Cited by 126Software-Defined Networks and 5GIoT and Edge/Fog ComputingNetwork Traffic and Congestion Control

Routing for Crowd Management in Smart Cities: A Deep Reinforcement Learning Perspective

Zhao, Lei, Wang, Jiadai, Liu, Jiajia, Kato, Nei·2019·IEEE Communications Magazine

Abstract

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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Crossref · 10.1109/mcom.2019.1800603

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16 of 16 references verified0 citation errors · 0 not checkable

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Authors
Zhao, L., Wang, J., Liu, J., & Kato, N.
Affiliations
  • Xidian University (CN)
  • Tohoku University (JP)
Venue
IEEE Communications Magazine
Published
2019-04
Volume
57
Issue
4
Pages
88-93
ISSN
  • 0163-6804 (ISSN-L)
  • 1558-1896
OpenAlex
W2943466984
Cited by
126
References
16
Citations by year
2026: 3 · 2025: 6 · 2024: 16 · 2023: 15 · 2022: 18 · 2021: 24 · 2020: 34 · 2019: 10
FWCI
11.77
Type
journal article
Language
en
Open access
closed
Locations
IEEE Communications Magazine (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Computer Science › Computer Networks and Communications › Network Traffic and Congestion Control
Keywords
crowd management, smart cities, deep reinforcement learning, smart routing, network congestion, load balancing, delay constraints, mobile edge computing, software-defined networking

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