New cloud offloading algorithm for better energy consumption and process time

R. Aldmour (), S. Yousef (), M. Yaghi, S. Tapaswi, K. K. Pattanaik and M. Cole
Additional contact information
R. Aldmour: Anglia Ruskin University
S. Yousef: Anglia Ruskin University
M. Yaghi: Anglia Ruskin University
S. Tapaswi: Anglia Ruskin University
K. K. Pattanaik: Anglia Ruskin University
M. Cole: Anglia Ruskin University

International Journal of System Assurance Engineering and Management, 2017, vol. 8, issue 2, No 16, 730-733

Abstract: 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.

Keywords: Offloading; Power consumption; Execution time; Cloud computing; Mobile cloud computing (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13198-016-0515-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-016-0515-2

Ordering information: This journal article can be ordered from
http://www.springer.com/engineering/journal/13198

DOI: 10.1007/s13198-016-0515-2

Access Statistics for this article

International Journal of System Assurance Engineering and Management is currently edited by P.K. Kapur, A.K. Verma and U. Kumar

More articles in International Journal of System Assurance Engineering and Management from Springer, The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().