Virtual machine(VM)-based computation offloading suffers from long delay for VM provisioning. Existing researches are not suitable for edge computing since they are designed for resource rich cloud servers. In this paper, we reduce the delay by pre-provisioning and cloning them later. We collect a large-scale measurement trace of global users and combine them with the existing Google cloud trace. Extensive evaluation indicates that the proposed scheme outperforms the existing schemes in edge nodes.
|Title of host publication||Proceedings - 2019 IEEE International Conference on Cloud Computing, CLOUD 2019 - Part of the 2019 IEEE World Congress on Services|
|Editors||Elisa Bertino, Carl K. Chang, Peter Chen, Ernesto Damiani, Michael Goul, Katsunori Oyama|
|Publisher||IEEE Computer Society|
|Number of pages||3|
|Publication status||Published - 2019 Jul|
|Event||12th IEEE International Conference on Cloud Computing, CLOUD 2019 - Milan, Italy|
Duration: 2019 Jul 8 → 2019 Jul 13
|Name||IEEE International Conference on Cloud Computing, CLOUD|
|Conference||12th IEEE International Conference on Cloud Computing, CLOUD 2019|
|Period||19/7/8 → 19/7/13|
Bibliographical noteFunding Information:
ACKNOWLEDGEMENT This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. NRF2016R1A2B4014505).
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Information Systems