A self-healing clustering algorithm for underwater sensor networks

Huang, Chenn‐Jung; Wang, Yu-Wu; Lin, Chin-Fa; Chen, Yu-To; Chen, Heng-Ming; Shen, Hung-Yen; Chen, You-Jia; Chen, I-Fan; Hu, Kai‐Wen; Yang, Dian-Xiu

doi:10.1007/s10586-010-0139-2

Cited by 20 publications

(10 citation statements)

References 11 publications

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“…With the consideration of various shadowing and path loss conditions in a basic operational area, the closed‐form expressions for the optimal number of clusters have also presented. Huang et al developed a clustering algorithm for UWSNs that integrates the concepts of application‐specific data aggregation technique and energy‐efficient cluster‐based routing to find the best performance in terms of application‐perceived quality and system enhancement lifetime. Further, they have also taken the idea of self‐healing to minimize the extremely frequent occurrence of reclustering due to the breakdown of individual clusters.…”

Section: Motivationmentioning

confidence: 99%

Energy‐efficient design of 3D UWSNs leveraging compressive sensing and principal component analysis: A communication techniques perspective

Yadav

Kumar

2019

Int J Communication

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Summary The design of energy‐efficient underwater wireless sensor networks (UWSNs) poses many challenges due to the intrinsic properties of propagation medium and limited battery power of sensor nodes. This paper proposes the concept of optimal clustering for three‐dimensional (3D) UWSNs leveraging compressive sensing (CS) and principal component analysis (PCA) technique of data compression. Optimal clustering reduces the energy consumption by selecting the optimal number of clusters whereas CS and PCA compression techniques reduce the energy consumption by considering a lesser number of samples and reduce the data redundancy at cluster heads (CHs) level, respectively. Moreover, three communication techniques like acoustic, electromagnetic (EM), and free‐space optical (FSO) wave are considered for communication in 3D UWSNs. We compared the energy efficiency for all three communication techniques by examining the three base station (BS) positions at the center, at the corner, and at the lateral midpoint of the 3D sensing area. Moreover, performance parameters (network lifetime, throughput, packet drop rate, and latency) are also evaluated for 3D UWSNs. It is observed that PCA outperforms the CS technique. The proposed technique is suitable for long‐term and densely deployed 3D UWSNs, in which saving energy is of crucial importance.

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Section: Motivationmentioning

confidence: 99%

Energy‐efficient design of 3D UWSNs leveraging compressive sensing and principal component analysis: A communication techniques perspective

Yadav

Kumar

2019

Int J Communication

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“…Current research of UWSNs has focused on acoustic communication, network protocol, routing algorithms, and node localization and tracking [21,22,23]. However, the strategy of node deployment directly correlates to network operation performances and thus has a strong influence on designs of network protocol and topology control subsequently.…”

Section: Related Workmentioning

confidence: 99%

A High-Efficiency Uneven Cluster Deployment Algorithm Based on Network Layered for Event Coverage in UWSNs

Shu

Liu

Jiang

2016

Sensors

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Most existing deployment algorithms for event coverage in underwater wireless sensor networks (UWSNs) usually do not consider that network communication has non-uniform characteristics on three-dimensional underwater environments. Such deployment algorithms ignore that the nodes are distributed at different depths and have different probabilities for data acquisition, thereby leading to imbalances in the overall network energy consumption, decreasing the network performance, and resulting in poor and unreliable late network operation. Therefore, in this study, we proposed an uneven cluster deployment algorithm based network layered for event coverage. First, according to the energy consumption requirement of the communication load at different depths of the underwater network, we obtained the expected value of deployment nodes and the distribution density of each layer network after theoretical analysis and deduction. Afterward, the network is divided into multilayers based on uneven clusters, and the heterogeneous communication radius of nodes can improve the network connectivity rate. The recovery strategy is used to balance the energy consumption of nodes in the cluster and can efficiently reconstruct the network topology, which ensures that the network has a high network coverage and connectivity rate in a long period of data acquisition. Simulation results show that the proposed algorithm improves network reliability and prolongs network lifetime by significantly reducing the blind movement of overall network nodes while maintaining a high network coverage and connectivity rate.

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“…Because network clustering has many advantages over flat networks for wireless sensor networks, such as allowing for scalability of MAC and routing [16], it has been widely investigated [17][18][19][20][21][22][23]. In a mobile and large network, convergence to new routing paths after topology changes takes time.…”

Section: Related Workmentioning

confidence: 99%

MURAO: A multi-level routing protocol for acoustic-optical hybrid underwater wireless sensor networks

Fei

2012

2012 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON)

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In the past decade, underwater acoustic sensor networks (UW-ASNs) have been studied broadly in various aquatic applications, enabling humans to observe and explore the vast underwater domain. Although acoustic underwater communications are able to support long-range and low-bandwidth applications, the capabilities of UW-ASN are greatly limited by the long delay and low data rate of acoustic communications. Underwater freespace optical communication is a potential alternative solution. However, it has short transmission ranges and requires dense deployment. In this paper, we propose a novel acoustic-optical hybrid architecture for underwater wireless sensor networks, and a multi-level Q-learning based routing protocol, MURAO, for such networks. The network is physically partitioned into several groups and logically divided into two layers. The upperlayer group leaders supervise the routing in the lower layer, and the lower-layer group members carry out the actual data packet routing. Because upper-layer group leaders have a boarder view of the network and all the groups are able to carry out the learning process concurrently, the performance of routing is greatly improved compared to the flat Q-learning-based routing. The experiment results show that MURAO is more robust to changes of network topology, and achieves much higher delivery rates as well as shorter delays in a dynamic network than the flat Q-learning routing.

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A self-healing clustering algorithm for underwater sensor networks

Cited by 20 publications

References 11 publications

Energy‐efficient design of 3D UWSNs leveraging compressive sensing and principal component analysis: A communication techniques perspective

Energy‐efficient design of 3D UWSNs leveraging compressive sensing and principal component analysis: A communication techniques perspective

A High-Efficiency Uneven Cluster Deployment Algorithm Based on Network Layered for Event Coverage in UWSNs

MURAO: A multi-level routing protocol for acoustic-optical hybrid underwater wireless sensor networks

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