Next Article in Journal
Underground Microseismic Event Monitoring and Localization within Sensor Networks
Previous Article in Journal
Movement Path Data Generation from Wi-Fi Fingerprints for Recurrent Neural Networks
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Sink-Type-Dependent Data-Gathering Frameworks in Wireless Sensor Networks: A Comparative Study

Department of Computer Engineering, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju 61452, Korea
*
Author to whom correspondence should be addressed.
Sensors 2021, 21(8), 2829; https://doi.org/10.3390/s21082829
Submission received: 23 February 2021 / Revised: 13 April 2021 / Accepted: 14 April 2021 / Published: 16 April 2021
(This article belongs to the Section Sensor Networks)

Abstract

Owing to automation trends, research on wireless sensor networks (WSNs) has become prevalent. In addition to static sinks, ground and aerial mobile sinks have become popular for data gathering because of the implementation of WSNs in hard-to-reach or infrastructure-less areas. Consequently, several data-gathering mechanisms in WSNs have been investigated, and the sink type plays a major role in energy consumption and other quality of service parameters, such as packet delivery ratio, delay, and throughput. However, the data-gathering schemes based on different sink types in WSNs have not been investigated previously. This paper reviews such data-gathering frameworks based on three different types of sinks (i.e., static, ground mobile, and aerial mobile sinks), analyzing the data-gathering frameworks both qualitatively and quantitatively. First, we examine the frameworks by discussing their working principles, advantages, and limitations, followed by a qualitative comparative study based on their main ideas, optimization criteria, and performance evaluation parameters. Next, we present a simulation-based quantitative comparison of three representative data-gathering schemes, one from each category. Simulation results are shown in terms of energy efficiency, number of dead nodes, number of exchanged control packets, and packet drop ratio. Finally, lessons learned from the investigation and recommendations made are summarized.
Keywords: wireless sensor network; static sink; mobile sink; energy efficiency; routing protocol; data gathering; aerial sink; unmanned aerial vehicle; base station wireless sensor network; static sink; mobile sink; energy efficiency; routing protocol; data gathering; aerial sink; unmanned aerial vehicle; base station

Share and Cite

MDPI and ACS Style

Nazib, R.A.; Moh, S. Sink-Type-Dependent Data-Gathering Frameworks in Wireless Sensor Networks: A Comparative Study. Sensors 2021, 21, 2829. https://doi.org/10.3390/s21082829

AMA Style

Nazib RA, Moh S. Sink-Type-Dependent Data-Gathering Frameworks in Wireless Sensor Networks: A Comparative Study. Sensors. 2021; 21(8):2829. https://doi.org/10.3390/s21082829

Chicago/Turabian Style

Nazib, Rezoan Ahmed, and Sangman Moh. 2021. "Sink-Type-Dependent Data-Gathering Frameworks in Wireless Sensor Networks: A Comparative Study" Sensors 21, no. 8: 2829. https://doi.org/10.3390/s21082829

APA Style

Nazib, R. A., & Moh, S. (2021). Sink-Type-Dependent Data-Gathering Frameworks in Wireless Sensor Networks: A Comparative Study. Sensors, 21(8), 2829. https://doi.org/10.3390/s21082829

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop