MMNET: A Multi-Modal Network Architecture for Underwater Networking

• Main Authors: Jun Liu, Jun Wang, Shanshan Song, Junhong Cui, Xiaoyu Wang, Benyuan Li
• Format: Article
• Language: English
• Published: MDPI AG 2020-12-01
• Series: Electronics
• Subjects: multi-modal; heterogeneous network; under-water sensor network; personalized network resource allocation
• Online Access: https://www.mdpi.com/2079-9292/9/12/2186

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.