AURP: An AUV-Aided Underwater Routing Protocol for Underwater Acoustic Sensor Networks

Yoon, Seokhoon; Azad, Abul Kalam; Oh, Hoon; Kim, Sunghwan

doi:10.3390/s120201827

Cited by 129 publications

(86 citation statements)

References 39 publications

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“…The protocol exploits link quality information to route around connectivity voids and shadow zones. Yoon et al [12] proposed an AUV-aided underwater routing protocol (AURP) to maximize the data delivery ratio and minimize the energy consumption of underwater sensor nodes. The scheme not only uses heterogeneous acoustic channels but also controls the mobility of the AUVs.…”

Section: Related Workmentioning

confidence: 99%

Cognitive Routing in Software-Defined Underwater Acoustic Networks

Ghafoor

Koo

2017

Applied Sciences

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Abstract:There are two different types of primary users (natural acoustic and artificial acoustic), and there is a long propagation delay for acoustic links in underwater cognitive acoustic networks (UCANs). Thus, the selection of a stable route is one of the key design factors for improving overall network stability, thereby reducing end-to-end delay. Software-defined networking (SDN) is a novel approach that improves network intelligence. To this end, we propose a novel SDN-based routing protocol for UCANs in order to find a stable route between source and destination. A main controller is placed in a surface buoy that is responsible for the global view of the network, whereas local controllers are placed in different autonomous underwater vehicles (AUVs) that are responsible for a localized view of the network. The AUVs have fixed trajectories, and sensor nodes within transmission range of the AUVs serve as gateways to relay the gathered information to the controllers. This is an SDN-based underwater communications scheme whereby two nodes can only communicate when they have a consensus about a common idle channel. To evaluate our proposed scheme, we perform extensive simulations and improve network performance in terms of end-to-end delay, delivery ratio, and overhead.

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Section: Related Workmentioning

confidence: 99%

Cognitive Routing in Software-Defined Underwater Acoustic Networks

Ghafoor

Koo

2017

Applied Sciences

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“…The communication scenario between ROV and underwater sensor node depends on the distance and data between them and either acoustic or radio can be used. As the transmission is to be directly relayed to ROV, the sensors which have large data and are close to ROVs can use radio links while the sensors which have small data to transmit or are far from ROV can use acoustics links [7,8].…”

Section: 4mentioning

confidence: 99%

Underwater Sensor Network Applications: A Comprehensive Survey

Felemban

Shaikh

Qureshi

et al. 2015

International Journal of Distributed Sensor Networks

312

190

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There is no escaping fact that a huge amount of unexploited resources lies underwater which covers almost 70% of the Earth. Yet, the aquatic world has mainly been unaffected by the recent advances in the area of wireless sensor networks (WSNs) and their pervasive penetration in modern day research and industrial development. The current pace of research in the area of underwater sensor networks (UWSNs) is slow due to the difficulties arising in transferring the state-of-the-art WSNs to their underwater equivalent. Maximum underwater deployments rely on acoustics for enabling communication combined with special sensors having the capacity to take on harsh environment of the oceans. However, sensing and subsequent transmission tend to vary as per different subsea environments; for example, deep sea exploration requires altogether a different approach for communication as compared to shallow water communication. This paper particularly focuses on comprehensively gathering most recent developments in UWSN applications and their deployments. We have classified the underwater applications into five main classes, namely, monitoring, disaster, military, navigation, and sports, to cover the large spectrum of UWSN. The applications are further divided into relevant subclasses. We have also shown the challenges and opportunities faced by recent deployments of UWSN.

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“…Autonomous Underwater Automobiles (AUVs) that communicate to accomplish specific programs such as underwater tracking in UWSN [3]. Synchronization information between destination points and AUVs make the supply of security complicated.…”

Section: Underwater Sensor Networkmentioning

confidence: 99%

Security based on Received Signal Strength in Localization for Underwater Sensor Networks

Kaur¹,

Sekhon²

2016

CCS Archive

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Underwater sensor networks are envisioned to enable a broad category of underwater applications such as pollution tracking, offshore exploration, and oil spilling. Such applications require precise location information as otherwise the sensed data might be meaningless. On the other hand, security critical issue as underwater sensor networks are typically deployed in harsh environments. Localization is one of the latest research subjects in UWSNs since many useful applying UWSNs, e.g., event detecting. Now day's large number of localization methods arrived for UWSNs. However, few of them take place stability or security criteria. In purposed work taking up localization in underwater such that various wireless sensor nodes get localize to each other. RSS based localization technique used remove malicious nodes from the communication intermediate node list based on RSS threshold value. Purposed algorithm improves more throughput and less end to end delay without degrading energy dissipation at each node. The simulation is conducted in MATLAB and it suggests optimal result as comparison of end to end delay with and without malicious node.

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AURP: An AUV-Aided Underwater Routing Protocol for Underwater Acoustic Sensor Networks

Cited by 129 publications

References 39 publications

Cognitive Routing in Software-Defined Underwater Acoustic Networks

Cognitive Routing in Software-Defined Underwater Acoustic Networks

Underwater Sensor Network Applications: A Comprehensive Survey

Security based on Received Signal Strength in Localization for Underwater Sensor Networks

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