Optimal Edge Resource Allocation in IoT-Based Smart Cities

Lei Zhao; Jiadai Wang; Jiajia Liu; Nei Kato

doi:10.1109/MNET.2019.1800221

Optimal Edge Resource Allocation in IoT-Based Smart Cities

Lei Zhao, Jiadai Wang, Jiajia Liu, Nei Kato

Research output: Contribution to journal › Article › peer-review

127 Scopus citations

Abstract

With IoT-based smart cities, massive heterogeneous IoT devices are running diverse advanced services for unprecedented intelligence and efficiency in various domains of city life. Given the exponentially growing number of IoT devices and the large number of smart city services as well as their different QoS requirements, it has been a big challenge for servers to optimally allocate limited resources to all hosted applications for satisfactory performance. Note that by pushing the computing and storage resources to the proximity of end IoT devices, and deploying applications in distributed edge servers, edge computing technology appears to be a promising solution for this challenge. Toward this, we study in this article how to allocate edge resources for average service response time minimization. Besides the proposed algorithms, extensive numerical results are also presented to validate their efficacy.

Original language	English
Article number	8675169
Pages (from-to)	30-35
Number of pages	6
Journal	IEEE Network
Volume	33
Issue number	2
DOIs	https://doi.org/10.1109/MNET.2019.1800221
State	Published - 1 Mar 2019
Externally published	Yes

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10.1109/MNET.2019.1800221

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abstract = "With IoT-based smart cities, massive heterogeneous IoT devices are running diverse advanced services for unprecedented intelligence and efficiency in various domains of city life. Given the exponentially growing number of IoT devices and the large number of smart city services as well as their different QoS requirements, it has been a big challenge for servers to optimally allocate limited resources to all hosted applications for satisfactory performance. Note that by pushing the computing and storage resources to the proximity of end IoT devices, and deploying applications in distributed edge servers, edge computing technology appears to be a promising solution for this challenge. Toward this, we study in this article how to allocate edge resources for average service response time minimization. Besides the proposed algorithms, extensive numerical results are also presented to validate their efficacy.",

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AB - With IoT-based smart cities, massive heterogeneous IoT devices are running diverse advanced services for unprecedented intelligence and efficiency in various domains of city life. Given the exponentially growing number of IoT devices and the large number of smart city services as well as their different QoS requirements, it has been a big challenge for servers to optimally allocate limited resources to all hosted applications for satisfactory performance. Note that by pushing the computing and storage resources to the proximity of end IoT devices, and deploying applications in distributed edge servers, edge computing technology appears to be a promising solution for this challenge. Toward this, we study in this article how to allocate edge resources for average service response time minimization. Besides the proposed algorithms, extensive numerical results are also presented to validate their efficacy.

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Optimal Edge Resource Allocation in IoT-Based Smart Cities

Abstract

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