Achieving Efficient Data Collection in Heterogeneous Sensing WSNs | Zendy

Xingyu He | Zendy; Shuai Liu | Zendy; Guisong Yang | Zendy; Naixue Xiong | Zendy

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Achieving Efficient Data Collection in Heterogeneous Sensing WSNs

Author(s) -

Xingyu He,

Shuai Liu,

Guisong Yang,

Naixue Xiong

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2876552

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Nowadays, many applications of heterogeneous sensing wireless sensor networks (WSNs) employ more than one type of sensor nodes to acquire a variety of sensing data sources, which brings the dynamic diversity of generated data amount among different network regions. To adapt to that diversity and improve the data gathering efficiency, this paper first analyzes and models the diversity of generated data amount according to the diversities of data generating rate and operating mode among nodes and then proposes a data gathering scheme with a mobile sink. In the scheme, the movement trajectory for the mobile sink is determined by using Hilbert space-filling curve and adjusted dynamically based on the change of data amounts generated in different network regions. A hybrid routing method is also proposed to further reduce the network energy consumption. The simulation results show that the proposed data gathering scheme not only has effective performances on a promoting packet delivery ratio and reducing average energy consumption rate but also has great adaptability to the heterogeneous sensing WSNs.

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