(Offloading) QoE-Aware Application Mapping and Energy-Aware Module Placement in Fog Computing + Offloading

(Offloading) QoE-Aware Application Mapping and Energy-Aware Module Placement in Fog Computing + Offloading

Low Choon Keat, Ang Tan Fong, Chun Yong Chong, Tew Yiqi
Copyright: © 2022 |Pages: 28
DOI: 10.4018/IJWSR.299017
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Abstract

Fog computing is a potential solution for the Internet of Things in close connection with things and end-users. Fog computing will easily transfer sensitive data without delaying distributed devices. Moreover, fog computing is more in real-time streaming applications, sensor networks, IoT which need high speed and reliable internet connectivity. Due to the heterogeneous and distributed characteristics, finley distributing the task with computation offloading is a challenging task. Developing an efficient QoE-aware application mapping policy is challenging due to the different user interests. The energy consumption would usually increase after such an algorithm and policy are implemented. In this paper, we enhanced the future from the previous QoE paper by proposing a computation offloading algorithm. The proposed algorithm is to prevent overloading on fog devices. Our proposed solution has been evaluated and compared with other existing solutions, the results show that our proposed solution performs better in terms of execution time, energy consumption, and network usage.
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2. Challenges

Since QoE deals with users’ level of satisfaction for a given service or product from a service vendor, there is a challenge of developing QoE-aware policy in a real-time and heterogeneous environment (i.e. in a fog computing environment) due to the fact that the users’ interests for different services could be different from one to another and could change from time to time. Other than that, determining which applications to be mapped on which fog instances is also a challenging task as it needs to ensure that users’ QoE gain is maximized while the service QoS is observed. However, in a resource constraint and real-time environment like fog computing, it is difficult to ensure that the final objectives of the proposed policies are not obstructed where the application mapping and calculations carried out will only be performed in a short period of time with the minimum amount of computational effort.

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