TY - JOUR
T1 - CG-E2S2
T2 - Consistency-guaranteed and energy-efficient sleep scheduling algorithm with data aggregation for IoT
AU - Ko, Haneul
AU - Lee, Jaewook
AU - Pack, Sangheon
N1 - Funding Information:
In this paper, we propose a consistency-guaranteed and energy efficient sleep scheduling algorithm (CG-E2S2) with data aggregation. In CG-E2S2, the optimal sleep duration and aggregation duration are jointly determined by means of a Markov decision process (MDP) with consideration of the energy efficiency of IoT devices, data traffic in networks, and data consistency. The evaluation results demonstrate that CG-E2S2 with the optimal policy outperforms the comparison schemes in terms of energy efficiency, data traffic volume, and data consistency. In future works, we will investigate how to implement and deploy the proposed algorithm to cognitive wireless sensor networks. Haneul Ko received the B.S. and Ph.D. degrees from Korea University, Seoul, Korea, in 2011 and 2016, respectively, both in School of Electrical Engineering. He is currently Postdoctoral Researcher in the mobile network and communications laboratory, Korea University, Seoul, Korea. His research interests include 5G networks, mobility management, mobile cloud computing, SDN/NFV, and Future Internet. Jaewook Lee received the B.S. degree from Korea University, Seoul, Korea, in 2014. He is currently an M.S. and Ph.D. integrated course student in School of Electrical Engineering, Korea University, Seoul, Korea. His research interests include 5G networks, mobility management, and SDN/NFV. Sangheon Pack received the B.S. and Ph.D. degrees from Seoul National University, Seoul, Korea, in 2000 and 2005, respectively, both in computer engineering. In 2007, he joined the faculty of Korea University, Seoul, Korea. From 2005 to 2006, he was a Postdoctoral Fellow with the Broadband Communications Research Group, University of Waterloo, Waterloo, ON, Canada. He was the recipient of KICS (Korean Institute of Communications and Information Sciences) Haedong Young Scholar Award 2013, IEEE ComSoc APB Outstanding Young Researcher Award in 2009, LG Yonam Foundation Overseas Research Professor Program in 2012, and Student Travel Grant Award at the IFIP Personal Wireless Conference (PWC) 2003. From 2002 to 2005, he was a recipient of the Korea Foundation for Advanced Studies Computer Science and Information Technology Scholarship. He was a publication co-chair of IEEE INFOCOM 2014, a co-chair of IEEE VTC 2010-Fall transportation track, a co-chair of IEEE WCSP 2013 wireless networking symposium, a TPC vice-chair of ICOIN 2013, and a publicity co-chair of IEEE SECON 2012. He is an editor of Journal of Communications Networks (JCN) and a senior member of the IEEE. His research interests include Future Internet, SDN/ICN/DTN, mobility management, mobile cloud networking, multimedia networking, and vehicular networks.
Funding Information:
This work was supported in part by National Research Foundation of Korea Grant funded by the Korean Government (NRF-2014R1A2A1A12066986) and in part by IITP grant funded by the Korea government (MSIT) (No. B0190-16-2012, Global SDN/NFV Open-Source Software Core Module/Function Development).
Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2019/3
Y1 - 2019/3
N2 - In data acquisition (DAQ)-based services of Internet of things (IoT), IoT devices sense and transmit data to the application server through IoT gateway (GW). Due to the energy limitation of IoT devices, it is important to increase their energy efficiency. Further, when data from a very large number of IoT devices is individually transmitted, the data traffic volume can be significant. To resolve these issues, IoT devices and IoT GW can use sleep mode and data aggregation, respectively. However, when the IoT devices are in sleep mode for a long time and/or data are aggregated in IoT GW for a long time without any transmissions, data can become inconsistent. In this paper, we propose a consistency-guaranteed and energy efficient sleep scheduling algorithm (CG-E2S2) with data aggregation. In CG-E2S2, the optimal sleep duration of IoT devices and aggregation duration in IoT GW are jointly determined by means of a Markov decision process (MDP) with the consideration of energy efficiency of IoT devices, data traffic in networks, and data consistency. The evaluation results demonstrate that CG-E2S2 with the optimal policy outperforms the comparison schemes in terms of energy efficiency, data traffic volume, and data consistency.
AB - In data acquisition (DAQ)-based services of Internet of things (IoT), IoT devices sense and transmit data to the application server through IoT gateway (GW). Due to the energy limitation of IoT devices, it is important to increase their energy efficiency. Further, when data from a very large number of IoT devices is individually transmitted, the data traffic volume can be significant. To resolve these issues, IoT devices and IoT GW can use sleep mode and data aggregation, respectively. However, when the IoT devices are in sleep mode for a long time and/or data are aggregated in IoT GW for a long time without any transmissions, data can become inconsistent. In this paper, we propose a consistency-guaranteed and energy efficient sleep scheduling algorithm (CG-E2S2) with data aggregation. In CG-E2S2, the optimal sleep duration of IoT devices and aggregation duration in IoT GW are jointly determined by means of a Markov decision process (MDP) with the consideration of energy efficiency of IoT devices, data traffic in networks, and data consistency. The evaluation results demonstrate that CG-E2S2 with the optimal policy outperforms the comparison schemes in terms of energy efficiency, data traffic volume, and data consistency.
KW - Data aggregation
KW - Data consistency
KW - Energy
KW - Internet of things (IoT)
KW - Markov decision process (MDP)
KW - Sleep
UR - http://www.scopus.com/inward/record.url?scp=85029724801&partnerID=8YFLogxK
U2 - 10.1016/j.future.2017.08.040
DO - 10.1016/j.future.2017.08.040
M3 - Article
AN - SCOPUS:85029724801
SN - 0167-739X
VL - 92
SP - 1093
EP - 1102
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
ER -
