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Optimal Distributed MQTT Broker and Services Placement for SDN-Edge Based Smart City Architecture
A smart city is an urban area that collects data from various devices to effectively manage urban resources. The smart city IoT infrastructure connects numerous devices to an Internet-protocol-based low-power wireless network, shares massive amounts of data, and facilitates the development of new se...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9101202/ https://www.ncbi.nlm.nih.gov/pubmed/35591120 http://dx.doi.org/10.3390/s22093431 |
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author | Fawwaz, Dzaky Zakiyal Chung, Sang-Hwa Ahn, Chang-Woo Kim, Won-Suk |
author_facet | Fawwaz, Dzaky Zakiyal Chung, Sang-Hwa Ahn, Chang-Woo Kim, Won-Suk |
author_sort | Fawwaz, Dzaky Zakiyal |
collection | PubMed |
description | A smart city is an urban area that collects data from various devices to effectively manage urban resources. The smart city IoT infrastructure connects numerous devices to an Internet-protocol-based low-power wireless network, shares massive amounts of data, and facilitates the development of new services. Message queuing telemetry transport (MQTT), a lightweight exchange protocol for the IoT environment, uses a publish and subscribe structure via a centralized broker to share data. The extent of edge computing provides distributed and closer resources to the data source while maintaining low transmission costs. However, a centralized MQTT data broker is unsuitable for distributed edge resources and could result in high latency, traffic, and bottleneck risk. Therefore, we proposed a distributed MQTT broker optimized architecture. A distributed MQTT broker for edge resources could reduce network traffic and data delivery latency by only managing consumed topics in the network. We formulate an integer non-linear program to optimize container placement and avoid wasting edge computing resources. We compared our proposed architecture to the existing distributed MQTT middleware architecture with greedy and random container placement through extensive simulation. Our methods show better performance in lowering deployment failure ratio, power consumption, network usage, and synchronization overhead. |
format | Online Article Text |
id | pubmed-9101202 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91012022022-05-14 Optimal Distributed MQTT Broker and Services Placement for SDN-Edge Based Smart City Architecture Fawwaz, Dzaky Zakiyal Chung, Sang-Hwa Ahn, Chang-Woo Kim, Won-Suk Sensors (Basel) Article A smart city is an urban area that collects data from various devices to effectively manage urban resources. The smart city IoT infrastructure connects numerous devices to an Internet-protocol-based low-power wireless network, shares massive amounts of data, and facilitates the development of new services. Message queuing telemetry transport (MQTT), a lightweight exchange protocol for the IoT environment, uses a publish and subscribe structure via a centralized broker to share data. The extent of edge computing provides distributed and closer resources to the data source while maintaining low transmission costs. However, a centralized MQTT data broker is unsuitable for distributed edge resources and could result in high latency, traffic, and bottleneck risk. Therefore, we proposed a distributed MQTT broker optimized architecture. A distributed MQTT broker for edge resources could reduce network traffic and data delivery latency by only managing consumed topics in the network. We formulate an integer non-linear program to optimize container placement and avoid wasting edge computing resources. We compared our proposed architecture to the existing distributed MQTT middleware architecture with greedy and random container placement through extensive simulation. Our methods show better performance in lowering deployment failure ratio, power consumption, network usage, and synchronization overhead. MDPI 2022-04-30 /pmc/articles/PMC9101202/ /pubmed/35591120 http://dx.doi.org/10.3390/s22093431 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Fawwaz, Dzaky Zakiyal Chung, Sang-Hwa Ahn, Chang-Woo Kim, Won-Suk Optimal Distributed MQTT Broker and Services Placement for SDN-Edge Based Smart City Architecture |
title | Optimal Distributed MQTT Broker and Services Placement for SDN-Edge Based Smart City Architecture |
title_full | Optimal Distributed MQTT Broker and Services Placement for SDN-Edge Based Smart City Architecture |
title_fullStr | Optimal Distributed MQTT Broker and Services Placement for SDN-Edge Based Smart City Architecture |
title_full_unstemmed | Optimal Distributed MQTT Broker and Services Placement for SDN-Edge Based Smart City Architecture |
title_short | Optimal Distributed MQTT Broker and Services Placement for SDN-Edge Based Smart City Architecture |
title_sort | optimal distributed mqtt broker and services placement for sdn-edge based smart city architecture |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9101202/ https://www.ncbi.nlm.nih.gov/pubmed/35591120 http://dx.doi.org/10.3390/s22093431 |
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