A Survey of Fog Computing

Yi, Shanhe; Cheng, Li; Li, Qun

doi:10.1145/2757384.2757397

Cited by 1,093 publications

(135 citation statements)

References 45 publications

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“…Based on edge and fog computing definitions [34], exiting technology reviews [35,36], the identified technical requirements of the potential applications, and experience gained in the course of advanced cloud computing and software engineering projects, such as mOSAIC [37], SWITCH [38] and ENTICE [39], an adequate conceptual approach for edge computing in construction is prepared. It defines the main necessary services that can be used to obtain high QoS.…”

Section: Methodsmentioning

confidence: 99%

Supporting smart construction with dependable edge computing infrastructures and applications

Kochovski

Stankovski

2018

Automation in Construction

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The Internet of Things (IoT) such as the use of robots, sensors, actuators, electronic signalization and a variety of other Internet enabled physical devices may provide for new advanced smart applications to be used in construction in very near future. Such applications require real-time responses and are therefore time-critical. Therefore, in order to support collaboration, control, monitoring, supply management, safety and other construction processes, they have to meet dependability requirements, including requirements for high Quality of Service (QoS). Dependability and high QoS can be achieved by using adequate number and quality of computing resources, such as processing, memory and networking elements, geographically close to the smart environments. The goal of this study is to develop a practical edge computing architecture and design, which can be used in to support smart construction environments with high QoS. This study gives particular attention to the solution design, which relies on latest cloud and software engineering approaches and technologies, and provides elasticity, interoperability and adaptation to companies' specific needs. Two edge computing applications supporting video communications and construction process documentation are developed and demonstrate a viable edge computing design for smart construction.

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Section: Methodsmentioning

confidence: 99%

Supporting smart construction with dependable edge computing infrastructures and applications

Kochovski

Stankovski

2018

Automation in Construction

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“…Stern efforts are in progress across the power system and transportation communities to come up with SG cloud utilities and platforms leveraged with robust protective contrivances where the stakeholders could entrust the storage of sensitive and critical data even under concurrent share and access architectures [15], [16].…”

Section: Privacy and Securitymentioning

confidence: 99%

Computational Viability of Fog Methodologies in IoT Enabled Smart City Architectures-A Smart Grid Case Study

Hussain¹,

Alam²,

Beg³

2018

EAI Endorsed Transactions on Smart Cities

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The gradual evolution in the Information Communication Technology (ICT) support of Smart City (SC) architecture leveraged with meshes of Internet of Things (IoT) creates and welcomes research and investment efforts from academia, R&Ds and policymakers. The IoT utilities are being deployed at every layers of a typical SG backbone namely Application layer, Energy layer and Communication layer. The geo-distributed clusters of IoT -objects‖ produce galactic volume of data that exacerbates the need to make a paradigm shift from centralized data center based processing to a hybrid model that supports both in situ as well as cloud based storage and computational resources. To combat such SC issues, Fog Computing (FC) emerges as a promising solution, which pushes the computation resources onto the network edge nodes. This work investigates the high performance of Fog Computing over generic cloud computing in terms of metrics viz. latencies, power consumption etc, through a Smart Grid (SG) use-case. Through an operational cost optimization framework, the work comprehends the suitability of fog methodologies to make a synergistic interplay with the core centered clouds thus empowering a wide breed of real-time and latency free services. Finally, an overview of the core orchestration issues, challenges, and future research directions are presented for FC enabled SCs.

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“…Authors in [10][11][12] presented various scenarios for Fog computing. For instance, connected vehicles, smart grid, wireless sensor and actuator networks can benefit considerably from low-delay response using Fog computing [10].…”

Section: Fog Computingmentioning

confidence: 99%

“…For instance, connected vehicles, smart grid, wireless sensor and actuator networks can benefit considerably from low-delay response using Fog computing [10]. Other potential scenarios include Internet of Things (IoT) and cyber-physical systems [11]. Fog computing can also facilitate augmented reality and real-time video analytics and mobile big data analytics that require intensive computations [12].…”

Section: Fog Computingmentioning

confidence: 99%

“…Cloudlets can provide low delay, high bandwidth access to high-end computing devices that are within one wireless hop, which can bring substantial value to new emerging applications [8,9]. The concept of cloudlets is consistent with the recent concept of Fog computing [10][11][12] which focuses on the edge for mobile users so that mobile users can access computation-intensive services via short-distance and low-delay local connections. Further, cloudlets can also be considered as "second-class data centers" which are much more flexible and easier to maintain or replace compared to the traditional data centers [9].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Nearby live virtual machine migration using cloudlets and multipath TCP

2016

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A nearby virtual machine (VM) based cloudlet is proposed for mobile cloud computing (MCC) to enhance the performance of real-time resource-intensive mobile applications. Generally, when a mobile device (MD) discovers a cloudlet in the vicinity, it takes time to set up a VM inside the cloudlet before data offloading from the MD to the VM starts. The time between the discovery of the cloudlet and actual offloading of data is considered as the service initiation time. When multiple cloudlets are present in a nearby geographical location, initiating a service with each cloudlet may be frustrating for cloudlet users that moving from one location to another. In order to eliminate the delay caused by the service initiation time after moving away from the source cloudlet, this paper proposes a seamless live VM migration between neighbouring cloudlets. A seamless live VM migration is achieved with the prior knowledge of the migrating VM IP address in the destination cloudlet and more importantly with multipath TCP (MPTCP). We have performed a number of experiments to validate the proposed approach using Linux KVM hypervisor. The experimental results demonstrate the feasibility of the proposed approach and also show performance improvement. Specifically, there is almost zero downtime at the destination cloudlet after the migration is completed.

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A Survey of Fog Computing

Cited by 1,093 publications

References 45 publications

Supporting smart construction with dependable edge computing infrastructures and applications

Supporting smart construction with dependable edge computing infrastructures and applications

Computational Viability of Fog Methodologies in IoT Enabled Smart City Architectures-A Smart Grid Case Study

Nearby live virtual machine migration using cloudlets and multipath TCP

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