Design of underwater acoustic sensor communication systems based on software-defined networks in big data

Jianping Wang, Lijuan Ma and Wei Chen

International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 7, 1550147717719672

Abstract: The application based on big data is an important development trend of underwater acoustic sensor networks. However, traditional underwater acoustic sensor networks rely on the hardware infrastructure. The flexibility and scalability cannot be satisfied greatly. Due to the low performance of underwater acoustic sensor networks, it creates significant barriers to the implementation of big data. Software-defined network is regarded as a new infrastructure of next-generation network. It offers a novel solution for designing underwater acoustic sensor networks of high performance. In this article, a software-defined network–based solution is proposed to build the architecture of underwater acoustic sensor networks in big data. The design procedures of the data plane and control plane are described in detail. In the data plane, the works include the hardware design of OpenFlow-based virtual switch and the design of the physical layer based on software-defined radio. The hierarchical clustering technology and the node addressing techniques for designing media access control layer are well introduced. In the control plane, exploiting the hardware of the controller and designing the core module of controllers are presented as well. Through the study, it is supposed to maximize the capacity of underwater acoustic sensor networks, reduce the management complexity, and provide critical technical support for the high-performance underwater acoustic sensor networks.

Keywords: Underwater acoustic sensor networks; software-defined network; data plane; control plane; software-defined radio; OpenFlow; OpenFlow-based virtual switch; big data (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:7:p:1550147717719672

DOI: 10.1177/1550147717719672

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