Robust Software-Defined Scheme for Image Sensor Network 


Vol. 41,  No. 2, pp. 215-221, Feb.  2016


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  Abstract

Data failure in wireless communications considerably affects the reconstruction quality of transmitted data. Traditionally, fascinating trials have been conducted to overcome the data failure intensifying reliable reconstruction of a media. But, none of these efforts neither effective, computationally inexpensive nor simply configurable to reduce the problems of transmitting media or images. In practice, it is necessary to maintain the quality of transmitted image without sacrificing any data, content, or information. So, to deal with dynamic events such as sensor node participation and departure, during transmission, an efficient scheme is important. For this reason, a new robust scheme has been presented in this paper to minimize the limitation of traditional wireless networking. This scheme uses Software-Defined Image Sensor Network (SD-ISN) to ensure scalability and dependability of the sensor network of handling data losses. Finally, a comparison of our proposed SD-ISN with conventional wireless networking has been presented in simulation to test the robustness and effectiveness of our proposed SD-ISN approach.

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  Cite this article

[IEEE Style]

A. Islam, M. A. Hossain, N. Le, C. H. Hong, Y. M. Jang, "Robust Software-Defined Scheme for Image Sensor Network," The Journal of Korean Institute of Communications and Information Sciences, vol. 41, no. 2, pp. 215-221, 2016. DOI: .

[ACM Style]

Amirul Islam, Mohammad Arif Hossain, Nam-Tuan Le, Chang Hyun Hong, and Yeong Min Jang. 2016. Robust Software-Defined Scheme for Image Sensor Network. The Journal of Korean Institute of Communications and Information Sciences, 41, 2, (2016), 215-221. DOI: .

[KICS Style]

Amirul Islam, Mohammad Arif Hossain, Nam-Tuan Le, Chang Hyun Hong, Yeong Min Jang, "Robust Software-Defined Scheme for Image Sensor Network," The Journal of Korean Institute of Communications and Information Sciences, vol. 41, no. 2, pp. 215-221, 2. 2016.