Dependent task offloading with energy‐latency tradeoff in mobile edge computing
Abstract With the rapid development of Internet‐of‐Things (IoT) and mobile devices, the IoT applications become more computation‐intensive and latency‐sensitive, which bring severe challenges to the resource‐limited devices. Mobile Edge Computing has served as a key promising method to enhance the n...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-10-01
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| Series: | IET Communications |
| Online Access: | https://doi.org/10.1049/cmu2.12454 |
| _version_ | 1828725578744725504 |
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| author | Yanfang Zhang Jian Chen Yuchen Zhou Long Yang Bingtao He Yijin Yang |
| author_facet | Yanfang Zhang Jian Chen Yuchen Zhou Long Yang Bingtao He Yijin Yang |
| author_sort | Yanfang Zhang |
| collection | DOAJ |
| description | Abstract With the rapid development of Internet‐of‐Things (IoT) and mobile devices, the IoT applications become more computation‐intensive and latency‐sensitive, which bring severe challenges to the resource‐limited devices. Mobile Edge Computing has served as a key promising method to enhance the network's computing capability by enabling resource‐constrained devices to offload tasks to the edge servers. A major challenge, which has been overlooked by most existing works on task offloading, is the dependencies among tasks and subtasks. In this paper, the subtask offloading with logical dependency for IoT applications is focused on. Specifically, subtask dependent graphs are employed to explore the dependency of subtasks and consider the priority of task scheduling. Further, an offloading scheme is put forward for minimizing both task latency and energy consumption of the device with dependency guarantees for all IoT tasks in multi‐server edge networks. Finaly, the simulation results demonstrate that the overall reduction rate is around 14% and relatively stable can effectively reduce task latency in multi‐server edge networks. |
| first_indexed | 2024-04-12T13:29:36Z |
| format | Article |
| id | doaj.art-bfe4dd5711264bcc9954132574cf5f09 |
| institution | Directory Open Access Journal |
| issn | 1751-8628 1751-8636 |
| language | English |
| last_indexed | 2024-04-12T13:29:36Z |
| publishDate | 2022-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Communications |
| spelling | doaj.art-bfe4dd5711264bcc9954132574cf5f092022-12-22T03:31:13ZengWileyIET Communications1751-86281751-86362022-10-0116171993200110.1049/cmu2.12454Dependent task offloading with energy‐latency tradeoff in mobile edge computingYanfang Zhang0Jian Chen1Yuchen Zhou2Long Yang3Bingtao He4Yijin Yang5The State Key Laboratory of Integrated Service Networks Xidian University Xi'an 710071 People's Republic of ChinaThe State Key Laboratory of Integrated Service Networks Xidian University Xi'an 710071 People's Republic of ChinaThe State Key Laboratory of Integrated Service Networks Xidian University Xi'an 710071 People's Republic of ChinaThe State Key Laboratory of Integrated Service Networks Xidian University Xi'an 710071 People's Republic of ChinaThe State Key Laboratory of Integrated Service Networks Xidian University Xi'an 710071 People's Republic of ChinaThe State Key Laboratory of Integrated Service Networks Xidian University Xi'an 710071 People's Republic of ChinaAbstract With the rapid development of Internet‐of‐Things (IoT) and mobile devices, the IoT applications become more computation‐intensive and latency‐sensitive, which bring severe challenges to the resource‐limited devices. Mobile Edge Computing has served as a key promising method to enhance the network's computing capability by enabling resource‐constrained devices to offload tasks to the edge servers. A major challenge, which has been overlooked by most existing works on task offloading, is the dependencies among tasks and subtasks. In this paper, the subtask offloading with logical dependency for IoT applications is focused on. Specifically, subtask dependent graphs are employed to explore the dependency of subtasks and consider the priority of task scheduling. Further, an offloading scheme is put forward for minimizing both task latency and energy consumption of the device with dependency guarantees for all IoT tasks in multi‐server edge networks. Finaly, the simulation results demonstrate that the overall reduction rate is around 14% and relatively stable can effectively reduce task latency in multi‐server edge networks.https://doi.org/10.1049/cmu2.12454 |
| spellingShingle | Yanfang Zhang Jian Chen Yuchen Zhou Long Yang Bingtao He Yijin Yang Dependent task offloading with energy‐latency tradeoff in mobile edge computing IET Communications |
| title | Dependent task offloading with energy‐latency tradeoff in mobile edge computing |
| title_full | Dependent task offloading with energy‐latency tradeoff in mobile edge computing |
| title_fullStr | Dependent task offloading with energy‐latency tradeoff in mobile edge computing |
| title_full_unstemmed | Dependent task offloading with energy‐latency tradeoff in mobile edge computing |
| title_short | Dependent task offloading with energy‐latency tradeoff in mobile edge computing |
| title_sort | dependent task offloading with energy latency tradeoff in mobile edge computing |
| url | https://doi.org/10.1049/cmu2.12454 |
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