Energy conscious multi-site computation offloading for mobile cloud computing

Energy conscious multi-site computation offloading for mobile cloud computing In mobile devices, one of the major reasons for battery consumption is due to computation of complex applications. To provide high performance of execution on the mobile devices, the concept of mobile cloud computing (MCC) is used. MCC allows the computation complex modules to offload onto a cloud from a mobile device, which helps to remove the resource constraint condition of the mobile devices. Computations can also be offloaded to nearby clouds called multi-sites, which may have different resources, access delays, computation capability or service charges. The mobile users can specify their priority such as total completion time, cost or energy saving of the application execution in MCC environment. But most of the existing research is focused to optimize only one objective, i.e., either total completion time or cost or energy. But when offloading computation modules onto cloud-based multi-sites, a tradeoff solution is required to strike a balance between the total completion time and energy savings. Further, the entire computational execution on the cloud is to be served efficiently with optimal power utilization. Various algorithms are developed to reduce power consumption, and one such algorithm is dynamic voltage and frequency scaling (DVFS) algorithm. In this paper, new algorithms known http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Soft Computing Springer Journals

Energy conscious multi-site computation offloading for mobile cloud computing

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2018 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Engineering; Computational Intelligence; Artificial Intelligence (incl. Robotics); Mathematical Logic and Foundations; Control, Robotics, Mechatronics
ISSN
1432-7643
eISSN
1433-7479
D.O.I.
10.1007/s00500-018-3264-0
Publisher site
See Article on Publisher Site

Abstract

In mobile devices, one of the major reasons for battery consumption is due to computation of complex applications. To provide high performance of execution on the mobile devices, the concept of mobile cloud computing (MCC) is used. MCC allows the computation complex modules to offload onto a cloud from a mobile device, which helps to remove the resource constraint condition of the mobile devices. Computations can also be offloaded to nearby clouds called multi-sites, which may have different resources, access delays, computation capability or service charges. The mobile users can specify their priority such as total completion time, cost or energy saving of the application execution in MCC environment. But most of the existing research is focused to optimize only one objective, i.e., either total completion time or cost or energy. But when offloading computation modules onto cloud-based multi-sites, a tradeoff solution is required to strike a balance between the total completion time and energy savings. Further, the entire computational execution on the cloud is to be served efficiently with optimal power utilization. Various algorithms are developed to reduce power consumption, and one such algorithm is dynamic voltage and frequency scaling (DVFS) algorithm. In this paper, new algorithms known

Journal

Soft ComputingSpringer Journals

Published: May 28, 2018

References

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