Collaborative task offloading and resource allocation optimization for intelligent edge devices
In order to deal with the increasingly scarce computing resources, a cooperative edge computing scheme was proposed, which makes full use of the idle resources among users to improve the overall data processing performance.To maximize the user utility, the target problem was formulated as an MINLP (...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
China InfoCom Media Group
2022-12-01
|
| Series: | 物联网学报 |
| Subjects: | |
| Online Access: | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2022.00303/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841533737624403968 |
|---|---|
| author | Xian LI Suzhi BI Hongru ZENG Bin LIN Xiaohui LIN |
| author_facet | Xian LI Suzhi BI Hongru ZENG Bin LIN Xiaohui LIN |
| author_sort | Xian LI |
| collection | DOAJ |
| description | In order to deal with the increasingly scarce computing resources, a cooperative edge computing scheme was proposed, which makes full use of the idle resources among users to improve the overall data processing performance.To maximize the user utility, the target problem was formulated as an MINLP (mixed integer non-linear programming), and a learning-optimization-integrated method was proposed to jointly optimize the resource allocation and user offloading decisions.Simulation results show that the proposed scheme can produce a near-optimal solution in sub-second and effectively improve the system utility at least 85.4% compared to the considered benchmark methods. |
| format | Article |
| id | doaj-art-8886c520be9740428b606df5acb99901 |
| institution | Kabale University |
| issn | 2096-3750 |
| language | zho |
| publishDate | 2022-12-01 |
| publisher | China InfoCom Media Group |
| record_format | Article |
| series | 物联网学报 |
| spelling | doaj-art-8886c520be9740428b606df5acb999012025-01-15T02:54:44ZzhoChina InfoCom Media Group物联网学报2096-37502022-12-016415259580188Collaborative task offloading and resource allocation optimization for intelligent edge devicesXian LISuzhi BIHongru ZENGBin LINXiaohui LINIn order to deal with the increasingly scarce computing resources, a cooperative edge computing scheme was proposed, which makes full use of the idle resources among users to improve the overall data processing performance.To maximize the user utility, the target problem was formulated as an MINLP (mixed integer non-linear programming), and a learning-optimization-integrated method was proposed to jointly optimize the resource allocation and user offloading decisions.Simulation results show that the proposed scheme can produce a near-optimal solution in sub-second and effectively improve the system utility at least 85.4% compared to the considered benchmark methods.http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2022.00303/mobile edge computingutility maximizationconvex optimizationreinforcement learning |
| spellingShingle | Xian LI Suzhi BI Hongru ZENG Bin LIN Xiaohui LIN Collaborative task offloading and resource allocation optimization for intelligent edge devices 物联网学报 mobile edge computing utility maximization convex optimization reinforcement learning |
| title | Collaborative task offloading and resource allocation optimization for intelligent edge devices |
| title_full | Collaborative task offloading and resource allocation optimization for intelligent edge devices |
| title_fullStr | Collaborative task offloading and resource allocation optimization for intelligent edge devices |
| title_full_unstemmed | Collaborative task offloading and resource allocation optimization for intelligent edge devices |
| title_short | Collaborative task offloading and resource allocation optimization for intelligent edge devices |
| title_sort | collaborative task offloading and resource allocation optimization for intelligent edge devices |
| topic | mobile edge computing utility maximization convex optimization reinforcement learning |
| url | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2022.00303/ |
| work_keys_str_mv | AT xianli collaborativetaskoffloadingandresourceallocationoptimizationforintelligentedgedevices AT suzhibi collaborativetaskoffloadingandresourceallocationoptimizationforintelligentedgedevices AT hongruzeng collaborativetaskoffloadingandresourceallocationoptimizationforintelligentedgedevices AT binlin collaborativetaskoffloadingandresourceallocationoptimizationforintelligentedgedevices AT xiaohuilin collaborativetaskoffloadingandresourceallocationoptimizationforintelligentedgedevices |