Research of clustering protocol based on correlation of sensed data

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (5): 92-95.

• 网络、通信、安全 • Previous Articles Next Articles

Research of clustering protocol based on correlation of sensed data

ZHANG Qiang，ZHANG Huazhong，ZHOU Yingchun

College of Computer Science and Technology，Shandong University，Jinan 250101，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-02-11 Published:2011-02-11

基于数据相关的分簇协议研究

张强，张华忠，周迎春

山东大学计算机科学与技术学院，济南 250101

Abstract

Abstract: Considering the spatio-temporal correlation of sensed data，the clustering algorithm based on correlation of sensed data for wireless sensor network is proposed.According to the correlation of sensed data in CACD algorithm，sensor nodes with the same or similar data are divided into the same region.In cluster construction stage，the member nodes of a cluster come from the same region.There is only one cluster head communicating with base station in each region.In the intra-cluster communication，the continuously same data is transmitted only once.Because this algorithm takes account of reducing redundant data during transmission，it can prolong the lifetime of the whole network.

Key words: wireless sensor network, cluster, spatio-temporal correlation, redundant data

摘要： 针对传感器节点采集的数据具有时空相关性的特点，提出了一种基于数据相关的无线传感器网络分簇算法（CACD）。在CACD算法中，首先根据各个节点采集到的数据的相关性，将数据相同或相近的节点划分到一块相同的区域中。在簇形成阶段，令同一个簇的成员都来自同一个区域，并使每个区域最终只有一个簇首与基站通信。在簇内通信阶段，连续相同的数据只传输一次。算法大大减少了冗余数据的传输，从而延长了网络的生命周期。

关键词: 无线传感器网络, 簇, 时空相关性, 冗余数据

ZHANG Qiang，ZHANG Huazhong，ZHOU Yingchun. Research of clustering protocol based on correlation of sensed data[J]. Computer Engineering and Applications, 2011, 47(5): 92-95.

张强，张华忠，周迎春. 基于数据相关的分簇协议研究[J]. 计算机工程与应用, 2011, 47(5): 92-95.

[1]	LAN Hong, HUANG Min. Fusion of KNN Optimized Density Peaks and FCM Clustering Algorithm [J]. Computer Engineering and Applications, 2021, 57(9): 81-88.
[2]	GUO Xiaojing, SUI Haoda. Application of Improved YOLOv3 in Foreign Object Debris Target Detection on Airfield Pavement [J]. Computer Engineering and Applications, 2021, 57(8): 249-255.
[3]	SHENG Jianhui, FAN Yinting, XIA Minjie. Physical Layer Security Performance Analysis for Wireless Sensor Network [J]. Computer Engineering and Applications, 2021, 57(8): 91-95.
[4]	LI Li, JI Xinyuan, SONG Song. Prediction Model for Number of Software Defects in Loop [J]. Computer Engineering and Applications, 2021, 57(7): 158-163.
[5]	HUO Guangyu, ZHANG Yong, SUN Yanfeng, YIN Baocai. Research on Archive Data Intelligent Classification Based on Semantic [J]. Computer Engineering and Applications, 2021, 57(6): 247-253.
[6]	YANG Fang, YIN Xi, SI Jianhui, LIU Hongyuan, WANG Xue. Mathematical Expression Similarity Calculation Method Based on Focus Clustering [J]. Computer Engineering and Applications, 2021, 57(6): 88-93.
[7]	ZHAO Fan, ZHANG Lin, WEN Zhiquan, YANG Linlin, LIN Guangfeng. Direct and Efficient Natural Scene Chinese Character Approaching Spotting Method [J]. Computer Engineering and Applications, 2021, 57(6): 159-167.
[8]	PENG Qihui, XUAN Shibin, GAO Qing. Distribution Automatic Threshold Density Peak Clustering Algorithm [J]. Computer Engineering and Applications, 2021, 57(5): 71-78.
[9]	LI Yongzhen, LIAO Husheng. Multi-view Clustering via Graph Convolutional Neural Network [J]. Computer Engineering and Applications, 2021, 57(5): 115-122.
[10]	WANG Changlong, ZHANG Yuandong, MIAO Hong, YANG Yuheng. Application of Double Channel Convolutional Neural Network in Pumpkin Diseases Identification [J]. Computer Engineering and Applications, 2021, 57(5): 183-189.
[11]	HU Xiaomin, WANG Mingfeng, ZHANG Shourong, LI Min. New Differential Evolution with Particle Swarm Optimization Algorithm for Text Clustering [J]. Computer Engineering and Applications, 2021, 57(4): 61-67.
[12]	WANG Junling, LU Xinming. Video Key Frame Extraction Algorithm Based on Semantic Correlation [J]. Computer Engineering and Applications, 2021, 57(4): 192-198.
[13]	WANG Fuyin, ZHANG Desheng, ZHANG Xiao. Adaptive Density Peaks Clustering Algorithm Combining with Whale Optimization Algorithm [J]. Computer Engineering and Applications, 2021, 57(3): 94-102.
[14]	CHEN Junfeng, ZHENG Zhongtuan. Over-Sampling Method on Imbalanced Data Based on WKMeans and SMOTE [J]. Computer Engineering and Applications, 2021, 57(23): 106-112.
[15]	ZHANG Zhonglin, ZHAO Yu, YAN Guanghui. Natural Neighbor Density Extremum Clustering Algorithm [J]. Computer Engineering and Applications, 2021, 57(23): 200-210.

Research of clustering protocol based on correlation of sensed data

基于数据相关的分簇协议研究

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics