NDLI: Adaptive Sampling Algorithm with Endocrine Regulation Mechanism for Wireless Sensor Network

Content Provider	IEEE Xplore Digital Library
Author	Jiankai Zhang Lihong Ren Yongsheng Ding Kuangrong Hao
Copyright Year	2015
Description	Author affiliation: Eng. Res. Center of Digitized Textile & Apparel Technol., Donghua Univ., Shanghai, China (Jiankai Zhang; Lihong Ren; Yongsheng Ding; Kuangrong Hao)
Abstract	Studies in Wireless sensor network (WSN) have been extensively focused on developing different medium access control (MAC) and routing protocols instead of ignoring that on data acquisition and processing. Unfortunately, setting the sampling frequency of nodes in WSN will unreasonably cause low precision, and even result in premature failure of the network. Aimed at solving this problem, an adaptive sampling algorithm based on endocrine regulation mechanism in WSN is proposed. The algorithm uses hormone information to control the nodes in working state or resting state, and adjusts collecting frequency dynamically. When the targets change slowly, the nodes send inhibitory hormone to reduce the collecting frequency and extend lifetime of the network. Conversely, while the targets change rapidly, the nodes send trophic hormone to increase the sampling frequency and ensure the sampling accuracy. Finally, the results of the simulation experiments show that the algorithm can effectively prolong the lifetime of network without losing sampling accuracy.
Starting Page	502
Ending Page	507
File Size	324220
Page Count	6
File Format	PDF
e-ISBN	9781467393232
DOI	10.1109/ISKE.2015.66
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-24
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Temperature measurement adaptive sampling Wireless sensor networks Energy consumption WSN Glands Biochemistry endocrine regulation Monitoring network lifetime
Content Type	Text
Resource Type	Article

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