Energy-Balanced Unequal Layering Clustering in Underwater Acoustic Sensor Networks

Hou, Rui; He, Liuting; Huang, Shan; Luo, Jiangtao

doi:10.1109/access.2018.2854276

Cited by 74 publications

(35 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The issue of the energy sink-hole at one-hop and two-hop neighbor coronas of the sink is not addressed by the EEBET protocol. In [29], the authors proposed the energy-balanced unequal layering clustering (EULC) algorithm, which designs UWA-SNs with unequal layering based on the depth of nodes. This approach constructs clusters of varying sizes within the same layer to solve the "hot spot" issue.…”

Section: Related Workmentioning

confidence: 99%

Node Energy Consumption Balanced Multi-Hop Transmission for Underwater Acoustic Sensor Networks Based on Clustering Algorithm

et al. 2020

View full text Add to dashboard Cite

With the advancement and implementation of marine strategies in various countries, it is of great significance to collect marine data by using underwater acoustic sensor networks (UWA-SNs). Due to the difficulties in charging or replacing batteries, how to prolong the lifetime of underwater sensor nodes is one of the key problems to be solved. In this paper, we propose a new energy consumption balanced protocol, named as dynamic clustering K-means (DC-K-means) based simplified balanced energy adaptive routing (S-BEAR), to prolong the lifetime of a UWA-SN by balancing the energy consumption of underwater sensor nodes and avoiding the energy hole. First, by considering the residual energy of the underwater sensor nodes, we propose the DC-K-means algorithm to cluster the underwater sensor nodes and optimize the topology of data transmission among underwater sensor nodes so that the overall energy consumption of the system can be reduced and the problem of energy consumption balance of underwater sensor nodes can be solved. Then, the S-BEAR protocol is designed for multi-hop transmissions, where the data collected by each cluster head is transmitted to the surface receiving terminal equipment, and thus further balances and saves the energy consumption of the system. The simulation results demonstrate that the proposed DC-K-means based S-BEAR scheme has the advantages of more balanced energy consumption among sensor nodes and higher overall residual energy as compared to the state-of-the-art schemes.

show abstract

Section: Related Workmentioning

confidence: 99%

Node Energy Consumption Balanced Multi-Hop Transmission for Underwater Acoustic Sensor Networks Based on Clustering Algorithm

et al. 2020

View full text Add to dashboard Cite

show abstract

“…They used an adaptive approach for the LEACH protocol in which the residual energy of clustering head (CH) is considered. Hou et al [24] proposed a new clustering model that considers the required transmission power of sensor nodes, and CH residual energy and loads to improve upon the poor stability and unsatisfactory clustering results of the existing USN clustering algorithms.…”

Section: Related Workmentioning

confidence: 99%

Research on Hybrid Cooperative Charging Scheduling Schemes in Underwater Sensor Networks

2019

View full text Add to dashboard Cite

The lifetime of underwater sensor networks (USNs) can be prolonged significantly thanks to wireless power transfer technology. In this paper, we first proposed a Shortest Path Partial Charging based on Charging Curve Scheme (SPBS) to increase the survival rate of nodes in 3D underwater networks, and then we proposed a concept of secondary charging stations for mobile charging ships to reduce the traveling cost and improve charging efficiency. We first use k-means clustering algorithm to divide our network with k clusters, and then we place our secondary stations at k clustering centers, in this way, mobile charging ships can be charged at secondary stations quickly. Based on secondary stations, we proposed Hamilton Charging Scheme (HCS) using the Hamilton ring, and then we proposed a temporal and spatial collaborative charging algorithm (mCS-TS) for USNs with multiple mobile charging ships and secondary charging stations, which also takes the cluster factor and deadline time into consideration. Simulation results show the effectiveness of our proposed algorithms. INDEX TERMS Underwater sensor networks, survival rate, SPBS, secondary charging stations, mobile charging ships, cluster factor.

show abstract

“…Lately, they introduced several different protocols for WSN, which improves the security issues, enhance the boost energy efficiency and network reliability [19] [20]. Game theory and ML (Machine Learning) has been employed in the solutions of computing routing for the wireless networks [21], [22].…”

Section: Literature Surveymentioning

confidence: 99%

WSN Clustering Based on EECI (Energy Efficient Clustering using Interconnection) Method

2019

IJITEE

View full text Add to dashboard Cite

in WSN, clustering gives an effective way to enhance the network lifetime. Moreover It has been observed that the clustering algorithm utilizes the two main technique first is selection of cluster head and cycling it periodically in order to distribute the energy among the clusters and this in terms increases the lifetime of network. Another challenge comes with this is minimize the energy consumption. In past several algorithm has been proposed to increase the lifetime of the network and energy consumption, however these methodologies lacks from efficiency. In this paper, we have proposed a methodologies named as EE-CI (Energy Efficient Clustering using Interconnection), along with the random updation. Here the networks are parted into different clusters, the cluster updation are done based on the CHC scheme. Moreover, in proposed methodology cluster updation and data sample is determined through the change in sensor data. Here we propose a method for sampling sensor and CHC for selecting the cluster head to balance the energy and improvise the energy efficiency. Moreover, the proposed methodology is evaluated and the result is demonstrated by considering the Leach as existing methodology, experiments results shows that the proposed methodology outperforms the existing methodology.

show abstract

Energy-Balanced Unequal Layering Clustering in Underwater Acoustic Sensor Networks

Cited by 74 publications

References 14 publications

Node Energy Consumption Balanced Multi-Hop Transmission for Underwater Acoustic Sensor Networks Based on Clustering Algorithm

Node Energy Consumption Balanced Multi-Hop Transmission for Underwater Acoustic Sensor Networks Based on Clustering Algorithm

Research on Hybrid Cooperative Charging Scheduling Schemes in Underwater Sensor Networks

WSN Clustering Based on EECI (Energy Efficient Clustering using Interconnection) Method

Contact Info

Product

Resources

About