• norsk
    • English
  • norsk 
    • norsk
    • English
  • Logg inn
Vis innførsel 
  •   Hjem
  • Øvrige samlinger
  • Publikasjoner fra CRIStin - NTNU
  • Vis innførsel
  •   Hjem
  • Øvrige samlinger
  • Publikasjoner fra CRIStin - NTNU
  • Vis innførsel
JavaScript is disabled for your browser. Some features of this site may not work without it.

Edge Computing-Enabled Resource Provisioning for Video Surveillance in Internet of Vehicles

Xu, Xiaolong; Wu, Qi; He, Chengxun; Wan, Shaohua; Qi, Lianyong; Wang, Hao
Journal article, Peer reviewed
Accepted version
Thumbnail
Åpne
Xu (398.4Kb)
Permanent lenke
http://hdl.handle.net/11250/2638794
Utgivelsesdato
2019
Metadata
Vis full innførsel
Samlinger
  • Institutt for datateknologi og informatikk [3771]
  • Publikasjoner fra CRIStin - NTNU [19694]
Originalversjon
Communications in Computer and Information Science. 2019, 1122 128-140.   https://doi.org/10.1007/978-981-15-1301-5_11
Sammendrag
As a novel technology, Internet of Vehicles (IoV) is employed to gather real-time traffic information for drivers from sensors and video surveillance devices with image processing, circumstances analysis and events recognition. In spite of multiple advantages of IoV, preprocessing the huge data may demand abundant computation resources for video surveillance devices. Migrating tasks to remote servers for performing is efficient to solve this problem, but it needs high network bandwidth, which causes traffic congestion and delay. Edge computing has capability to enhance processing performance, which complements video surveillance device and addresses numerous shortcomings. Nevertheless, edge computing for video surveillance remains a challenge to achieve low-latency and load balance through limited amount of edge servers. To handle this challenge, an Edge computing-enabled Resource Provisioning Method (ERPM) for Video Surveillance in IoV is proposed in this paper. Technically, SPEA2 (improving the Strength Pare to Evolutionary Algorithm) is picked to solve the multi-objective optimization problem aiming at minimizing the time consumption and optimizing load balance. Finally, experimental simulation for Evolution algorithm demonstrate the appropriation and efficiency of ERPM.
Utgiver
Springer Verlag
Tidsskrift
Communications in Computer and Information Science

Kontakt oss | Gi tilbakemelding

Personvernerklæring
DSpace software copyright © 2002-2019  DuraSpace

Levert av  Unit
 

 

Bla i

Hele arkivetDelarkiv og samlingerUtgivelsesdatoForfattereTitlerEmneordDokumenttyperTidsskrifterDenne samlingenUtgivelsesdatoForfattereTitlerEmneordDokumenttyperTidsskrifter

Min side

Logg inn

Statistikk

Besøksstatistikk

Kontakt oss | Gi tilbakemelding

Personvernerklæring
DSpace software copyright © 2002-2019  DuraSpace

Levert av  Unit