TY - JOUR
T1 - Routing for crowd management in smart cities
T2 - A deep reinforcement learning perspective
AU - Zhao, Lei
AU - Wang, Jiadai
AU - Liu, Jiajia
AU - Kato, Nei
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China (61771374, 61771373, and 61601357), in part by China 111 Project (B16037), and in part by the Fundamental Research Fund for the Central Universities (JB171501, JB181506, JB181507, and JB181508).
Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - The concept of smart city has been flourishing based on the prosperous development of various advanced technologies: Mobile edge computing (MEC), ultra-dense networking, and software defined networking. However, it becomes increasingly complicated to design routing strategies to meet the stringent and ever changing network requirements due to the dynamic distribution of the crowd in different sectors of smart cities. To alleviate the network congestion and balance the network load for supporting smart city services with dramatic disparities, we design a deep-reinforcement-learning-based smart routing algorithm to make the distributed computing and communication infrastructure thoroughly viable while simultaneously satisfying the latency constraints of service requests from the crowd. Besides the proposed algorithm, extensive numerical results are also presented to validate its efficacy.
AB - The concept of smart city has been flourishing based on the prosperous development of various advanced technologies: Mobile edge computing (MEC), ultra-dense networking, and software defined networking. However, it becomes increasingly complicated to design routing strategies to meet the stringent and ever changing network requirements due to the dynamic distribution of the crowd in different sectors of smart cities. To alleviate the network congestion and balance the network load for supporting smart city services with dramatic disparities, we design a deep-reinforcement-learning-based smart routing algorithm to make the distributed computing and communication infrastructure thoroughly viable while simultaneously satisfying the latency constraints of service requests from the crowd. Besides the proposed algorithm, extensive numerical results are also presented to validate its efficacy.
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U2 - 10.1109/MCOM.2019.1800603
DO - 10.1109/MCOM.2019.1800603
M3 - Review article
AN - SCOPUS:85065435968
SN - 0163-6804
VL - 57
SP - 88
EP - 93
JO - IEEE Communications Magazine
JF - IEEE Communications Magazine
IS - 4
M1 - 8703471
ER -
