Toward an autonomic approach for Internet of Things service placement using gray wolf optimization in the fog computing environment

Author(s):  
Mahboubeh Salimian ◽  
Mostafa Ghobaei‐Arani ◽  
Ali Shahidinejad
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.


2021 ◽  
Vol 11 (4) ◽  
pp. 1909
Author(s):  
Jung-Fa Tsai ◽  
Chun-Hua Huang ◽  
Ming-Hua Lin

With the advent of the Internet of Things era, more and more emerging applications need to provide real-time interactive services. Although cloud computing has many advantages, the massive expansion of the Internet of Things devices and the explosive growth of data may induce network congestion and add network latency. Cloud-fog computing processes some data locally on edge devices to reduce the network delay. This paper investigates the optimal task assignment strategy by considering the execution time and operating costs in a cloud-fog computing environment. Linear transformation techniques are used to solve the nonlinear mathematical programming model of the task assignment problem in cloud-fog computing systems. The proposed method can determine the globally optimal solution for the task assignment problem based on the requirements of the tasks, the processing speed of nodes, and the resource usage cost of nodes in cloud-fog computing systems.


PLoS ONE ◽  
2019 ◽  
Vol 14 (11) ◽  
pp. e0224934 ◽  
Author(s):  
Saurabh Shukla ◽  
Mohd Fadzil Hassan ◽  
Muhammad Khalid Khan ◽  
Low Tang Jung ◽  
Azlan Awang

Author(s):  
Kashif Munir ◽  
Lawan Ahmed Mohammed

Fog computing is a distributed infrastructure in which certain application processes or services are managed at the edge of the network by a smart device. Fog systems are capable of processing large amounts of data locally, operate on-premise, are fully portable, and can be installed on heterogeneous hardware. These features make the fog platform highly suitable for time and location-sensitive applications. For example, internet of things (IoT) devices are required to quickly process a large amount of data. The significance of enterprise data and increased access rates from low-resource terminal devices demand reliable and low-cost authentication protocols. Lots of researchers have proposed authentication protocols with varied efficiencies. As a part of this chapter, the authors propose a secure authentication protocol that is strongly secure and best suited for the fog computing environment.


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