.png){kind=icon}
返回
A Genetic Algorithm-Based, Dynamic Clustering Method Towards Improved WSN Longevity
.png){kind=icon}
PRE
AI
DOI：10.1007/s10922-016-9379-7.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The dynamic nature of wireless sensor networks (WSNs) and numerous possible cluster configurations make searching for an optimal network structure on-the-fly an open challenge. To address this problem, we propose a genetic algorithm-based, self-organizing network clustering (GASONeC) method that provides a framework to dynamically optimize wireless sensor node clusters. In GASONeC, the residual energy, the expected energy expenditure, the distance to the base station, and the number of nodes in the vicinity are employed in search for an optimal, dynamic network structure. Balancing these factors is the key of organizing nodes into appropriate clusters and designating a surrogate node as cluster head. Compared to the state-of-the-art methods, GASONeC greatly extends the network life and the improvement up to 43.44 %. The node density greatly affects the network longevity. Due to the increased distance between nodes, the network life is usually shortened. In addition, when the base station is placed far from the sensor field, it is preferred that more clusters are formed to conserve energy. The overall average time of GASONeC is 0.58 s with a standard deviation of 0.05.
Keyword:
Wireless sensor networks
Genetic algorithms
Clustering
Energy consumption
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.9
论文数:
1.0K
被引数:
1.3K
机构
引用论文
HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networksHEED: 一种用于ad hoc传感器网络的混合，节能，分布式分簇方法
OAAI
OAAI分享收藏分享收藏A Fuzzy Logic-Based Clustering Algorithm for WSN to Extend the Network Lifetime.png)
IEEE SENSORS JOURNAL
IEEE SENSORS JOURNALIF4.5
PREAI
分享收藏分享收藏
查看更多内容