An improved DV-Hop algorithm for wireless sensor networks based on neural dynamics
文献类型：期刊论文
| 作者 | Liu, Jingping4,5; Liu, Mei4; Du, Xiujuan6; Stanimirovi, Predrag S.2; Jin, Long1,3 |
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2022-06-28 |
| 卷号 | 491页码:172-185 |
| 关键词 | Localization DV-Hop Neural dynamics Convergence analyses Anti-noise analyses |
| ISSN号 | 0925-2312 |
| DOI | 10.1016/j.neucom.2022.03.050 |
| 通讯作者 | Jin, Long(jinlongsysu@foxmail.com) |
| 英文摘要 | Among the localization algorithms of wireless sensor networks (WSNs), the distance vector-hop (DV-Hop) algorithm has been widely concerned thanks to its simplicity, low hardware requirements, and easy implementation. However, the localization accuracy of the DV-Hop algorithm declines greatly when the sensor nodes are unevenly distributed. To improve the accuracy of the DV-Hop algorithm, we propose an improved DV-Hop algorithm based on neural dynamics (ND-DV-Hop). First, the fluctuant range of dis-tance errors between the unknown nodes and the anchor nodes is computed via error analysis. Then, the traditional localization model is transformed into an algebraic equation in which the distances and coordinates change with time. Besides, a neural dynamics (ND) algorithm is used to solve the equation and obtain the solution with the residual errors eliminated. Theoretical analyses are provided to verify the convergence and anti-noise performance of the ND-DV-Hop algorithm. Finally, numerical simulations are carried out to confirm the superiority, efficiency, robustness, and accuracy of the proposed algorithm for dealing with WSNs localization problems.(c) 2022 Elsevier B.V. All rights reserved. |
| 资助项目 | Key Laboratory of IoT of Qinghai[2022-ZJ-Y21] ; Natural Science Foundation of China[62176109] ; Natural Science Foundation of Gansu Province[21JR7RA531] ; Team Project of Natural Science Foundation of Qinghai Province China[2020-ZJ-903] ; Gansu Provincial Youth Doctoral Fund of Colleges and Universities[2021QB-003] ; Fundamental Research Funds for the Central Universities[lzujbky-2021-65] ; Supercomputing Center of Lanzhou University ; CAS Light of West China Program ; Natural Science Foundation of Chongqing (China)[cstc2020jcyjzdxmX0028] ; Chongqing Entrepreneurship and Innovation Support Program for Overseas Returnees[CX2021100] ; Ministry of Education, Science and Technological Development, Republic of Serbia[451-03-68/2022-14/200124] ; Science Fund of the Republic of Serbia[7750185] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000788143600015 |
| 出版者 | ELSEVIER |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/15843]  |
| 专题 | 中国科学院重庆绿色智能技术研究院 |
| 通讯作者 | Jin, Long |
| 作者单位 | 1.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing Key Lab Big Data & Intelligent Comp, Chongqing 400714, Peoples R China 2.Univ Nis, Fac Sci & Math, Viegradska 33, Nish 18000, Serbia 3.Lanzhou Univ, Dept Comp Sci, Lanzhou 730000, Peoples R China 4.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China 5.Qinghai Normal Univ, Network Informat Ctr, Xining 810016, Peoples R China 6.Qinghai Normal Univ, Comp Coll, Xining 810016, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Jingping,Liu, Mei,Du, Xiujuan,et al. An improved DV-Hop algorithm for wireless sensor networks based on neural dynamics[J]. NEUROCOMPUTING,2022,491:172-185. |
| APA | Liu, Jingping,Liu, Mei,Du, Xiujuan,Stanimirovi, Predrag S.,&Jin, Long.(2022).An improved DV-Hop algorithm for wireless sensor networks based on neural dynamics.NEUROCOMPUTING,491,172-185. |
| MLA | Liu, Jingping,et al."An improved DV-Hop algorithm for wireless sensor networks based on neural dynamics".NEUROCOMPUTING 491(2022):172-185. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。