A collision-analysis-based energy-efficient routing protocol in 3D underwater acoustic sensor networks

Chun Hao Yang, Kuo-Feng Ssu, Chun Lin Yang

研究成果: Article同行評審

9 引文 斯高帕斯(Scopus)

摘要

In recent years, three-dimensional (3D) underwater sensor networks (USNs) have received substantial attention as a promising tool for target tracking and remote monitoring under the seas. Energy consumption is crucial in USNs because it is nearly impossible to recharge the batteries of the sensors. Given the properties of intermittent link connectivity in USNs, the existing message-based and synchronization-based approaches cannot meet packet delivery requirements. In this paper, an analysis for the probability of collisions between any two transmissions in USNs is presented, in which the analyzed collision rate corresponds to the simulation and is demonstrated to be relaxed with a sufficient data processing rate in underwater networks. Based on this result, a tailored delay-aware energy-efficient routing protocol (DEEP) is proposed. DEEP is composed of an energy model with realistic parameters in which the available 3-dB bandwidth is derived with respect to the distances between nodes. DEEP involves an adaptable forwarding node selection mechanism, which incorporates the concept of energy efficiency and further reduces the collision rate. Simulations show that DEEP expends less energy for successful packet delivery compared with previous studies. Benefits from the higher bandwidth in USNs, DEEP reduces the collision occurrences and elevates the packet delivery ratio with less end-to-end delay time especially when the network conditions are unfavorable. These results confirm that DEEP effectively handles the challenges.

原文English
頁(從 - 到)25-35
頁數11
期刊Computer Communications
66
DOIs
出版狀態Published - 2015 七月 15

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

指紋 深入研究「A collision-analysis-based energy-efficient routing protocol in 3D underwater acoustic sensor networks」主題。共同形成了獨特的指紋。

引用此