TY - GEN
T1 - Modelling and Optimization of DRX in Cellular IoT Networks
T2 - 2023 IEEE International Conference on Communications, ICC 2023
AU - Accurso, Nicholas
AU - Mastronarde, Nicholas
AU - Malandra, Filippo
N1 - Publisher Copyright: © 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Due to the exponential growth of endpoints in the Internet of Things (IoT), new protocols have been proposed to utilize cellular infrastructures, allowing a large amount of IoT devices to communicate through them. These novel protocols make up the Cellular IoT (C-IoT). In C-IoT, the energy efficiency of endpoints is essential in order to reduce both operational cost and required maintenance. One method of energy reduction is Discontinuous Reception (DRX). DRX allows a device's Radio Frequency (RF) circuitry to turn off for brief periods of time. While off, the device experiences a tradeoff between saving energy and an increase in expected latency, which can be tuned by how long the device spends asleep. In this paper, we model DRX as a Markov Decision Process (MDP). This MDP is solved using a dynamic programming approach and verified through simulation. Further, the energy-latency tradeoff is explored by varying the device's priority on either energy or network performance in addition to varying the traffic intensity.
AB - Due to the exponential growth of endpoints in the Internet of Things (IoT), new protocols have been proposed to utilize cellular infrastructures, allowing a large amount of IoT devices to communicate through them. These novel protocols make up the Cellular IoT (C-IoT). In C-IoT, the energy efficiency of endpoints is essential in order to reduce both operational cost and required maintenance. One method of energy reduction is Discontinuous Reception (DRX). DRX allows a device's Radio Frequency (RF) circuitry to turn off for brief periods of time. While off, the device experiences a tradeoff between saving energy and an increase in expected latency, which can be tuned by how long the device spends asleep. In this paper, we model DRX as a Markov Decision Process (MDP). This MDP is solved using a dynamic programming approach and verified through simulation. Further, the energy-latency tradeoff is explored by varying the device's priority on either energy or network performance in addition to varying the traffic intensity.
KW - Cellular IoT
KW - Constrained Devices
KW - Device Management
KW - Discontinuous reception (DRX)
KW - Efficient Communications and Networking
KW - Energy Efficient Devices
KW - Markov Decision Processes
UR - https://www.scopus.com/pages/publications/85178291231
U2 - 10.1109/ICC45041.2023.10279184
DO - 10.1109/ICC45041.2023.10279184
M3 - Conference contribution
T3 - IEEE International Conference on Communications
SP - 6169
EP - 6174
BT - ICC 2023 - IEEE International Conference on Communications
A2 - Zorzi, Michele
A2 - Tao, Meixia
A2 - Saad, Walid
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 28 May 2023 through 1 June 2023
ER -