TY - GEN
T1 - Enabling Proactive Microservice Placement in Collaborative Edge Computing Networks
AU - Wang, Zichen
AU - Jin, Kunming
AU - Zeng, Luchuan
AU - Zhang, Chen
AU - Du, Hongwei
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - Service placement is a critical problem in mobile edge computing (MEC) to ensure seamless service provision. Recently, some proactive service placement schemes have been proposed. However, most of these designs focus on the placement of independent services, which cannot efficiently handle directed acyclic graph (DAG)-based services. Existing DAG-based service placement schemes fail to consider the collaboration of the edge server for placing microservices. Moreover, they do not consider the impact of microservice placement orders on service latency. In this paper, we propose a proactive microservice placement framework in collaborative edge computing, aiming to minimize the overall service latency. To improve the microservice placement rate on a single edge server, we first design a microservice sorting scheme and then develop a dynamic microservice placement algorithm, employing the concept of the sliding window. After that, we extend the design and propose a critical path-based collaborative microservice placement algorithm. This algorithm supports collaboration across edge servers and reduces the need for forwarding requests to the remote cloud. Finally, we analyze the theoretical results and time complexity of the proposed algorithms. The experiment results indicate that our proposed algorithm can reduce DAG service response latency by 2.28–30.45%.
AB - Service placement is a critical problem in mobile edge computing (MEC) to ensure seamless service provision. Recently, some proactive service placement schemes have been proposed. However, most of these designs focus on the placement of independent services, which cannot efficiently handle directed acyclic graph (DAG)-based services. Existing DAG-based service placement schemes fail to consider the collaboration of the edge server for placing microservices. Moreover, they do not consider the impact of microservice placement orders on service latency. In this paper, we propose a proactive microservice placement framework in collaborative edge computing, aiming to minimize the overall service latency. To improve the microservice placement rate on a single edge server, we first design a microservice sorting scheme and then develop a dynamic microservice placement algorithm, employing the concept of the sliding window. After that, we extend the design and propose a critical path-based collaborative microservice placement algorithm. This algorithm supports collaboration across edge servers and reduces the need for forwarding requests to the remote cloud. Finally, we analyze the theoretical results and time complexity of the proposed algorithms. The experiment results indicate that our proposed algorithm can reduce DAG service response latency by 2.28–30.45%.
KW - DAG task
KW - Mobile edge computing
KW - Proactive microservice placement
UR - https://www.scopus.com/pages/publications/85205490969
U2 - 10.1007/978-981-97-7801-0_4
DO - 10.1007/978-981-97-7801-0_4
M3 - 会议稿件
AN - SCOPUS:85205490969
SN - 9789819778003
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 40
EP - 51
BT - Algorithmic Aspects in Information and Management - 18th International Conference, AAIM 2024, Proceedings
A2 - Ghosh, Smita
A2 - Zhang, Zhao
PB - Springer Science and Business Media Deutschland GmbH
T2 - 18th International Conference on Algorithmic Aspects in Information and Management, AAIM 2024
Y2 - 21 September 2024 through 23 September 2024
ER -