TY - JOUR
T1 - A fast hybrid multi-site computation offloading for mobile cloud computing
AU - Goudarzi, Mohammad
AU - Zamani, Mehran
AU - Haghighat, Abolfazl Toroghi
N1 - Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2017/2/15
Y1 - 2017/2/15
N2 - Due to nowadays advances of mobile technologies in both hardware and software, mobile devices have become an inseparable part of human life. Along with this progress, mobile devices are expected to perform various types of applications. However, the energy challenge of mobile devices along with their limited computation power act as barriers in front of this expectation. To address this deficiency, mobile cloud computing has been proposed in which computation-intensive tasks of mobile devices are offloaded to cloud resources, so that the energy and time spent for executing the mobile application are reduced. Moreover, in the real world, different types of clouds/servers with heterogeneous processing speeds and access delays are available for offloading resulting in time consuming process of making decision for offloading. To address these objectives, we propose a fast hybrid multi-site computation offloading solution which finds the offloading solution in a timely manner. Our solution includes two decision algorithms to achieve the optimal or near-optimal solution of multi-site offloading considering the application size. We evaluated the efficiency of the proposed solution using both simulation and testbed experiments. The evaluation study demonstrates that our proposal can outperform existing optimal and near-optimal counterparts in terms of weighted execution cost, energy consumption and execution time.
AB - Due to nowadays advances of mobile technologies in both hardware and software, mobile devices have become an inseparable part of human life. Along with this progress, mobile devices are expected to perform various types of applications. However, the energy challenge of mobile devices along with their limited computation power act as barriers in front of this expectation. To address this deficiency, mobile cloud computing has been proposed in which computation-intensive tasks of mobile devices are offloaded to cloud resources, so that the energy and time spent for executing the mobile application are reduced. Moreover, in the real world, different types of clouds/servers with heterogeneous processing speeds and access delays are available for offloading resulting in time consuming process of making decision for offloading. To address these objectives, we propose a fast hybrid multi-site computation offloading solution which finds the offloading solution in a timely manner. Our solution includes two decision algorithms to achieve the optimal or near-optimal solution of multi-site offloading considering the application size. We evaluated the efficiency of the proposed solution using both simulation and testbed experiments. The evaluation study demonstrates that our proposal can outperform existing optimal and near-optimal counterparts in terms of weighted execution cost, energy consumption and execution time.
KW - Mobile cloud computing
KW - Multi-site computation offloading
KW - Near-optimal partitioning
KW - Optimal partitioning
KW - Optimization
UR - http://www.scopus.com/inward/record.url?scp=85008512233&partnerID=8YFLogxK
U2 - 10.1016/j.jnca.2016.12.031
DO - 10.1016/j.jnca.2016.12.031
M3 - Article
AN - SCOPUS:85008512233
SN - 1084-8045
VL - 80
SP - 219
EP - 231
JO - Journal of Network and Computer Applications
JF - Journal of Network and Computer Applications
ER -