Fog Computing: Survey of Trends, Architectures, Requirements, and Research Directions
Emerging technologies such as the Internet of Things (IoT) require latency-aware computation for real-time application processing. In IoT environments, connected things generate a huge amount of data, which are generally referred to as big data. Data generated from IoT devices are generally processe...
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| Vydané v: | IEEE access Ročník 6; s. 47980 - 48009 |
|---|---|
| Hlavní autori: | , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Piscataway
IEEE
01.01.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 2169-3536, 2169-3536 |
| On-line prístup: | Získať plný text |
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| Abstract | Emerging technologies such as the Internet of Things (IoT) require latency-aware computation for real-time application processing. In IoT environments, connected things generate a huge amount of data, which are generally referred to as big data. Data generated from IoT devices are generally processed in a cloud infrastructure because of the on-demand services and scalability features of the cloud computing paradigm. However, processing IoT application requests on the cloud exclusively is not an efficient solution for some IoT applications, especially time-sensitive ones. To address this issue, Fog computing, which resides in between cloud and IoT devices, was proposed. In general, in the Fog computing environment, IoT devices are connected to Fog devices. These Fog devices are located in close proximity to users and are responsible for intermediate computation and storage. One of the key challenges in running IoT applications in a Fog computing environment are resource allocation and task scheduling. Fog computing research is still in its infancy, and taxonomy-based investigation into the requirements of Fog infrastructure, platform, and applications mapped to current research is still required. This survey will help the industry and research community synthesize and identify the requirements for Fog computing. This paper starts with an overview of Fog computing in which the definition of Fog computing, research trends, and the technical differences between Fog and cloud are reviewed. Then, we investigate numerous proposed Fog computing architectures and describe the components of these architectures in detail. From this, the role of each component will be defined, which will help in the deployment of Fog computing. Next, a taxonomy of Fog computing is proposed by considering the requirements of the Fog computing paradigm. We also discuss existing research works and gaps in resource allocation and scheduling, fault tolerance, simulation tools, and Fog-based microservices. Finally, by addressing the limitations of current research works, we present some open issues, which will determine the future research direction for the Fog computing paradigm. |
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| AbstractList | Emerging technologies such as the Internet of Things (IoT) require latency-aware computation for real-time application processing. In IoT environments, connected things generate a huge amount of data, which are generally referred to as big data. Data generated from IoT devices are generally processed in a cloud infrastructure because of the on-demand services and scalability features of the cloud computing paradigm. However, processing IoT application requests on the cloud exclusively is not an efficient solution for some IoT applications, especially time-sensitive ones. To address this issue, Fog computing, which resides in between cloud and IoT devices, was proposed. In general, in the Fog computing environment, IoT devices are connected to Fog devices. These Fog devices are located in close proximity to users and are responsible for intermediate computation and storage. One of the key challenges in running IoT applications in a Fog computing environment are resource allocation and task scheduling. Fog computing research is still in its infancy, and taxonomy-based investigation into the requirements of Fog infrastructure, platform, and applications mapped to current research is still required. This survey will help the industry and research community synthesize and identify the requirements for Fog computing. This paper starts with an overview of Fog computing in which the definition of Fog computing, research trends, and the technical differences between Fog and cloud are reviewed. Then, we investigate numerous proposed Fog computing architectures and describe the components of these architectures in detail. From this, the role of each component will be defined, which will help in the deployment of Fog computing. Next, a taxonomy of Fog computing is proposed by considering the requirements of the Fog computing paradigm. We also discuss existing research works and gaps in resource allocation and scheduling, fault tolerance, simulation tools, and Fog-based microservices. Finally, by addressing the limitations of current research works, we present some open issues, which will determine the future research direction for the Fog computing paradigm. |
| Author | Jayaraman, Prem Prakash Gao, Longxiang Naha, Ranesh Kumar Xiang, Yong Garg, Saurabh Georgakopoulos, Dimitrios Ranjan, Rajiv |
| Author_xml | – sequence: 1 givenname: Ranesh Kumar surname: Naha fullname: Naha, Ranesh Kumar organization: School of Technology, Environments and Design, University of Tasmania, Hobart, TAS, Australia – sequence: 2 givenname: Saurabh orcidid: 0000-0001-8719-284X surname: Garg fullname: Garg, Saurabh organization: School of Technology, Environments and Design, University of Tasmania, Hobart, TAS, Australia – sequence: 3 givenname: Dimitrios surname: Georgakopoulos fullname: Georgakopoulos, Dimitrios organization: Faculty of Science, Engineering and Technology, Swinburne University of Technology, Melbourne, VIC, Australia – sequence: 4 givenname: Prem Prakash surname: Jayaraman fullname: Jayaraman, Prem Prakash organization: Faculty of Science, Engineering and Technology, Swinburne University of Technology, Melbourne, VIC, Australia – sequence: 5 givenname: Longxiang orcidid: 0000-0002-3026-7537 surname: Gao fullname: Gao, Longxiang email: longxiang.gao@deakin.edu.au organization: School of Information Technology, Deakin University, Burwood, VIC, Australia – sequence: 6 givenname: Yong surname: Xiang fullname: Xiang, Yong organization: School of Information Technology, Deakin University, Burwood, VIC, Australia – sequence: 7 givenname: Rajiv surname: Ranjan fullname: Ranjan, Rajiv organization: School of Computing, Newcastle University, Newcastle upon Tyne, U.K |
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| SubjectTerms | Cloud computing Computer architecture Edge computing Electronic devices Fault tolerance Fog computing fog devices Infrastructure Internet of Things Internet of Things (IoT) IoT application microservices New technology Resource allocation Resource management Resource scheduling Task scheduling Taxonomy Trends |
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