Cargando…
Service Migration Policy Optimization considering User Mobility for E-Healthcare Applications
Mobile edge computing (MEC) is an emerging technology that provides cloud services at the edge of network to enable latency-critical and resource-intensive E-healthcare applications. User mobility is common in MEC. User mobility can result in an interruption of ongoing edge services and a dramatic d...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8238570/ https://www.ncbi.nlm.nih.gov/pubmed/34249298 http://dx.doi.org/10.1155/2021/9922876 |
_version_ | 1783714925944766464 |
---|---|
author | Zhao, Xuhui Liu, Jianghui Ji, Baofeng Wang, Lin |
author_facet | Zhao, Xuhui Liu, Jianghui Ji, Baofeng Wang, Lin |
author_sort | Zhao, Xuhui |
collection | PubMed |
description | Mobile edge computing (MEC) is an emerging technology that provides cloud services at the edge of network to enable latency-critical and resource-intensive E-healthcare applications. User mobility is common in MEC. User mobility can result in an interruption of ongoing edge services and a dramatic drop in quality of service. Service migration has a great potential to address the issues and brings inevitable cost for the system. In this paper, we propose a service migration solution based on migration zone and formulate service migration cost with a comprehensive model that captures the key challenges. Then, we formulate service migration problem into Markov decision process to obtain optimal service migration policies that decide where to migrate in a limited area. We propose three algorithms to resolve the optimization problem given by the formulated model. Finally, we demonstrate the performance of our proposed algorithms by carrying out extensive experiments. We show that the proposed service migration approach reduces the total cost by up to 3 times compared to no migration and outperforms the general solution in terms of the total expected reward. |
format | Online Article Text |
id | pubmed-8238570 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-82385702021-07-08 Service Migration Policy Optimization considering User Mobility for E-Healthcare Applications Zhao, Xuhui Liu, Jianghui Ji, Baofeng Wang, Lin J Healthc Eng Research Article Mobile edge computing (MEC) is an emerging technology that provides cloud services at the edge of network to enable latency-critical and resource-intensive E-healthcare applications. User mobility is common in MEC. User mobility can result in an interruption of ongoing edge services and a dramatic drop in quality of service. Service migration has a great potential to address the issues and brings inevitable cost for the system. In this paper, we propose a service migration solution based on migration zone and formulate service migration cost with a comprehensive model that captures the key challenges. Then, we formulate service migration problem into Markov decision process to obtain optimal service migration policies that decide where to migrate in a limited area. We propose three algorithms to resolve the optimization problem given by the formulated model. Finally, we demonstrate the performance of our proposed algorithms by carrying out extensive experiments. We show that the proposed service migration approach reduces the total cost by up to 3 times compared to no migration and outperforms the general solution in terms of the total expected reward. Hindawi 2021-06-19 /pmc/articles/PMC8238570/ /pubmed/34249298 http://dx.doi.org/10.1155/2021/9922876 Text en Copyright © 2021 Xuhui Zhao et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Zhao, Xuhui Liu, Jianghui Ji, Baofeng Wang, Lin Service Migration Policy Optimization considering User Mobility for E-Healthcare Applications |
title | Service Migration Policy Optimization considering User Mobility for E-Healthcare Applications |
title_full | Service Migration Policy Optimization considering User Mobility for E-Healthcare Applications |
title_fullStr | Service Migration Policy Optimization considering User Mobility for E-Healthcare Applications |
title_full_unstemmed | Service Migration Policy Optimization considering User Mobility for E-Healthcare Applications |
title_short | Service Migration Policy Optimization considering User Mobility for E-Healthcare Applications |
title_sort | service migration policy optimization considering user mobility for e-healthcare applications |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8238570/ https://www.ncbi.nlm.nih.gov/pubmed/34249298 http://dx.doi.org/10.1155/2021/9922876 |
work_keys_str_mv | AT zhaoxuhui servicemigrationpolicyoptimizationconsideringusermobilityforehealthcareapplications AT liujianghui servicemigrationpolicyoptimizationconsideringusermobilityforehealthcareapplications AT jibaofeng servicemigrationpolicyoptimizationconsideringusermobilityforehealthcareapplications AT wanglin servicemigrationpolicyoptimizationconsideringusermobilityforehealthcareapplications |