Adaptive Sampling Algorithm with Endocrine Regulation Mechanism for Wireless Sensor Network

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.