EURASIP Journal on Wireless Communications and Networking (Aug 2020)

Bi-adjusting duty cycle for green communications in wireless sensor networks

  • Guopeng Li,
  • Fufang Li,
  • Tian Wang,
  • Jinsong Gui,
  • Shaobo Zhang

DOI
https://doi.org/10.1186/s13638-020-01767-5
Journal volume & issue
Vol. 2020, no. 1
pp. 1 – 55

Abstract

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Abstract Green communications is a challenging issue for communications and networking. In order to save energy, nodes of the wireless sensor networks (WSNs) usually adopt the low duty cycle mode which brings a large delay to the event detection and data transmission to the sink and deteriorates the network’s timely processing of the event. In this paper, bi-adjusting duty cycle schedule (BADCS) scheme is proposed to reduce event detection latency as well as data routing delay for low duty cycle wireless sensor networks. BADCS scheme consists mainly of two duty cycle adjustment algorithms: (a) active slot asynchronous adjustment algorithm for nodes in the same sensing area; (b) the continuous adjustment algorithm for two adjacent nodes on the routing path with one active slot interval. Specifically, the operations are 2-fold. First, perform asynchronous operations on the active slots of the nodes in the same sensing area, so that the active slots of the nodes in the same sensing area are distributed as evenly as possible without overlapping. In this way, it is possible to reduce the latency by the time the event is perceived after its occurrence. Secondly, active slots of the nodes on the routing path are adjusted to be with pipeline style, so that when the nodes receive the data packet, they can route through the continuous active slots, thus greatly reducing the delay of data routing. Two adjustment algorithms of active slot are given in detail in this paper. The performance of BADCS mode is discussed in detail, and its performance is better than the previous strategy. Comprehensive experiments are conducted, and the results demonstrate that the proposed BADCS scheme significantly improves event detection performance in terms of detection latency, detection probability, and routing delay. Detection delay and routing delay are reduced as high as 3.91% and 56.22% respectively.

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