General optimization framework for surface gateway deployment problem in underwater sensor networks

Ibrahim, Saleh; Al-Bzoor, Manal; Li, Jun; Ammar, Reda A.; Rajasekaran, Sanguthevar; Cui, Jun-Hong

doi:10.1186/1687-1499-2013-128

Cited by 15 publications

(24 citation statements)

References 20 publications

(19 reference statements)

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“…Due to the abovementioned limitations of USNs, most studies have been focused on specific techniques to enhance USN performance metrics. Ibrahim et al propose the use of multiple surfacelevel gateways to improve end-to-end delay and reduce energy consumption by distributing traffic loads [10,12]. The authors show the significant advantages of their approach.…”

Section: Related Workmentioning

confidence: 99%

“…However, the performance of USNs is greatly limited by the low-bandwidth and high propagation delay of underwater acoustic communications [9,10]. In this regard, several network-related factors such as the packet reception rate and the delay and throughput, as well as node related factors, such as the transceiver power, the battery, and the CPU power, should be taken into consideration [11].…”

Section: Related Workmentioning

confidence: 99%

“…All three boats followed a specific, predefined path to reach the target point. Then, the second and the third ones went back to their original positions, (10,76) and (44, 21), respectively, while the first one tracked a different path to go to a new target point located at (34,34). The full dataset used in this study is given in Table 1 and comprises 164 sets of input-output variables values.…”

Section: Performance Evaluation Of the Proposed Ann Modelmentioning

confidence: 99%

“…Boat 1 was initially located at the virtual -plane position (10,76), Boat 2 at (24, 50), and Boat 3 at (44, 21). There was a target point which was located at the static position (27,34).…”

Section: Performance Evaluation Of the Proposed Ann Modelmentioning

confidence: 99%

See 3 more Smart Citations

ANN-Based Control of a Multiboat Group for the Deployment of an Underwater Sensor Network

Michailidis

Tuna

Gezer

et al. 2014

International Journal of Distributed Sensor Networks

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Underwater sensor networks (USNs) can be used for several types of commercial and noncommercial applications. However, some constraints resulting from the nature of aquatic environments severely limit their use. Due to constraints such as large propagation latency, low-bandwidth capacity, and short-distance communications, a large number of USN nodes are deployed to provide reliability in most applications. In this study, an unattended deployment approach based on the use of an autonomous boat group is proposed. A map of the deployment zone and optimal locations of USN nodes are fed into the onboard computers of the boat group. After processing these data and determining paths to be followed, the boat group deploys sensor nodes at predetermined locations. During the deployment, the boat group is controlled by an artificial neural network-(ANN-) based control system for reducing path errors. A set of performance evaluations is given to prove efficiency of the proposed control system. Performance results show that the boat group can successfully follow a predefined path set and deploy USN nodes. The tradeoffs between energy consumptions, end-to-end delay, and number of hops between underwater relay nodes of energy-efficient USN are also examined. The results indicate that increasing the number of hops reduces the total energy consumption and the end-to-end delay.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Performance Evaluation Of the Proposed Ann Modelmentioning

confidence: 99%

“…Boat 1 was initially located at the virtual -plane position (10,76), Boat 2 at (24, 50), and Boat 3 at (44, 21). There was a target point which was located at the static position (27,34).…”

Section: Performance Evaluation Of the Proposed Ann Modelmentioning

confidence: 99%

See 2 more Smart Citations

ANN-Based Control of a Multiboat Group for the Deployment of an Underwater Sensor Network

Michailidis

Tuna

Gezer

et al. 2014

International Journal of Distributed Sensor Networks

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“…The other method is to use surface gateways floating on water to link UANETs especially underwater sensor networks [29] through acoustic wave or green/blue lasers. The marine Internet above water surface can be used to inter-network different UANETs by connecting their surface gateways as illustrated in Fig.…”

Section: Underwater Inter-networkingmentioning

confidence: 99%

A Possible Development of Marine Internet: A Large Scale Cooperative Heterogeneous Wireless Network

Jiang¹,

Chen²

2015

JCC

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Today, terrestrial Internet can be easily accessed with various types of terminals almost anytime and anywhere on the land. But this is not yet the case in the ocean mainly due to huge differences between terrestrial and marine environments. Although satellite Internet services are available in marine environments, at the time-being, they are neither cost-effective nor popular due to their inherent weaknesses in construction, launching and operation. Ever-increasing human activities in the ocean require marine Internet to provide handy, reliable and cost-effective high-speed Internet access not only on surface but also underwater in marine environments. This is due to the fact that a huge number of sensors and things have been deployed underwater, and this number is still increasing. How to interconnect them becomes an important issue that is necessarily addressed in order to form large and sophisticated underwater systems. This paper discusses the major available network technologies and new networking approaches that can be used to develop marine Internet, particularly a large scale cooperative heterogeneous wireless network, along with some further research issues.

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Investigation of maximum lifetime and minimum delay trade‐off in underwater sensor networks

Yildiz

2019

Int J Communication

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Summary Underwater acoustic sensor networks (UASNs) are subjected to harsh characteristics of underwater acoustic channel such as severe path losses, noise, and high propagation delays. Among these constraints, propagation delay (more generally, end‐to‐end delay) is the most dominating limitation especially for time‐critical UASN applications. Although the minimization of end‐to‐end delay can be achieved by using the minimum hop routing, this solution cannot lead prolonged lifetimes since nodes consume excessive energy for transmission over long links. On the other hand, the maximization of network lifetime is possible by using energy efficient paths, which consist of relatively short links but high number of hops. However, this solution results in long end‐to‐end delays. Hence, there is a trade‐off between maximizing the network lifetime and minimizing the end‐to‐end delay in UASNs. In this work, we develop a novel multi‐objective–optimization (MOO) model that jointly maximizes the network lifetime while minimizing the end‐to‐end delay. We systematically analyze the effects of limiting the end‐to‐end delay on UASN lifetime. Our results reveal that the minimum end‐to‐end delay routing solution results in at most 72.93% reduction in maximum network lifetimes obtained without any restrictions on the end‐to‐end delay. Nevertheless, relaxing the minimum end‐to‐end delay constraint at least by 30.91% yields negligible reductions in maximum network lifetimes.

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General optimization framework for surface gateway deployment problem in underwater sensor networks

Cited by 15 publications

References 20 publications

ANN-Based Control of a Multiboat Group for the Deployment of an Underwater Sensor Network

ANN-Based Control of a Multiboat Group for the Deployment of an Underwater Sensor Network

A Possible Development of Marine Internet: A Large Scale Cooperative Heterogeneous Wireless Network

Investigation of maximum lifetime and minimum delay trade‐off in underwater sensor networks

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