An energy-efficient relay node selection scheme for underwater acoustic sensor networks

Su, Ruoyu; Venkatesan, R.; Li, Cheng

doi:10.1080/23335777.2016.1145742

Cited by 14 publications

(11 citation statements)

References 26 publications

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“…They use the linear programming approach for the relay node selection with the principle aim of enhancing the network lifetime. They also implemented a routing metric that considers both the transmitting energy and the residual energy [25]. Additionally, Khan et al presented a scheme for relay node selection in UWSNs based on harvested energy levels.…”

Section: Related Workmentioning

confidence: 99%

“…However, the coordination between static and dynamic nodes during communication is lacking in these three types of deployment architectures. To support these deployment approaches, a linear programming-centric approach has been suggested for selecting underwater relay nodes focusing on a longer network lifetime [25].In a similar work, node-level energy harvesting capability has been used as a parameter in relay node selection for a longer network lifetime [26]. However, the impact of self-mobility of underwater nodes due to underwater flow is not considered in both approaches, including deployment-centric network lifetime optimization and harvested energy level-centric network lifetime optimization.…”

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confidence: 99%

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confidence: 99%

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W-GUN: Whale Optimization for Energy and Delay-Centric Green Underwater Networks

Rathore

Sangwan

Mazumdar

et al. 2020

Sensors

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Underwater sensor networks (UWSNs) have witnessed significant R&D attention in both academia and industry due to their growing application domains, such as border security, freight via sea or river, natural petroleum production and the fishing industry. Considering the deep underwater-oriented access constraints, energy-centric communication for the lifetime maximization of tiny sensor nodes in UWSNs is one of the key research themes in this domain. Existing literature on green UWSNs are majorly adapted from the existing techniques in traditional wireless sensor network relying on geolocation and the quality of service-centric underwater relay node selection, without paying much attention to the dynamic underwater network environments. To this end, this paper presents an adapted whale and wolf optimization-based energy and delay-centric green underwater networking framework (W-GUN). It focuses on exploiting dynamic underwater network characteristics by effectively utilizing underwater whale-centric optimization in relay node selection. Firstly, an underwater relay node optimization model is mathematically derived, focusing on underwater whale dynamics for incorporating realistic underwater characteristics in networking. Secondly, the optimization model is used to develop an adapted whale and grey wolf optimization algorithm for selecting optimal and stable relay nodes for centric underwater communication paths. Thirdly, a complete workflow of the W-GUN framework is presented with an optimization flowchart. The comparative performance evaluation attests to the benefits of the proposed framework and is compared to state-of-the-art techniques considering various metrics related to underwater network environments.Sensors 2020, 20, 1377 2 of 23 water-based transport applications [6,7], oil, and natural gas production applications [8,9], and developing fishing-centric industries [10,11]. In underwater networking, tiny sensor nodes are deployed underwater, as well as on the upper surface layer for monitoring the specific underwater area [12]. These underwater nodes communicate with the surface nodes, acting as access points or cluster heads for reaching the sink node of the network, which accumulates the information and communicates with the cloud-enabled computing resources [13]. Underwater networking is significantly challenging compared to traditional wireless networking due to the dynamic self-mobility of the medium of communication and constraints in signal propagation in the underwater environment [14][15][16]. In this constrained networking environment, the underwater network deployment-oriented challenges further complicate scientific investigations towards the development of an energy-centric green underwater network for various application domains [17][18][19].Towards enabling green underwater networking, several service and geolocation-centric techniques of varying quality have been suggested [20,21]. A heuristic approach has been suggested in underwater networking for solving the surface gateway deployment o...

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Section: Related Workmentioning

confidence: 99%

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confidence: 99%

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W-GUN: Whale Optimization for Energy and Delay-Centric Green Underwater Networks

Rathore

Sangwan

Mazumdar

et al. 2020

Sensors

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“…The sensor nodes deployed underwater operate on limited battery power, the process of the substituting or charging a node's battery is difficult and usually not preferred [11]. There are various protocols for UWSNs that do not introduce a reliability technique in the data forwarding process [12][13][14][15]. Therefore, they have no promising results in data delivery to the water surface, because in these protocols, a source node delivers a packet through a single path.…”

Section: Introductionmentioning

confidence: 99%

Energy Balanced Localization-Free Cooperative Noise-Aware Routing Protocols for Underwater Wireless Sensor Networks

et al. 2019

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Owing to the harsh and unpredictable behavior of the sea channel, network protocols that combat the undesirable and challenging properties of the channel are of critical significance. Protocols addressing such challenges exist in literature. However, these protocols consume an excessive amount of energy due to redundant packets transmission or have computational complexity by being dependent on the geographical positions of nodes. To address these challenges, this article designs two protocols for underwater wireless sensor networks (UWSNs). The first protocol, depth and noise-aware routing (DNAR), incorporates the extent of link noise in combination with the depth of a node to decide the next information forwarding candidate. However, it sends data over a single link and is, therefore, vulnerable to the harshness of the channel. Therefore, routing in a cooperative fashion is added to it that makes another scheme called cooperative DNAR (Co-DNAR), which uses source-relay-destination triplets in information advancement. This reduces the probability of information corruption that would otherwise be sent over a single source-destination link. Simulations-backed results reveal the superior performance of the proposed schemes over some competitive schemes in consumed energy, packet advancement to destination, and network stability.

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“…In comparison, an event or time-driven scheme that involves periodic data communications will result in relatively higher energy consumption. Proposed methods have ranged from the use of complex sensors [7], through efficient relay node selection [8], to cooperative data gathering [9] and game-theoretical energy management designs [10]. However, each approach addresses a specific application and none introduce a general framework to guide balancing the energy cost of onboard image processing with that of communication.…”

Section: Introductionmentioning

confidence: 99%

Autonomous monitoring framework for resource-constrained environments

Nazir

Hamdoun

Verdicchio

et al. 2018

Cyber-Physical Systems

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The availability of low-cost imaging devices for embedded applications has enabled development of wireless monitoring systems capable of acquiring and transmitting both image and video data. Remote deployment of such systems is often constrained by limited power resources, thus a system must operate autonomously, balancing operational needs against available resources. This paper describes a framework for the design and implementation of an autonomous embedded remote monitoring system employing information-driven sensing to conserve energy and extend the system deployment lifetime. The results from two case studies show improvements over a conventional system and other similar systems through the use of intelligent algorithms for reliable event detection and enhanced system operational lifetime by efficient utilisation of limited resources. The results are applicable to low-power battery-operated field devices offering better resource utilisation in disaster management systems, intelligent transportation and remote monitoring.

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An energy-efficient relay node selection scheme for underwater acoustic sensor networks

Cited by 14 publications

References 26 publications

W-GUN: Whale Optimization for Energy and Delay-Centric Green Underwater Networks

W-GUN: Whale Optimization for Energy and Delay-Centric Green Underwater Networks

Energy Balanced Localization-Free Cooperative Noise-Aware Routing Protocols for Underwater Wireless Sensor Networks

Autonomous monitoring framework for resource-constrained environments

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