scholarly journals An Efficient Architecture for Resource Provisioning in Fog Computing

2017 ◽  
Vol 6 (1) ◽  
pp. 2065-2069
Author(s):  
Shanthi Thangam Manukumar ◽  
Vijayalakshmi Muthuswamy

With the development of edge devices and mobile devices, the authenticated fast access for the networks is necessary and important. To make the edge and mobile devices smart, fast, and for the better quality of service (QoS), fog computing is an efficient way. Fog computing is providing the way for resource provisioning, service providers, high response time, and the best solution for mobile network traffic. In this chapter, the proposed method is for handling the fog resource management using efficient offloading mechanism. Offloading is done based on machine learning prediction technology and also by using the KNN algorithm to identify the nearest fog nodes to offload. The proposed method minimizes the energy consumption, latency and improves the QoS for edge devices, IoT devices, and mobile devices.


2019 ◽  
Vol 2 (2) ◽  
pp. 57-70 ◽  
Author(s):  
Rajni Gupta

Internet of Things (IoT) has emerged as a computing paradigm to develop smart applications such e-health care systems, smart city, smart waste management systems, etc. It contains a large number of different devices and heterogeneous networks, which make it difficult to provide secure and fast response to the end user. To provide the faster response services, there is a need to use the concept of Fog computing Recently, the use of fog computing is a rapidly increasing in many industries for the development of applications such as manufacturing, e-health, oil and gas, As more and more users have started to store/process their real-time data in Fog-based Cloud environments, resource provisioning and scheduling of IoT based applications becomes a key element of consideration for efficient execution of these applications. This article will help to select the most suitable technique for processing smart IoT based applications in Fog computing environments.


2020 ◽  
Vol 146 ◽  
pp. 96-106
Author(s):  
Shuaibing Lu ◽  
Jie Wu ◽  
Yubin Duan ◽  
Ning Wang ◽  
Juan Fang

2020 ◽  
Vol 11 (4) ◽  
pp. 17-30
Author(s):  
Shefali Varshney ◽  
Rajinder Sandhu ◽  
P. K. Gupta

Application placement in the fog environment is becoming one of the major challenges because of its distributed, hierarchical, and heterogeneous nature. Also, user expectations and various features of IoT devices further increase the complexity of the problem for the placement of applications in the fog computing environment. Therefore, to improve the QoE of various end-users for the use of various system services, proper placement of applications in the fog computing environment plays an important role. In this paper, the authors have proposed a service placement methodology for the fog computing environment. For a better selection of application services, AHP technique has been used which provides results in the form of ranks. The performance evaluation of the proposed technique has been done by using a customized testbed that considers the parameters like CPU cycle, storage, maximum latency, processing speed, and network bandwidth. Experimental results obtained for the proposed methodology improved the efficiency of the fog network.


Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2238 ◽  
Author(s):  
José Santos ◽  
Tim Wauters ◽  
Bruno Volckaert ◽  
Filip De Turck

The Internet-of-Things (IoT) and Smart Cities continue to expand at enormous rates. Centralized Cloud architectures cannot sustain the requirements imposed by IoT services. Enormous traffic demands and low latency constraints are among the strictest requirements, making cloud solutions impractical. As an answer, Fog Computing has been introduced to tackle this trend. However, only theoretical foundations have been established and the acceptance of its concepts is still in its early stages. Intelligent allocation decisions would provide proper resource provisioning in Fog environments. In this article, a Fog architecture based on Kubernetes, an open source container orchestration platform, is proposed to solve this challenge. Additionally, a network-aware scheduling approach for container-based applications in Smart City deployments has been implemented as an extension to the default scheduling mechanism available in Kubernetes. Last but not least, an optimization formulation for the IoT service problem has been validated as a container-based application in Kubernetes showing the full applicability of theoretical approaches in practical service deployments. Evaluations have been performed to compare the proposed approaches with the Kubernetes standard scheduling feature. Results show that the proposed approaches achieve reductions of 70% in terms of network latency when compared to the default scheduling mechanism.


2021 ◽  
Vol 14 (4) ◽  
pp. 94-106
Author(s):  
Pushpa Singh ◽  
Rajeev Agrawal

Fog computing is used to enrich the ability of cloud computing applications. Fog is a kind of buffer area placed between the data processing location and the data storage equipment in the network and plays a significant role in processing the real time data. The lack of resource provisioning approaches and high demand for IoT services make the fog node overloaded. Load balancing is a method to realize efficient resource utilization to avoid bottlenecks, overload, and fog node failure. This study suggests a concept to compute the probabilistic overloading state of a fog node and identification of fog node for load sharing. Each fog node computes Fstate and sends the message at regular intervals to the fog node coordinator (FNC). FNC maintains a fog that is utilized for offloading in case of fog overloading. A comparative study shows that the proposed model avoids an overloading state by the transfer of a certain number of requests to an underloaded fog node before actual overloading occurs. Numerical results validate theoretical investigation and efficiency of the proposed study.


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