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Wireless Communications and Mobile Computing
Volume 2018, Article ID 9715428, 23 pages
Research Article

Green Data Gathering under Delay Differentiated Services Constraint for Internet of Things

1School of Information Science and Engineering, Central South University, Changsha 410083, China
2School of Computer Science, National Huaqiao University, Quanzhou 362000, China
3School of Information Technology in Education, South China Normal University, Guangzhou 510631, China

Correspondence should be addressed to Anfeng Liu; nc.ude.usc.liam@uilgnefa

Received 22 August 2017; Revised 4 December 2017; Accepted 19 December 2017; Published 26 February 2018

Academic Editor: Zhi Liu

Copyright © 2018 Mingfeng Huang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Energy-efficient data gathering techniques play a crucial role in promoting the development of smart portable devices as well as smart sensor devices based Internet of Things (IoT). For data gathering, different applications require different delay constraints; therefore, a delay Differentiated Services based Data Routing (DSDR) scheme is creatively proposed to improve the delay differentiated services constraint that is missed from previous data gathering studies. The DSDR scheme has three advantages: first, DSDR greatly reduces transmission delay by establishing energy-efficient routing paths (E2RPs). Multiple E2RPs are established in different locations of the network to forward data, and the duty cycles of nodes on E2RPs are increased to 1, so the data is forwarded by E2RPs without the existence of sleeping delay, which greatly reduces transmission latency. Secondly, DSDR intelligently chooses transmission method according to data urgency: the direct-forwarding strategy is adopted for delay-sensitive data to ensure minimum end-to-end delay, while wait-forwarding method is adopted for delay-tolerant data to perform data fusion for reducing energy consumption. Finally, DSDR make full use of the residual energy and improve the effective energy utilization. The E2RPs are built in the region with adequate residual energy and they are periodically rotated to equalize the energy consumption of the network. A comprehensive performance analysis demonstrates that the DSDR scheme has obvious advantages in improving network performance compared to previous studies: it reduces transmission latency of delay-sensitive data by 44.31%, reduces transmission latency of delay-tolerant data by 25.65%, and improves network energy utilization by 30.61%, while also guaranteeing the network lifetime is not lower than previous studies.