An Optimized Data Obtaining Strategy for Large-Scale Sensor Monitoring Networks

被引:1
|
作者
Wang, Yan [1 ,2 ]
Wang, Junlu [1 ]
Wang, Fengtong [1 ]
Wang, Ling [1 ]
Wei, Wei [3 ,4 ]
机构
[1] Liaoning Univ, Sch Informat, Shenyang 110036, Peoples R China
[2] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110819, Peoples R China
[3] Xian Univ Technol, Sch Comp Sci & Engn, Xian 710048, Peoples R China
[4] Xi An Jiao Tong Univ, State Key Lab Strength & Vibrat Mech Struct, Xian 710049, Peoples R China
基金
中国国家自然科学基金; 高等学校博士学科点专项科研基金;
关键词
D O I
10.1155/2016/4262565
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As the technology of the Internet of Things (IoT) becomes more widely used in large-scale monitoring networks, this paper proposes an optimized obtaining strategy (OFS) for large-scale sensor monitoring networks. First, because of the large-scale features of sensor node network, this paper proposes a large-scale monitoring network area clustering optimization strategy. Second, based on the characteristics of regular changes in the sensed data in large-scale monitoring networks, this paper proposes a strategy for acquiring sensor data based on an adaptive frequency conversion. The OFS optimization strategy can prolong network lifetime, reduce the transmission bandwidth resources, and reduce average energy consumption of the cluster head and network energy consumption.
引用
收藏
页数:10
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