A Mobility and Execution Time Aware Task Offloading in Mobile Cloud Computing
Dublin Core
Title
A Mobility and Execution Time Aware Task Offloading in Mobile Cloud Computing
Subject
VM-migration
offloading
mobile cloud computing
cloudlet
mobility aware
Description
Nowadays, mobile devices perform almost all tasks that can be performed by a computer but empties the battery and consumes memory. It is not necessary to execute the tasks on mobile devices; instead, it is executed in the far-away cloud. To save battery energy, the tasks are offloaded and hopped through several access points to reach the cloud and executed which increased the execution time of the task. Therefore, to save execution time and energy, the tasks are offloaded to a nearby cloudlet and as the device moves, the cloudlet and mobile device are disconnected. The mobile device is connected to the next cloudlet; while the offloaded tasks are partially executed in the previous cloudlet VM migrates to the new cloudlet. The previous cloudlet examined the remaining execution time of the task. If it is less than the connection time, the task is finished and the result is transferred to the new cloudlet; otherwise, the task is offloaded to the new cloudlet. It is seen that the mobility and execution time aware task offloading model reduces the execution time and power consumption by 21-40% and 26-34% approximately to the existing mobility-aware offloading approach.
Creator
J. Arockia Mary
Alyosius, A.
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 15 (2022); pp. 30-45
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2022-08-17
Rights
Copyright (c) 2022 J.Arockia Mary, Aloysius
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
J. Arockia Mary and A Alyosius., A Mobility and Execution Time Aware Task Offloading in Mobile Cloud Computing, International Association of Online Engineering (IAOE), Vienna, Austria, 2022, accessed November 23, 2024, https://igi.indrastra.com/items/show/2324