Advances in Software-Defined Technologies for Underwater Acoustic Sensor Networks: A Survey

Wang, Jianping; Kong, Dechuan; Chen, Wei; Zhang, Shujing

doi:10.1155/2019/3470390

Cited by 19 publications

(14 citation statements)

References 116 publications

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“…Therefore, an UWSN framework supporting heterogeneous communication of various hardware is needed. Most of the existing underwater multi-mode communication frameworks are based on the adaptation layer, and need a special routing algorithm to support, but cannot achieve the versatility, re-programmability and transparency of multi-mode communication [7][8][9][10][11][12][13][14]. The routing and forwarding of traditional UWSN depends on the node address.…”

Section: Difficult Communicationmentioning

confidence: 99%

MMNET: A Multi-Modal Network Architecture for Underwater Networking

Wang

Song

et al. 2020

Electronics

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At present, the key to underwater sensor network (UWSN) research is to provide personalized network support for many underwater applications. In order to achieve this goal, people need a general UWSN. Most of the current UWSN architecture is based on the traditional network, which are limited to a single hardware platform and software platform. Facing the current numerous underwater applications and heterogeneous networks, the UWSN is unable to provide personalized network services according to different application requirements. In this paper, we propose a heterogeneous network framework called MMNET (multimodal network) based on the idea of multimodality, aiming to achieve the compatibility of heterogeneous networks and the scalability of the new architecture. In addition, in the face of the complexity of heterogeneous networks and the personalized needs of network applications, the resource allocation is expressed as a personalized recommendation problem. The distributed personalized recommendation algorithm is used to configure personalized network resources for applications. Each node only needs to solve its own problems, instead of exchanging channel state information by using a distributed algorithm, so the computational complexity can be greatly reduced and signaling is overhead. Finally, we give a special example to prove that our network framework provides a good application.

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Section: Difficult Communicationmentioning

confidence: 99%

MMNET: A Multi-Modal Network Architecture for Underwater Networking

Wang

Song

et al. 2020

Electronics

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“…The experiment revealed that it had advantages in the end-to-end delay, the surviving time, and coverage. J. Wang et al [30] made a comprehensive investigation of SDN and analyzed the progress of softwaredefined underwater networks.…”

Section: B Advances In Software-defined Uans 1) Advancement In the Amentioning

confidence: 99%

SM-UAN: A Software-Defined Underwater Acoustic Network of Multi-Controllers for Inland Waterway Systems

et al. 2020

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Underwater acoustic network (UAN) is a lightweight system used in inland waterway systems. Software-defined networking (SDN) is a promising approach to improve the supervision abilities and integration services. This paper introduces SM-UAN, an SDN-based UAN with multi-controllers. Firstly, a hierarchical framework of SM-UAN is offered. Secondly, a multi-flow table structure and a multi-flow processing method is built. Followed by, a distributed deployment model of controllers and a load balancing mechanism are established. Finally, we construct an experimental scenario on Mininet with WOSS-NS3. The simulation demonstrates that the compression ratio is promoted to 24.1%, the compression ratio 29.4%, the packet forwarding rate 14.7% and the processing delay 31.2%, when comparing SM-UAN with the item-by-item matching (IM) system. For the load balancing mechanism, it shows that the maximum load for a master controller is balanced to 0.55, while the minimum load for a slave controller 0.46, which proves that a fair load distribution achieves. In addition, SM-UAN is compared with the traditional single-sink-based UAN (TS-UAN), the traditional multi-sink-based UAN (TM-UAN), and the SDN-based UAN with a single controller (SS-UAN). The results reveal that the survival time of SM-UAN is extended to 32.7%, 24.9%, and 21.6%, respectively. Also, the bit error rate (BER) of that is less than 10-4. In conclusion, advantages of SM-UAN have been highlighted, which provides theoretical support for inland waterway systems.

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“…Most of these algorithms implement based on the residual energy and other constraints, and adopt the transmission of multi-hop mode. Nevertheless, none is SDN-driven type [80], [81]. To the best of our knowledge, it is the first paper to introduce the clustering of UASNs based on SDN.…”

Section: Progress Of Clustering Technologiesmentioning

confidence: 99%

A Software-Defined Clustering Mechanism for Underwater Acoustic Sensor Networks

Wang

Gao

et al. 2019

IEEE Access

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Underwater acoustic sensor networks (UASNs) are important technical means to explore the ocean realm. Clustering is a crucial strategy which determines the performance and the lifetime of UASNs significantly. As a technological innovation, software defined networking (SDN) separates the data plane from the control plane to build a programmable network infrastructure. This paper presents a clustering mechanism based on SDN. Firstly, we introduce the architecture of software-defined UASN named SD-UASN. Secondly, we investigate hardware models of the underwater node and the surface controller. Thirdly, we define the communication procedure of SD-UASN, and implement the clustering mechanism. Finally, we perform simulations to verify the effectiveness of the proposed mechanism. The results reveal that a tradeoff of multiple constraints is achieved, and the performance of the clustering mechanism can be enhanced greatly. This work provides essential theoretical and technical support for software-defined UASNs.INDEX TERMS Underwater acoustic sensor networks (UASNs), clustering algorithm, software defined networking (SDN), software-defined UASN (SD-UASN), OpenFlow.

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Advances in Software-Defined Technologies for Underwater Acoustic Sensor Networks: A Survey

Cited by 19 publications

References 116 publications

MMNET: A Multi-Modal Network Architecture for Underwater Networking

MMNET: A Multi-Modal Network Architecture for Underwater Networking

SM-UAN: A Software-Defined Underwater Acoustic Network of Multi-Controllers for Inland Waterway Systems

A Software-Defined Clustering Mechanism for Underwater Acoustic Sensor Networks

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