TY - JOUR
T1 - Internet of Things Session Management over LTE - Balancing Signal Load, Power, and Delay
AU - Wang, Xiaoli
AU - Sheng, Ming Jye
AU - Lou, Yuan Yao
AU - Shih, Yuan Yao
AU - Chiang, Mung
N1 - Funding Information:
This work was supported in part by the National Science Foundation (NSF) under NSF Grant CNS-1456847
Publisher Copyright:
© 2014 IEEE.
PY - 2016/6
Y1 - 2016/6
N2 - To efficiently support and manage massive number of Internet of Things (IoT) short and bursty sessions, current long-term evolution (LTE) system needs to reduce signal load generated by IoT session setup/synchronization, while balancing the system performance, such as UE power consumption and delays to time-sensitive traffic. In LTE, radio resource control (RRC) and discontinuous reception (DRX) affect power consumption, signal load, and delay. We provide a session management methodology suitable for IoT traffic over LTE. Our analysis starts with a Markov chain analysis of the impact of DRX parameters. This is followed by an optimal uplink scheduler design and an IoT-aware adaptive DRX algorithm at the client, both of which modulate the tradeoff among signal load, delay, and power consumption. Scalability is also considered by providing a high-priority clustering-based adaptive DRX algorithm at eNB. Simulation results show that for packets with 0.1 s delay, our scheduler outperforms 'Tx now' (and 'Wait Till Deadline') by 50% (and 30%) in power saving and by 60% (and 15%) in signal saving. With knowledge of the traffic pattern, IoT-aware adaptive DRX can further reduce signal load by 25%, especially for delay-sensitive traffic.
AB - To efficiently support and manage massive number of Internet of Things (IoT) short and bursty sessions, current long-term evolution (LTE) system needs to reduce signal load generated by IoT session setup/synchronization, while balancing the system performance, such as UE power consumption and delays to time-sensitive traffic. In LTE, radio resource control (RRC) and discontinuous reception (DRX) affect power consumption, signal load, and delay. We provide a session management methodology suitable for IoT traffic over LTE. Our analysis starts with a Markov chain analysis of the impact of DRX parameters. This is followed by an optimal uplink scheduler design and an IoT-aware adaptive DRX algorithm at the client, both of which modulate the tradeoff among signal load, delay, and power consumption. Scalability is also considered by providing a high-priority clustering-based adaptive DRX algorithm at eNB. Simulation results show that for packets with 0.1 s delay, our scheduler outperforms 'Tx now' (and 'Wait Till Deadline') by 50% (and 30%) in power saving and by 60% (and 15%) in signal saving. With knowledge of the traffic pattern, IoT-aware adaptive DRX can further reduce signal load by 25%, especially for delay-sensitive traffic.
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U2 - 10.1109/JIOT.2015.2497230
DO - 10.1109/JIOT.2015.2497230
M3 - Article
AN - SCOPUS:84969756513
SN - 2327-4662
VL - 3
SP - 339
EP - 353
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 3
M1 - 7314871
ER -