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dc.contributor.authorSandar, Nay Myo
dc.contributor.authorChaisiri, Sivadon
dc.contributor.authorYongchareon, Sira
dc.contributor.authorLiesaputra, Veronica
dc.description.abstractAbstract. Closed-circuit television (CCTV) and Internet protocol (IP) cameras have been applied to a surveillance or monitoring system, from which users can remotely monitor video streams. The system has been employed for many applications such as home surveillance, traffic monitoring, and crime prevention. Currently, cloud computing has been integrated with the video monitoring system for achieving value-added services such as video adjustment, encoding, image/video recognition, and backup services. One of the challenges in this integration is due to the size and geographical scalability problems when video streams are transferred to and retrieved from the cloud services by numerous cameras and users, respectively. Unreliable network connectivity is a major factor that causes the problems. To deal with the scalability problems, this paper proposes a framework designed for a cloud-based video monitoring (CVM) system. In particular, this framework applies two major approaches, namely stream aggregation (SA) and software-defined networking (SDN). The SA approach can reduce the network latency between cameras and cloud services. The SDN approach can achieve the adaptive routing control which improves the network performance. With the SA and SDN approaches applied by the framework, the total latency for transferring video streams can be minimized and the scalability of the CVM system can be significantly enhanced.en_NZ
dc.publisherCham Springer International Publishingen_NZ
dc.rightsAn author may self-archive an author-created version of his/her article on his/her own website and or in his/her institutional repository. He/she may also deposit this version on his/her funder’s or funder’s designated repository at the funder’s request or as a result of a legal obligation, provided it is not made publicly available until 12 months after official publication. He/ she may not use the publisher's PDF version, which is posted on, for the purpose of self-archiving or deposit. Furthermore, the author may only post his/her version provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at”en_NZ
dc.subjectcloud-based video-monitoringen_NZ
dc.subjectcloud computingen_NZ
dc.subjectvideo monitoringen_NZ
dc.subjectvideo surveillanceen_NZ
dc.subjectsoftware-defined networkingen_NZ
dc.titleCloud-based Video Monitoring Framework: An Approach based on Software-Defined Networking for Addressing Scalability Problemsen_NZ
dc.typeConference Contribution - Paper in Published Proceedingsen_NZ
dc.rights.holderCham Springer International Publishingen_NZ
dc.subject.marsden160206 Private Policing and Security Servicesen_NZ
dc.subject.marsden080503 Networking and Communicationsen_NZ
dc.identifier.bibliographicCitationSandar, N.M., Chaisiri, S., Yongchareon, S., Liesaputra, and V. (2014). Cloud-based Video Monitoring Framework: An Approach based on Software-Defined Networking for Addressing Scalability Problems. Web Information Systems Engineering – WISE 2014 Workshops(Ed.), LNCSen_NZ
unitec.institutionShinawatra University, Thailanden_NZ
unitec.institutionUnitec Institute of Technologyen_NZ
unitec.publication.titleWeb Information Systems Engineering – WISE 2014 Workshops 15th International Workshops IWCSN 2014, Org2 2014, PCS 2014, and QUAT 2014, Thessaloniki, Greece, October 12-14, 2014, Revised Selected Papersen_NZ
unitec.conference.titleWeb Information Systems Engineering – WISE 2014 Workshopsen_NZ
unitec.conference.orgWeb Information Systems Engineering – WISEen_NZ
unitec.conference.locationThessaloniki, Greeceen_NZ
dc.contributor.affiliationUnitec Institute of Technologyen_NZ
dc.contributor.affiliationShinawatra University (Thailand)en_NZ

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