Optimal Task Processing and Energy Consumption Using Intelligent Offloading in Mobile Edge Computing
Dublin Core
Title
Optimal Task Processing and Energy Consumption Using Intelligent Offloading in Mobile Edge Computing
Subject
Mobile Edge Computing
Computation offloading
Resource optimization
energy efficiency
Description
The appearance of Edge Computing with the possibility to bring powerful computation servers near the mobile device is a major stepping stone towards better user experience and resource consumption optimization. Due to the Internet of Things invasion that led to the constant demand for communication and computation resources, many issues were imposed in order to deliver a seamless service within an optimized cost of time and energy, since most of the applications nowadays require real response time and rely on a limited battery resource. Therefore, Mobile Edge Computing is the new reliable paradigm in terms of communication and computation consumption by the mobile devices. Mobile Edge Computing rely on computation offloading to surpass cloud-based technologies issues and break the limitations of mobile devices such as computing, storage and battery resources. However, computation offloading is not always the optimal choice to adopt, which makes the offloading decision a crucial part in which many parameters should be taken in consideration such as delegating the heavy tasks to the appropriate machine within the network by migrating the high-resource node to an edge server and lend these capabilities to the low-resources one. In this paper, we use an Edge Computing simulator to see how network delay can impact the delivery of a certain result, we also experiment computation offloading using a two-tier with Edge Orchestration architecture, which turns out to be efficient in terms of processing time.
Creator
Maftah, Sara
El Ghmary, Mohamed
El Bouabidi, Hamid
Amnai, Mohamed
Ouacha, Ali
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 20 (2022); pp. 130-142
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2022-10-31
Rights
Copyright (c) 2022 Sara Maftah, Mohamed El Ghmary, Hamid El Bouabidi, Mohamed Amnai, Ali Ouacha
https://creativecommons.org/licenses/by/4.0
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Sara Maftah et al., Optimal Task Processing and Energy Consumption Using Intelligent Offloading in Mobile Edge Computing, International Association of Online Engineering (IAOE), Vienna, Austria, 2022, accessed November 7, 2024, https://igi.indrastra.com/items/show/2392