Help your mobile applications with fog computing

Hassan, Mohammed Anowarul; Xiao, Mengbai; Wei, Qi; Chen, Songqing

doi:10.1109/seconw.2015.7328146

Cited by 98 publications

(62 citation statements)

References 11 publications

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“…This stresses the need for the algorithms that perform offloading and load redistribution in the system. In this context, Hassan et al [91] and Ye et al [92] have focused on offloading devices in the IoT/end-users stratum to nodes in the fog stratum. Instead, Fricker et al [93], Ningning et al [94] have only focused on the fog stratum and addressed offloading and load redistribution.…”

Section: ) Offloading and Load Redistributionmentioning

confidence: 99%

“…Previous works have mainly considered this aspect in the specific context of Fog-Radio Access Networks (F-RAN), as in the case of Tandon et al [97], Park et al [98], Hung et al [99], and Xiang et al [100]. Other works have covered this aspect for the fog systems, operating on top of any underlying communication network, as in the case of Do et al [101], Jingtao et al [102], Malensek et al [103], and Hassan et al [91].…”

Section: B Algorithms For Content Storage and Distribution In The Fogmentioning

confidence: 99%

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

Mouradian

Naboulsi

Yangui

et al. 2018

IEEE Commun. Surv. Tutorials

851

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: ) Offloading and Load Redistributionmentioning

confidence: 99%

Section: B Algorithms For Content Storage and Distribution In The Fogmentioning

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

851

405

View full text Add to dashboard Cite

show abstract

“…Overall, FBRC can always schedule resource optimally to obtain the low response latency. V. RELATED WORK Hassan [1] proposed an offloading mechanism using fog computing to provide nearby computing resources for mobile applications and mobile storage. It processed mobile computation tasks faster with including mobile devices and servers.…”

Section: B On Effects Of Computation Service Ratementioning

confidence: 99%

“…Nevertheless, heavy computation tasks still need to be processed at a remote cloud due to the limitation of fog's resources. Research on computation offloading has been explored on methods and in frameworks over the last few years [1][2][3]. These approaches showed that processing requests at local fog platforms results in faster response times in general compared to handling them at centralized clouds.…”

Section: Introductionmentioning

confidence: 99%

FBRC: Optimization of task Scheduling in Fog-Based Region and Cloud

Hoang

Dang

2017

2017 IEEE Trustcom/BigDataSE/Icess

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Abstract-Fog computing preserves benefits of cloud computing and is strategically positioned to address effectively many local and performance issues because its resources and specific services are virtualized and located at the edge of the customer premises. Resource management is a critical issue affecting system performance significantly. Due to the complex distribution and high mobility of fog devices, computation resources still experience high latencies in fog's large coverage area. This paper considers a Fog-based Region and Cloud (FBRC) in which requests are locally handled not just by a region but multiple regions when additional resources are needed. An efficient task scheduling mechanism is thus essential to minimize the completion time of tasks and improve user experiences. To this end, two issues are investigated in the paper: 1) designing a fog-based region architecture to provide nearby computing resources; 2) investigating efficient scheduling algorithms to distribute tasks among regions and remote clouds. To deal with the complexity of scheduling tasks, a heuristic-based algorithm is proposed based on our formulation and validated by extensive simulations.

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“…As well as other related research studies, see [10,19,20], we consider the fog layer closest to the edge of the network has the highest amount of computing nodes with limited capacity. This capacity limitation is because Local Fog devices are edge devices (e.g., mobile phone or smart sensors) that do not have high computing capacity.…”

Section: A C C E P T E D Mmentioning

confidence: 99%

Evaluating the benefits of combined and continuous Fog-to-Cloud architectures

Ramírez

Masip-Bruin

Marín‐Tordera

et al. 2017

Computer Communications

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The need to extend the features of Cloud computing to the edge of the network has fueled the development of new computing architectures, such as Fog computing. When put together, the combined and continuous use of fog and cloud computing, lays the foundation for a new and highly heterogeneous computing ecosystem, making the most out of both, cloud and fog. Incipient research efforts are devoted to propose a management architecture to properly manage such combination of resources, such as the reference architecture proposed by the OpenFog Consortium or the recent Fog-to-Cloud (F2C). In this paper, we pay attention to such a combined ecosystem and particularly evaluate the potential benefits of F2C in dynamic scenarios, considering computing resources mobility and different traffic patterns. By means of extensive simulations we specifically study the aspects of service response time, network bandwidth occupancy, power consumption and service disruption probability. The results indicate that a combined fog-to-cloud architecture brings significant performance benefits in comparison with the traditional standalone Cloud, e.g., over 50% reduction in terms of power consumption.

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Help your mobile applications with fog computing

Cited by 98 publications

References 11 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

FBRC: Optimization of task Scheduling in Fog-Based Region and Cloud

Evaluating the benefits of combined and continuous Fog-to-Cloud architectures

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