-2017
person.identifier.scopus-author-id6701838347
relation.isAuthorOfPublication25649bb9-f135-48e8-8d0f-3706b86701d3
relation.isAuthorOfPublication.latestForDiscovery25649bb9-f135-48e8-8d0f-3706b86701d3

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The increase of computational resources in mobile devices and the availability of reliable communication infrastructures provide support for acquisition, display, coding/decoding and transmission of high-resolution video in a broad set of equipment such as tablets and smartphones. Nevertheless, real-time video encoding and decoding is still a challenge in such computing environments, especially when considering the amount of computational resources required by state-of-the-art video coding standards. Moreover, battery technologies did not evolve as much as desired, which makes power consumption minimization an important issue for the mobile devices industry and users. Therefore, in current mobile systems, the available computational resources along with battery-life are responsible for imposing significant limitations on mobile real-time multimedia communications. This chapter presents an overview of the state-of-the-art research on management of computational resources for video encoding systems in mobile communications equipment. A review on computational complexity analysis of both H.264/AVC and HEVC video coding standards is presented, followed by a description of current methods for modelling, reducing and controlling the expenditure of computational resources on these video codecs. Finally, future trends on computational complexity management for video codecs implemented on power-constrained devices are lined out.
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