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Mobile Information Systems
Volume 2017 (2017), Article ID 3206160, 17 pages
https://doi.org/10.1155/2017/3206160
Research Article

Comprehensive Optimization of Energy Consumption and Delay Performance for Green Communication in Internet of Things

1School of Information Science and Engineering, Central South University, Changsha 410083, China
2Key Laboratory of Hunan Province for Mobile Business Intelligence, Hunan University of Commerce, Changsha 410205, China
3Mobile E-Business Collaborative Innovation Center of Hunan Province, Hunan University of Commerce, Changsha 410205, China

Correspondence should be addressed to Chunhua Hu; moc.361@777auhnuhcuh and Anfeng Liu; nc.ude.usc.liam@uilgnefa

Received 16 December 2016; Accepted 22 February 2017; Published 23 March 2017

Academic Editor: Ning Zhang

Copyright © 2017 Jiaze Wang 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.

Abstract

Energy efficiency as well as fast data transmission is vital to green communications-based applications for Internet of Things (IoT). Wireless sensors, which constitute one of the important parts of IoT, adopt duty cycle operating mode to save energy. Although duty cycle operating mode will decrease the energy consumption of sensor nodes, it leads to a larger communication delay. In this paper, a utility-based adaptive duty cycle (UADC) routing algorithm is proposed to increase energy efficiency, reduce transmission delay, and keep long lifetime at the same time. First, UADC routing algorithm adopts a comprehensive performance evaluation function to evaluate the utility of choosing different relay nodes. Then it selects the node which maximizes the utility of the system to perform data relay. The utility function synthesizes comprehensive indexes like the reliability, energy consumption, and delay of the node. UADC routing algorithm adopts a high-duty cycle operating mode in the areas which have more remaining energy to decrease the delay. And a low-duty cycle operating mode in the energy-strained areas is adopted to ensure a long lifetime. The simulation results also prove the significant performances of our proposed algorithms.