Energy-Efficient Guiding-Network-Based Routing for Underwater Wireless Sensor Networks

Liu, Zhixin; Jin, Xiaocao; Yang, Yi; Ma, Kai; Guan, Xinping

doi:10.1109/jiot.2022.3183128

Cited by 26 publications

(8 citation statements)

References 26 publications

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“…To enable time-saving and reliable routing for UWSN, [28] offers the energy-efficient guiding-network-based routing (EEGNBR) protocol. It considers the beneficial distance-vector technique and creates a guiding network to give underwater sensor nodes the shortest route (least hop counts) toward the sinks in order to reduce network latency.…”

Section: Related Workmentioning

confidence: 99%

Energy and Path-Aware-Reliable Routing in Underwater Acoustic Wireless Sensor Networks

Ali

Khan

Bertozzi

et al. 2022

Wireless Communications and Mobile Computing

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In underwater acoustic sensor networks (UASNs), energy awareness, best path selection, reliability, and scalability are among the key factors that decide information delivery to the sea surface. Existing protocols usually do not combine such performance-affecting factors in information routing. As a result, the performance of such protocols usually deteriorates if multiple performance factors are taken into account. To cope with such performance deterioration, this article proposes two routing protocols for UASNs: energy and path-aware reliable routing (EPRR) and cooperative EPRR (Co-EPRR). Compared with the counterpart systems, the proposed protocols have been designed to deal with the problem of long propagation delays and achieve network reliability. The EPRR scheme uses nodes’ physical distance from the surface with its depth, which minimized the delay of packet transmission. The channel interaction time has been reduced, therefore, reducing unwanted channel effects on the data. Furthermore, the density of the nodes in the upper part of the network prevents data loss and limits the rapid death of the nodes. The second proposed scheme, Co-EPRR, uses the concept of routing information from the source to the destination on multiple paths. In Co-EPRR routing, the destination node can receive more than one copy of the data packet. This reduces unfavorable channel effects during data delivery. Both the schemes show good performance in terms of packet delivery ratio, received packet analysis, and end-to-end delay.

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Section: Related Workmentioning

confidence: 99%

Energy and Path-Aware-Reliable Routing in Underwater Acoustic Wireless Sensor Networks

Ali

Khan

Bertozzi

et al. 2022

Wireless Communications and Mobile Computing

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“…The sensors of UWSN are located underwater for evaluating the monitoring features such as density, temperature, pressure and so on [5]. UWSN is extensively used in diverse fields such as military target tracking, oil/gas spill monitoring, submarine detection, offshore exploration, disaster prevention and so on [6]. The UWSN faces various issues such as strong network dynamics, expensive deployment, less available bandwidth and restricted battery energy [7].…”

Section: Introductionmentioning

confidence: 99%

Multi Objective Energy Based Improved Jellyfish Swarm Optimization for Effective Cluster Head Discovery in UWSN

2023

IJIES

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Underwater wireless sensor networks (UWSNs) have a huge amount of sensors located underwater to collect data from the underwater scenario. UWSN is considered a promising method for monitoring and exploring an underwater scenario. Energy-efficient and reliable data broadcasting are considered challenging tasks, because of the limited energy source of sensors. To address this issue, an energy-efficient cluster head (CH) selection and multi-hop routing are developed in UWSN. The multi objective energy based improved jellyfish swarm optimization (MOEIJSO) is proposed to select optimal CHs from normal sensors. The input parameters of MOEIJSO are residual energy, neighbor node distance, sink distance, and CH balancing factor. Next, multi-hop routing is developed by using ant colony optimization (ACO) for delivering the data packets. Therefore, the proposed MOEIJSO-ACO method is used to improve energy efficiency while increasing data delivery. The proposed MOEIJSO-ACO method is evaluated by using the alive and dead nodes, total energy consumption, data received in base station (BS), and life expectancy. The existing researches such as metaheuristics-based clustering with a routing (MCR) for UWSN, modified low energy adaptive clustering hierarchy (MLEACH) and cooperative energy-efficient routing (CEER) approach are used to compare the MOEIJSO-ACO method. The alive nodes of the MOEIJSO-ACO are 399 for 800 rounds, which is high when compared to the MCR-UWSN.

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“…Redundant data transmissions increase the traffic pressure of UASNs, waste energy, and enhance the probability of data conflict and network congestion [ 11 , 12 ]. The traditional multi-hop routing protocols use unicast forwarding to choose single-route or multi-route forwarding, while they frequently exchange the collected information about the neighboring nodes to maintain the route [ 13 , 14 ]. Recently, opportunistic pouting (OR) uses broadcast forwarding by omnidirectional antennae to ensure network performance (such as the interconnection of communication, etc.…”

Section: Introductionmentioning

confidence: 99%

“…Some directional transmissions try to adjust the effective selection range of forwarders to control duplicated forwarding [ 10 ], while they might receive no successful forwarding ACK and cause multiple extra forwarding because coordination forwarders are not in the communication range of those with higher priority. And some location-based routing protocols and depth-based routing protocols select partial nodes toward the sinks or autonomous underwater vehicles (AUVs) as relay nodes under some routing metric, but these protocols need to transmit a longer data packet, including depth or location information, in the data forwarding process, or to interactively communicate some controlling information [ 14 , 16 ]. In addition, the uneven distribution of the load results in routing voids or long detours [ 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

Lightweight Differentiated Transmission Based on Fuzzy and Random Modeling in Underwater Acoustic Sensor Networks

Cao

Dou

Liu

et al. 2023

Sensors

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Energy-efficient and reliable underwater acoustic communication attracts a lot of research due to special marine communication conditions with limited resources in underwater acoustic sensor networks (UASNs). In their final analysis, the existing studies focus on controlling redundant communication and route void that greatly influence UASNs’ comprehensive performances. Most of them consider directional or omnidirectional transmission for partial optimization aspects, which still have many extra data loads and performance losses. This paper analyzes the main issue sources causing redundant communication in UASNs, and proposes a lightweight differentiated transmission to suppress extra communication to the greatest extent as well as balance energy consumption. First, the layered model employs layer ID to limit the scale of the data packet header, which does not need depth or location information. Second, the layered model, fuzzy-based model, random modeling and directional-omnidirectional differentiated transmission mode comb out the forwarders step by step to decrease needless duplicated forwarding. Third, forwarders are decided by local computation in nodes, which avoids exchanging controlling information among nodes. Simulation results show that our method can efficiently reduce the network load and improve the performance in terms of energy consumption balance, network lifetime, data conflict and network congestion, and data packet delivery ratio.

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Energy-Efficient Guiding-Network-Based Routing for Underwater Wireless Sensor Networks

Cited by 26 publications

References 26 publications

Energy and Path-Aware-Reliable Routing in Underwater Acoustic Wireless Sensor Networks

Energy and Path-Aware-Reliable Routing in Underwater Acoustic Wireless Sensor Networks

Multi Objective Energy Based Improved Jellyfish Swarm Optimization for Effective Cluster Head Discovery in UWSN

Lightweight Differentiated Transmission Based on Fuzzy and Random Modeling in Underwater Acoustic Sensor Networks

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