|Table of Contents|

[1] Yin Haohao, Ding Cui, Yan Feng, Xia Weiwei, et al. A movement-assisted software-defined sensor networkwith NFV support [J]. Journal of Southeast University (English Edition), 2018, (2): 156-165. [doi:10.3969/j.issn.1003-7985.2018.02.003]
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A movement-assisted software-defined sensor networkwith NFV support()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
Issue:
2018 2
Page:
156-165
Research Field:
Information and Communication Engineering
Publishing date:
2018-06-20

Info

Title:
A movement-assisted software-defined sensor networkwith NFV support
Author(s):
Yin Haohao Ding Cui Yan Feng Xia Weiwei Shen Lianfeng
National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
Keywords:
software-defined sensor network network function virtualization movement-assisted topology control
PACS:
TN915
DOI:
10.3969/j.issn.1003-7985.2018.02.003
Abstract:
A flexible and controllable movement-assisted software-defined sensor network(MA-SDSN)based on the software-defined network(SDN)and network function virtualization(NFV)is proposed. First, a three-layer fundamental architecture is proposed to overcome the inherent distributed management and rigidity of the conventional wireless sensor networks. Furthermore, the platform for research and development of MA-SDSN is established, and the dumb node(DN), the software-defined node(SN)and the movement-assisted node(MN)are designed and implemented. Then, the southbound application programming interface(API)is designed to provide a series of frames for communication between controllers and sensor nodes. The northbound API is developed and demonstrated overall and in detail. The functions of the controller are presented including topology discovery, dynamic networking, packet processing, mobility management and virtualization. Followed by the MA-SDSN network model, a Markov chain-based movement-assisted weighted relocation(MMWR)topology control algorithm is proposed to redeploy the MNs based on the node status and weight. Simulation results and analysis indicate that the proposed algorithm based on the MA-SDSN extends network lifetime with a lower average power consumption.

References:

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Memo

Memo:
Biographies: Yin Haohao(1991—), male, graduate; Shen Lianfeng(corresponding author), male, professor, lfshen@seu.edu.cn.
Foundation item: The National Natural Science Foundations of China(No.61471164, 61601122).
Citation: Yin Haohao, Ding Cui, Yan Feng, et al.A movement-assisted software-defined sensor network with NFV support[J].Journal of Southeast University(English Edition), 2018, 34(2):156-165.DOI:10.3969/j.issn.1003-7985.2018.02.003.
Last Update: 2018-06-20