2020
DOI: 10.1016/j.future.2020.01.036
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Classification of optimization problems in fog computing

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Cited by 87 publications
(44 citation statements)
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References 256 publications
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“…Both R5 and R6 relate to other system goals than data protection. Such other goals in cloud-based systems could include energy consumption reduction [27], cost reduction [28], latency minimization [29], and many others [30]. In this paper, we focus on the minimization of costs and the maximization of the available functionality as two representative examples, but the work presented here could be extended to address other goals as well.…”
Section: Requirementsmentioning
confidence: 99%
“…Both R5 and R6 relate to other system goals than data protection. Such other goals in cloud-based systems could include energy consumption reduction [27], cost reduction [28], latency minimization [29], and many others [30]. In this paper, we focus on the minimization of costs and the maximization of the available functionality as two representative examples, but the work presented here could be extended to address other goals as well.…”
Section: Requirementsmentioning
confidence: 99%
“…This layer has the function of allowing network access, conveniently and properly across all the shared resources in the IoT network. The storage and services areas of the IoT network requires heavy duty and is performed by the cloud layer [25].…”
Section: Fog Computing Architecturementioning
confidence: 99%
“…In recent years, Fog computing (FC) shows that it is a strong distributed computing environment that extends Cloud computing to the edge of networks [1]. The most crucial advantage of FC compared to cloud computing is the proximity to end‐devices such as sensors, actuators, smart cameras, smartphones, and Internet‐of‐Things (IoT) devices [2]. Resource management in FC can be performed using various FDs with many constraints to meet the computational demand of IoT‐enabled systems in a distributed manner [3].…”
Section: Introductionmentioning
confidence: 99%