期刊
SENSORS
卷 21, 期 13, 页码 -出版社
MDPI
DOI: 10.3390/s21134514
关键词
underwater sensor networks; nodes clustering; dragonfly optimization; optimized routing; transmission range; adaptive node clustering technique; ANC-UWSNs
资金
- faculty research fund of Sejong University in 2019
- MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program [IITP-2021-2016-0-00312]
In this paper, an adaptive node clustering technique for UWSNs using a dragonfly optimization algorithm is proposed to optimize routing and network lifespan. Results show that the DFO algorithm outperforms other algorithms by producing a higher number of optimized clusters.
Monitoring of an underwater environment and communication is essential for many applications, such as sea habitat monitoring, offshore investigation and mineral exploration, but due to underwater current, low bandwidth, high water pressure, propagation delay and error probability, underwater communication is challenging. In this paper, we proposed a sensor node clustering technique for UWSNs named as adaptive node clustering technique (ANC-UWSNs). It uses a dragonfly optimization (DFO) algorithm for selecting ideal measure of clusters needed for routing. The DFO algorithm is inspired by the swarming behavior of dragons. The proposed methodology correlates with other algorithms, for example the ant colony optimizer (ACO), comprehensive learning particle swarm optimizer (CLPSO), gray wolf optimizer (GWO) and moth flame optimizer (MFO). Grid size, transmission range and nodes density are used in a performance matrix, which varies during simulation. Results show that DFO outperform the other algorithms. It produces a higher optimized number of clusters as compared to other algorithms and hence optimizes overall routing and increases the life span of a network.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据