TY - GEN
T1 - Real-time resources allocation framework for multi-task offloading in mobile cloud computing
AU - Gu, Zhiqiang
AU - Takahashi, Ryuichi
AU - Fukazawa, Yoshiaki
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Cloudlet can effectively reduce the computing load and communication delay of the remote cloud. However, since the cloudlet does not have the powerful computing performance of the remote cloud, as the number of users changes, the resources that the cloudlet can provide for each user change. In addition, as the user has mobility and the service coverage of the cloudlet is limited, the user may get out of the service coverage of the cloudlet during the task execution. In this case, the user will not receive the calculation results, which will lead to the failure of cloud computing. In order to allocate the necessary and sufficient resources to the users, this paper proposes a real-time resource allocation framework. A task movement record-based particle swarm optimization (MRPSO) algorithm is introduced to solve the problem of real-time resource allocation and task failure. Experiments show that the proposed method can provide an effective solution which performs faster than the original PSO method.
AB - Cloudlet can effectively reduce the computing load and communication delay of the remote cloud. However, since the cloudlet does not have the powerful computing performance of the remote cloud, as the number of users changes, the resources that the cloudlet can provide for each user change. In addition, as the user has mobility and the service coverage of the cloudlet is limited, the user may get out of the service coverage of the cloudlet during the task execution. In this case, the user will not receive the calculation results, which will lead to the failure of cloud computing. In order to allocate the necessary and sufficient resources to the users, this paper proposes a real-time resource allocation framework. A task movement record-based particle swarm optimization (MRPSO) algorithm is introduced to solve the problem of real-time resource allocation and task failure. Experiments show that the proposed method can provide an effective solution which performs faster than the original PSO method.
KW - Cloudlet
KW - Mobile cloud computing
KW - PSO
UR - http://www.scopus.com/inward/record.url?scp=85074141490&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85074141490&partnerID=8YFLogxK
U2 - 10.1109/CITS.2019.8862120
DO - 10.1109/CITS.2019.8862120
M3 - Conference contribution
AN - SCOPUS:85074141490
T3 - CITS 2019 - Proceeding of the 2019 International Conference on Computer, Information and Telecommunication Systems
BT - CITS 2019 - Proceeding of the 2019 International Conference on Computer, Information and Telecommunication Systems
A2 - Obaidat, Mohammad S.
A2 - Mi, Zhenqiang
A2 - Hsiao, Kuei-Fang
A2 - Nicopolitidis, Petros
A2 - Cascado-Caballero, Daniel
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Conference on Computer, Information and Telecommunication Systems, CITS 2019
Y2 - 28 August 2019 through 31 August 2019
ER -