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Lookup NU author(s): Rohin Gillgallon, Dr Giacomo BergamiORCiD, Professor Graham MorganORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Modern smart cities are comprised of multiple sensors, all with their own collection of communicating devices transmitting data towards cloud data centres for analysis. Smart cities have limited bandwidth resources, which, if not managed correctly, can lead to network bottlenecks. These bottlenecks are commonly addressed through bottleneck mitigation strategies and load balancing algorithms, which aim to maximise the throughput of a smart city’s network infrastructure. Network simulators are a crucial tool for developing and testing bottleneck mitigation and load balancing techniques before deployment in real systems; however, many network simulators are developed as single-purpose tools, aiming to simulate a particular subset of an overarching use case. Such tools are therefore unable to model a real-world smart city infrastructure, which receives communications across a wide range of scenarios and from a wide variety of devices. This paper surveys the current state-of-the-art for network simulation tools, modern bottleneck mitigation strategies and load balancing techniques, evaluating each in terms of its suitability for smart cities and smart city simulation. This survey finds there is a lack of current network simulation tools up to the task of modelling smart city infrastructure and found no such simulation tools capable of modelling both smart city infrastructure and implementing the state-of-the-art bottleneck mitigation and load balancing strategies outlined within this work, highlighting this as a significant gap in current research before providing future work suggestions, including a federated approach for future simulation tools.
Author(s): Gillgallon R, Bergami G, Morgan G
Publication type: Article
Publication status: Published
Journal: Applied Sciences
Year: 2025
Volume: 15
Issue: 20
Print publication date: 15/10/2025
Online publication date: 11/10/2025
Acceptance date: 09/10/2025
Date deposited: 11/10/2025
ISSN (electronic): 2076-3417
Publisher: MDPI
URL: https://doi.org/10.3390/app152010920
DOI: 10.3390/app152010920
Data Access Statement: Not applicable
Notes: This article belongs to the Special Issue Advanced Internet of Things Ecosystems: Architectures, Intelligence, and Communication Innovations.
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