Energy Consumption at the Node in Underwater Wireless Sensor Network (UWSNs)

Rachman, Reza; Laksana, Eka Purwa; Putra, Darma Setiawan; Sari, Riri Fitri

doi:10.1109/ems.2012.71

Cited by 8 publications

(2 citation statements)

References 5 publications

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“…After the sink node completes the 2D convex hull activation process, the communication complexity of the process can be obtained, and it is O ( n × h ) according to the GiftWrapping algorithm [ 34 ], where h denotes the required number of active nodes to achieve the 2D convex hull, and its asymptotic value is

. Given that the numbers of elements in Nei(f j i ) − NeigInter i i+ 1 and NeigInter i i+ 1 are N ij and

respectively, node f j i broadcasts a message to its neighbor child nodes, and all parent nodes compare the distances of all neighbor child nodes and must send a total of

messages for an overall situation significance.…”

Section: Complexity Analysismentioning

confidence: 99%

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

Jiang

Liu

et al. 2016

Sensors

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Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don’t discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability.

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. Given that the numbers of elements in Nei(f j i ) − NeigInter i i+ 1 and NeigInter i i+ 1 are N ij and

respectively, node f j i broadcasts a message to its neighbor child nodes, and all parent nodes compare the distances of all neighbor child nodes and must send a total of

messages for an overall situation significance.…”

Section: Complexity Analysismentioning

confidence: 99%

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

Jiang

Liu

et al. 2016

Sensors

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“…Then, the energy consumption of the underwater acoustic sensing node during communication is analyzed [46]. Figure 1 shows the power consumption of the sensor of a UASN.…”

Section: Problem Description and System Model A Problem Descriptionmentioning

confidence: 99%

An Energy-Efficient MAC Protocol for Three-Dimensional Underwater Acoustic Sensor Networks With Time Synchronization and Power Control

et al. 2023

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In recent years, Underwater Acoustic Sensor Networks (UASNs) have gained considerable attention for their unique role in detecting and monitoring the underwater environment. However, due to the long propagation time, high bit error rate, and limited bandwidth of underwater acoustic systems, the design of media access control (MAC) protocols is extremely complex, especially for the power consumption of UASNs. Therefore, this paper proposes an energy-efficient MAC protocol for three-dimensional UASNs with time synchronization and power control (TDTSPC-MAC). The proposed protocol is a hybrid access scheme for three-dimensional UASN using techniques such as time synchronization, power control, clustering, layering, and sleep mechanisms. Moreover, the TDTSPC-MAC protocol uses the hierarchical concept and distributed clustering algorithm to divide the three-dimensional space, and combines time synchronization and power control strategies to avoid collisions. Besides, energy consumption is reduced through monitoring and sleep mode. Simulation results demonstrate that the proposed TDTSPC-MAC protocol has reasonable data transmission delay time, throughput, energy consumption, and other performance.

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Minimizing the Total Energy Consumption in Multi-hop UWASNs

Geethu

Babu

2015

Wireless Pers Commun

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This paper investigates the total energy consumption in multi-hop underwater acoustic sensor networks (UWASNs) for a given target signal to noise ratio (SNR) requirement. Specifically, our aim is to minimize the energy consumption along the route between source and destination and to find the optimal hop distance that result in minimum energy consumption, by taking into account the propagation characteristics of sound signals through the underwater acoustic medium. The proposed study will form the basis for the design of energy efficient routing protocols that select minimum energy route in UWASNs. The impact of various characteristics of underwater acoustic signal propagation such as attenuation, noise, and the dependence of usable bandwidth and transmit power on distance, are considered for the energy consumption analysis. Further, analysis is carried out for both shallow and deep water scenarios under the assumption that each node can adjust its transmission power for a link so that the signal reaches the destination node, satisfying a target received SNR. We observe that, a linear equidistant network consumes minimum energy for both shallow as well as deep water scenarios.

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Energy Consumption at the Node in Underwater Wireless Sensor Network (UWSNs)

Cited by 8 publications

References 5 publications

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

An Energy-Efficient MAC Protocol for Three-Dimensional Underwater Acoustic Sensor Networks With Time Synchronization and Power Control

Minimizing the Total Energy Consumption in Multi-hop UWASNs

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