Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

New cloud offloading algorithm for better energy consumption and process time

Aldmour, Rakan, Yousef, S., Yaghi, M., Tapaswi, S., Pattanaik, K. K. and Cole, M. 2017. New cloud offloading algorithm for better energy consumption and process time. International Journal of Systems Assurance Engineering and Management 8 (S2) , S730-S733. 10.1007/s13198-016-0515-2

[thumbnail of New cloud offloading Algorithm for better energy consumption and process time.pdf]
Preview
PDF - Accepted Post-Print Version
Download (175kB) | Preview

Abstract

Offloading in cloud computing is a way to execute big files in short times due to the available processing resources on core computers. However in some cases it is vital to execute the file locally on the node if the file size is less than a threshold size. There is a trade off in this issue due to the limited power of the node, therefore, in this paper a novel algorithm is proposed where the file size in each case is measured and then a decision is taken to either execute the file on the node or to send the file to be processed in the core cloud. The main reason is to save time of the execution of the file. However, the second and important reason, is to save the limited node energy in some large file, where the power consumption of the node will be very high. The measurement of the file size and the execution time and the power consumption for the local node and the core cloud is measured to represent an input to the execution decision.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Uncontrolled Keywords: Offloading, Power consumption, Execution time, Cloud computing, Mobile cloud computing
Publisher: Springer Verlag
ISSN: 0975-6809
Date of First Compliant Deposit: 12 February 2019
Date of Acceptance: 19 July 2016
Last Modified: 07 Nov 2023 11:26
URI: https://orca.cardiff.ac.uk/id/eprint/114613

Citation Data

Cited 7 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics