%0 Conference Paper %1 zha19ITC31 %A Zhao, Peiyue %A Dán, György %B 31th International Teletraffic Congress (ITC 31) %C Budapest, Hungary %D 2019 %K itc itc31 %T Scheduling Parallel Migration of Virtualized Services under Time Constraints in Mobile Edge Clouds %U https://gitlab2.informatik.uni-wuerzburg.de/itc-conference/itc-conference-public/-/raw/master/itc31/zha19ITC31.pdf?inline=true %X Migrating virtualized services (VSs) in mobile edge clouds is essential for maintaining service quality under mobility, for optimizing resource utilization, and for responding to incidents. We consider migrating VSs with heterogeneous resource requirements from a source placement to a target placement under a time constraint, while maintaining service continuity as much as possible. We formulate the VS migration problem as an integer programming problem, and propose an efficient algorithm to compute sequences of migration actions. The algorithm is based on a graphical representation of the VS dependencies, and constructs a collection of acyclic directed hypergraphs with bounded length. We evaluate our algorithm in realistic scenarios and compare it to the optimal solution and to a baseline algorithm. Extensive simulations show that our algorithm achieves near-optimal performance, and is computationally efficient and scalable.

@inproceedings{zha19ITC31, abstract = {Migrating virtualized services (VSs) in mobile edge clouds is essential for maintaining service quality under mobility, for optimizing resource utilization, and for responding to incidents. We consider migrating VSs with heterogeneous resource requirements from a source placement to a target placement under a time constraint, while maintaining service continuity as much as possible. We formulate the VS migration problem as an integer programming problem, and propose an efficient algorithm to compute sequences of migration actions. The algorithm is based on a graphical representation of the VS dependencies, and constructs a collection of acyclic directed hypergraphs with bounded length. We evaluate our algorithm in realistic scenarios and compare it to the optimal solution and to a baseline algorithm. Extensive simulations show that our algorithm achieves near-optimal performance, and is computationally efficient and scalable.}, added-at = {2020-04-29T15:29:04.000+0200}, address = {Budapest, Hungary}, author = {Zhao, Peiyue and Dán, György}, biburl = {https://www.bibsonomy.org/bibtex/26be80f8b77f99130dec30fb66009bd0e/itc}, booktitle = {31th International Teletraffic Congress (ITC 31)}, interhash = {9074a7320f3259f55981e882dd4c169a}, intrahash = {6be80f8b77f99130dec30fb66009bd0e}, keywords = {itc itc31}, timestamp = {2020-04-30T18:18:45.000+0200}, title = {Scheduling Parallel Migration of Virtualized Services under Time Constraints in Mobile Edge Clouds}, url = {https://gitlab2.informatik.uni-wuerzburg.de/itc-conference/itc-conference-public/-/raw/master/itc31/zha19ITC31.pdf?inline=true}, year = 2019 }