Dynamic scheming the duty cycle in the opportunistic routing sensor network. (10th September 2017)

• Record Type: Journal Article
• Authors: Niu, Bingxin; Qi, Heng; Li, Keqiu; Liu, Xiulong; Xue, Weilian
• Other Names: Lengauer Christian guestEditor.; Bolten Matthias guestEditor.; Falgout Robert guestEditor.; Schenk Olaf guestEditor.; Zhou Xiaobo guestEditor.; Zhao Laiping guestEditor.
• Is Part Of: Concurrency and computation. Volume 29:Number 17(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-09-10
• Subjects: Duty cycle -- end‐to‐end delay -- WSNs; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4196
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: In wireless sensor networks, a lot of applications need the sensed information be transmitted to the sink node within a predefined time threshold. So end‐to‐end delay is an important performance metric in wireless sensor networks. Opportunistic routing protocols have been proposed to reduce the waiting delay. In the duty cycle networks, increasing the duty cycle ratio can also reduce the end‐to‐end delay. However, this method will consume more energy. It is obvious that there exists a trade‐off between delay and energy consumption. So adjusting the duty cycle ratio of each node can investigate this trade‐off. To the best of our knowledge, no existing work takes both of end‐to‐end delay and energy efficiency into consideration in the opportunistic routing networks. In this paper, we want to minimize the whole energy consumption while guaranteeing the expected end‐to‐end delay between the source nodes and the sink node is below the given threshold. To deal with this problem, we propose a dynamic duty cycle scheme which can significantly reduce the energy consumption and guarantee the expected end‐to‐end delay demand in the opportunistic routing network. To be specific, firstly, we formulate a new metric with the wake‐up time slots as the variable to measure the end‐to‐end delay. Secondly, for simplifying the complex problem, we decompose it into a set of single‐hop delay guarantee problems. Feedback controller has been used to solve the problem. We also analyze the influence of the multiple receivers in the same forwarding set. Finally, we conduct extensive simulations to evaluate the performance of the proposed algorithm. The experimental results reveal that our scheme can guarantee the delay requirement, meanwhile, significantly reduce the energy consumption compared with prior schemes.