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    Cloud-based Video Monitoring Framework: An Approach based on Software-Defined Networking for Addressing Scalability Problems

    Sandar, Nay Myo; Chaisiri, Sivadon; Yongchareon, Sira; Liesaputra, Veronica

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    Date
    2014-10-12
    Citation:
    Sandar, 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.), LNCS
    Permanent link to Research Bank record:
    https://hdl.handle.net/10652/2984
    Abstract
    Abstract. 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.
    Keywords:
    cloud-based video-monitoring, cloud computing, video monitoring, video surveillance, software-defined networking
    ANZSRC Field of Research:
    160206 Private Policing and Security Services, 080503 Networking and Communications
    Copyright Holder:
    Cham Springer International Publishing
    Copyright Notice:
    An 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 www.springerlink.com, 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 www.springerlink.com”
    Available Online at:
    http://link.springer.com/chapter/10.1007/978-3-319-20370-6_14
    Rights:
    This digital work is protected by copyright. It may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use: Any use you make of these documents or images must be for research or private study purposes only, and you may not make them available to any other person. You will recognise the author's and publishers rights and give due acknowledgement where appropriate.
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    • Computing Conference Papers [147]

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