Robust optimization based on ant colony optimization in the data transmission path selection of WSNs

被引:6
|
作者
Zhang, Zhaohui [1 ]
Li, Jing [1 ]
Xu, Nan [2 ]
机构
[1] Xidian Univ, Sch Math & Stat, Xian 710071, Peoples R China
[2] Xidian Univ, Secur Dept, Xian 710071, Peoples R China
来源
NEURAL COMPUTING & APPLICATIONS | 2021年 / 33卷 / 24期
基金
中国国家自然科学基金;
关键词
Ant colony optimization; Robustness; Ratio of the successful path; Network overloads; PARTICLE SWARM OPTIMIZATION; WIRELESS SENSOR NETWORKS; ARTIFICIAL BEE COLONY; BIG DATA; ALGORITHM;
D O I
10.1007/s00521-021-06303-0
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Secure data transmission plays a very important role in the energy-efficient path topology establishment of wireless sensor networks. Robustness of data transmission path has been paid much attention. However, most researchers only focus on the security between data and path and ignore the impacts of malicious nodes. In this research, we first detect the malicious nodes by using the Bayesian voting algorithm and remove them from the network before the data transmission path construction. Then, we propose a new robust optimization based on ant colony optimization (ROACO) in the data transmission path selection to improve the lifetime of the network, where the residual energy of nodes, the distances between nodes, data redundancy and link security are taken into consideration comprehensively in the formulation of the probability formula of the node path selection. The MATLAB simulation results show that the proposed algorithm prolongs the network lifetime, reduces the load of the nodes and also improves the ratio of the successful path of the network obviously.
引用
收藏
页码:17119 / 17130
页数:12
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