TY - GEN
T1 - Microservice-Based Computation Offloading in Mobile Edge Computing
AU - Zhang, Shengnan
AU - Xu, Hanchuan
AU - Nie, Lanshun
AU - Zhan, Dechen
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - Microservices are an emerging service architecture that, when combined with mobile edge computing (MEC), can offer low latency to nearby mobile users. Several instances of microservices hosted on the server can be started or stopped flexibly to address computational requests from users at various times of the day or night thanks to the characteristics of dynamic deployment, quick start-up, and easy transfer of microservices. from the perspective of the application provider, we need to ensure the quality of service for end-users while minimizing the number of leased edge servers. To enable efficient use of MEC resources and provide reliable performance for mobile devices, we developed an Ant colony Optimization algorithm for computational offloading based on Microservices in MEC (ACO_MMCO). then we simulate the scenario using the simulation program iFogSim2 and real data sets. According to the experimental findings, this method’s generated offloading policy outperforms the benchmark method in a number of performance evaluation criteria.
AB - Microservices are an emerging service architecture that, when combined with mobile edge computing (MEC), can offer low latency to nearby mobile users. Several instances of microservices hosted on the server can be started or stopped flexibly to address computational requests from users at various times of the day or night thanks to the characteristics of dynamic deployment, quick start-up, and easy transfer of microservices. from the perspective of the application provider, we need to ensure the quality of service for end-users while minimizing the number of leased edge servers. To enable efficient use of MEC resources and provide reliable performance for mobile devices, we developed an Ant colony Optimization algorithm for computational offloading based on Microservices in MEC (ACO_MMCO). then we simulate the scenario using the simulation program iFogSim2 and real data sets. According to the experimental findings, this method’s generated offloading policy outperforms the benchmark method in a number of performance evaluation criteria.
KW - Ant colony Optimization
KW - computation offloading
KW - iFogSim2
KW - microservice
KW - mobile edge computing
UR - https://www.scopus.com/pages/publications/85172699901
U2 - 10.1007/978-981-99-4402-6_36
DO - 10.1007/978-981-99-4402-6_36
M3 - 会议稿件
AN - SCOPUS:85172699901
SN - 9789819944019
T3 - Communications in Computer and Information Science
SP - 505
EP - 519
BT - Service Science - CCF 16th International Conference, ICSS 2023, Revised Selected Papers
A2 - Wang, Zhongjie
A2 - Xu, Hanchuan
A2 - Wang, Shangguang
PB - Springer Science and Business Media Deutschland GmbH
T2 - 16th International Conference on Service Science, ICSS 2023
Y2 - 13 May 2023 through 14 May 2023
ER -