Next Article in Journal
Multi-Winner Election Control via Social Influence: Hardness and Algorithms for Restricted Cases
Previous Article in Journal
COVID-19 Outbreak Prediction with Machine Learning
Previous Article in Special Issue
When 5G Meets Deep Learning: A Systematic Review
Open AccessArticle

A Clustering Routing Algorithm Based on Improved Ant Colony Optimization Algorithms for Underwater Wireless Sensor Networks

by Xingxing Xiao 1,2,3 and Haining Huang 1,2,3,*
1
Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
2
Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing, Chinese Academy of Sciences, Beijing 100190, China
3
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Algorithms 2020, 13(10), 250; https://doi.org/10.3390/a13100250
Received: 15 August 2020 / Revised: 20 September 2020 / Accepted: 30 September 2020 / Published: 1 October 2020
(This article belongs to the Special Issue Networks, Communication, and Computing Vol. 2)
Because of the complicated underwater environment, the efficiency of data transmission from underwater sensor nodes to a sink node (SN) is faced with great challenges. Aiming at the problem of energy consumption in underwater wireless sensor networks (UWSNs), this paper proposes an energy-efficient clustering routing algorithm based on an improved ant colony optimization (ACO) algorithm. In clustering routing algorithms, the network is divided into many clusters, and each cluster consists of one cluster head node (CHN) and several cluster member nodes (CMNs). This paper optimizes the CHN selection based on the residual energy of nodes and the distance factor. The selected CHN gathers data sent by the CMNs and transmits them to the sink node by multiple hops. Optimal multi-hop paths from the CHNs to the SN are found by an improved ACO algorithm. This paper presents the ACO algorithm through the improvement of the heuristic information, the evaporation parameter for the pheromone update mechanism, and the ant searching scope. Simulation results indicate the high effectiveness and efficiency of the proposed algorithm in reducing the energy consumption, prolonging the network lifetime, and decreasing the packet loss ratio. View Full-Text
Keywords: underwater wireless sensor networks; ant colony optimization algorithms; clustering routing algorithms; energy efficiency; network lifetime underwater wireless sensor networks; ant colony optimization algorithms; clustering routing algorithms; energy efficiency; network lifetime
Show Figures

Figure 1

MDPI and ACS Style

Xiao, X.; Huang, H. A Clustering Routing Algorithm Based on Improved Ant Colony Optimization Algorithms for Underwater Wireless Sensor Networks. Algorithms 2020, 13, 250.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop