Components of fog computing in an industrial internet of things context

Gazis, Vangelis; Leonardi, Alessandro; Mathioudakis, K.; Sasloglou, Konstantinos; Kikiras, Panayotis; Sudhaakar, Raghuram S.

doi:10.1109/seconw.2015.7328144

Cited by 75 publications

(37 citation statements)

References 7 publications

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“…Gazis et al [78] propose an architecture to support the IoT applications in industrial domains. The proposed architecture allows predictive maintenance for industrial equipment by taking into account the configuration of each particular infrastructure machine.…”

Section: ) Architectures For Other Applicationsmentioning

confidence: 99%

A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges

Mouradian

Naboulsi

Yangui

et al. 2018

IEEE Commun. Surv. Tutorials

834

405

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Cloud computing with its three key facets (i.e., IaaS, PaaS, and SaaS) and its inherent advantages (e.g., elasticity and scalability) still faces several challenges. The distance between the cloud and the end devices might be an issue for latencysensitive applications such as disaster management and content delivery applications. Service Level Agreements (SLAs) may also impose processing at locations where the cloud provider does not have data centers. Fog computing is a novel paradigm to address such issues. It enables provisioning resources and services outside the cloud, at the edge of the network, closer to end devices or eventually, at locations stipulated by SLAs. Fog computing is not a substitute for cloud computing but a powerful complement. It enables processing at the edge while still offering the possibility to interact with the cloud. This article presents a comprehensive survey on fog computing. It critically reviews the state of the art in the light of a concise set of evaluation criteria. We cover both the architectures and the algorithms that make fog systems. Challenges and research directions are also introduced. In addition, the lessons learned are reviewed and the prospects are discussed in terms of the key role fog is likely to play in emerging technologies such as Tactile Internet.

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Section: ) Architectures For Other Applicationsmentioning

confidence: 99%

A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges

Mouradian

Naboulsi

Yangui

et al. 2018

IEEE Commun. Surv. Tutorials

834

405

View full text Add to dashboard Cite

show abstract

“…Naturally, the Industrial Internet of Things can be linked with Cloud and Fog Computing infrastructures that manage in efficient and effective ways the large amount of data that can potentially be generated. Lots of work has already discussed different aspects of this interaction [152,153,154]. Among topics that have attracted significant attention it is worth mentioning the standardization effort towards a reference architecture proposed by the the Industrial Internet Consortium [155].…”

Section: The Industrial Internet Of Thingsmentioning

confidence: 99%

The Internet of Things, Fog and Cloud continuum: Integration and challenges

et al. 2018

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The Internet of Things needs for computing power and storage are expected to remain on the rise in the next decade. Consequently, the amount of data generated by devices at the edge of the network will also grow. While cloud computing has been an established and effective way of acquiring computation and storage as a service to many applications, it may not be suitable to handle the myriad of data from IoT devices and fulfill largely heterogeneous application requirements. Fog computing has been developed to lie between IoT and the cloud, providing a hierarchy of computing power that can collect, aggregate, and process data from/to IoT devices. Combining fog and cloud may reduce data transfers and communication bottlenecks to the cloud and also contribute to reduced latencies, as fog computing resources exist closer to the edge. This paper examines this IoT-Fog-Cloud ecosystem and provides a literature review from different facets of it: how it can be organized, how management is being addressed, and how applications can benefit from it. Lastly, we present challenging issues yet to be addressed in IoT-Fog-Cloud infrastructures. low latency, and mobile applications. The centralized cloud data centers are often physically and/or logically distant from the cloud client, implying communication and data transfers to traverse multiple hops, which introduces delays and consumes network bandwidth of edge and core networks [2].The widespread adoption of cloud computing, combined with the ever increasing ability of edge devices to run heterogeneous applications that generate and consume all kinds of data from a variety of sources, requires novel distributed computing infrastructures that can cope with such heterogeneous application requirements. Computing infrastructures that enact applications at edge devices have started to appear in recent years [3,4], improving aspects such as response time and reducing bandwidth use. Combining the ability of running smaller, localized applications at the edge with the high-capacity from the cloud, fog computing has emerged as an paradigm that can support heterogeneous requirements of small and large applications through multiple layers of a computational infrastructure that combines resources from the edge of the network as well as from the cloud [5].In this paper, we aim at identifying and reviewing the main aspects and challenges that make the combination of fog computing and cloud computing suitable for all kinds of applications leveraged by the Internet of Things. We discuss aspects from the infrastructure (processing, networking, protocols, and infrastructure for 5G support) to applications (smart cities, urban computing, and industry 4.0), passing through the management complexity of the distributed IoT-fog-cloud system (services, resource allocation and optimization, energy consumption, data management and locality, devices federation and trust, and business and service models).In the next section we introduce concepts and definitions for Internet of Things (IoT), cloud computi...

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“…Gazis et al [89] have proposed a unique system as industrial perspective for organized fog computing framework to provide elasticity for individual operational processing requirements. Femtocloud by Habak et al [90] has offered a dynamically self-configured mobile cloud with multicomponent by a clustered mobile devices structure to make availability of cloud services at the edge.…”

Section: Fog Proposed Application Taxonomymentioning

confidence: 99%

Fog Computing: An Overview of Big IoT Data Analytics

Anawar

Wang

Zia

et al. 2018

Wireless Communications and Mobile Computing

145

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A huge amount of data, generated by Internet of Things (IoT), is growing up exponentially based on nonstop operational states. Those IoT devices are generating an avalanche of information that is disruptive for predictable data processing and analytics functionality, which is perfectly handled by the cloud before explosion growth of IoT. Fog computing structure confronts those disruptions, with powerful complement functionality of cloud framework, based on deployment of micro clouds (fog nodes) at proximity edge of data sources. Particularly big IoT data analytics by fog computing structure is on emerging phase and requires extensive research to produce more proficient knowledge and smart decisions. This survey summarizes the fog challenges and opportunities in the context of big IoT data analytics on fog networking. In addition, it emphasizes that the key characteristics in some proposed research works make the fog computing a suitable platform for new proliferating IoT devices, services, and applications. Most significant fog applications (e.g., health care monitoring, smart cities, connected vehicles, and smart grid) will be discussed here to create a well-organized green computing paradigm to support the next generation of IoT applications.

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Components of fog computing in an industrial internet of things context

Cited by 75 publications

References 7 publications

A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges

A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges

The Internet of Things, Fog and Cloud continuum: Integration and challenges

Fog Computing: An Overview of Big IoT Data Analytics

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