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An Optimized Data Obtaining Strategy for Large-Scale Sensor Monitoring Networks
Author(s) -
Yan Wang,
Junlu Wang,
Fengtong Wang,
Ling Wang,
Wei Wei
Publication year - 2016
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2016/4262565
Subject(s) - computer science , wireless sensor network , cluster analysis , energy consumption , real time computing , scale (ratio) , data transmission , sensor node , distributed computing , computer network , data mining , key distribution in wireless sensor networks , wireless network , wireless , telecommunications , artificial intelligence , ecology , physics , quantum mechanics , biology
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.

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