2019
DOI: 10.1002/dac.3926
|View full text |Cite
|
Sign up to set email alerts
|

Elucidating the challenges for the praxis of fog computing: An aspect‐based study

Abstract: Summary The evolutionary advancements in the field of technology have led to the instigation of cloud computing. The Internet of Things paradigm stimulated the extensive use of sensors distributed across the network edges. The cloud datacenters are assigned the responsibility for processing the collected sensor data. Recently, fog computing was conceptuated as a solution for the overwhelmed narrow bandwidth. The fog acts as a complementary layer that interplays with the cloud and edge computing layers, for pro… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
4
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
6
2

Relationship

2
6

Authors

Journals

citations
Cited by 17 publications
(5 citation statements)
references
References 120 publications
0
4
0
Order By: Relevance
“…Furthermore, the framework may also be integrated with self‐management capabilities 39 to perform SLA‐aware autonomic rescheduling of microservices. The recent Fog computing paradigm 40 facilitates the deployment and execution of Internet of Things applications designed as microservices. The TIARM framework may be further extended to consider the characteristics of Fog environments and perform rescheduling of Fog applications.…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, the framework may also be integrated with self‐management capabilities 39 to perform SLA‐aware autonomic rescheduling of microservices. The recent Fog computing paradigm 40 facilitates the deployment and execution of Internet of Things applications designed as microservices. The TIARM framework may be further extended to consider the characteristics of Fog environments and perform rescheduling of Fog applications.…”
Section: Discussionmentioning
confidence: 99%
“…The first were centralized, and relied mainly on the computational power of the cloud [44]. With the increasing number of assets being monitored and the high volumes of generated data, these approaches evolved into decentralized and modular solutions, exploiting the capabilities of edge devices to reduce the network latency and the storage requirements of the cloud [45]. For example, in [46], the authors preprocessed data and ran ML algorithms on edge devices, integrating these features within a modular platform with computational cloud capabilities.…”
Section: Architectural Perspectivementioning
confidence: 99%
“…A gigantic volume of data is generated from Internet of Everything (IoE) with a wide variety that needs technologies to become capable to perform a quick analysis of data streams. Here, authors have reviewed various fog computing advancements and application domain aspects in a structured manner with recent advancements that emphasises on the platform management [21].…”
Section: Literature Surveymentioning
confidence: 99%