Multi-user fine-grained task offloading scheduling strategy under cloud-edge-end collaboration
To solve the current problems of inefficiency, low utilization of intensive network resources, and high system cost in handling multi-user applications, a multi-user fine-grained task offloading scheduling approach under cloud-edge-end collaboration was proposed. Latency, energy consumption, and ser...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2024-04-01
|
| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2024086/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841533918242668544 |
|---|---|
| author | XIE Mande HUANG Zhufang SUN Hao |
| author_facet | XIE Mande HUANG Zhufang SUN Hao |
| author_sort | XIE Mande |
| collection | DOAJ |
| description | To solve the current problems of inefficiency, low utilization of intensive network resources, and high system cost in handling multi-user applications, a multi-user fine-grained task offloading scheduling approach under cloud-edge-end collaboration was proposed. Latency, energy consumption, and server rental costs were jointly considered. Application tasks were firstly divided and subtask priorities were designed. Then, a multi-user subtask scheduling scheme was proposed and an improved simulated annealing particle swarm algorithm was designed to minimize the total system cost to achieve the optimal offloading decision. Experimental results show that the proposed method reduces the total cost by at least 12.28% and 7.42% compared to other methods such as particle swarm and simulated annealing binary particle swarm, respectively. |
| format | Article |
| id | doaj-art-a021a45366794c0eb08148664f713da0 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2024-04-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-a021a45366794c0eb08148664f713da02025-01-15T02:48:25ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012024-04-014010712156705381Multi-user fine-grained task offloading scheduling strategy under cloud-edge-end collaborationXIE MandeHUANG ZhufangSUN HaoTo solve the current problems of inefficiency, low utilization of intensive network resources, and high system cost in handling multi-user applications, a multi-user fine-grained task offloading scheduling approach under cloud-edge-end collaboration was proposed. Latency, energy consumption, and server rental costs were jointly considered. Application tasks were firstly divided and subtask priorities were designed. Then, a multi-user subtask scheduling scheme was proposed and an improved simulated annealing particle swarm algorithm was designed to minimize the total system cost to achieve the optimal offloading decision. Experimental results show that the proposed method reduces the total cost by at least 12.28% and 7.42% compared to other methods such as particle swarm and simulated annealing binary particle swarm, respectively.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2024086/edge computingtask offloadingcloud-edge-end collaborationmulti-userfine-grained scheduling |
| spellingShingle | XIE Mande HUANG Zhufang SUN Hao Multi-user fine-grained task offloading scheduling strategy under cloud-edge-end collaboration Dianxin kexue edge computing task offloading cloud-edge-end collaboration multi-user fine-grained scheduling |
| title | Multi-user fine-grained task offloading scheduling strategy under cloud-edge-end collaboration |
| title_full | Multi-user fine-grained task offloading scheduling strategy under cloud-edge-end collaboration |
| title_fullStr | Multi-user fine-grained task offloading scheduling strategy under cloud-edge-end collaboration |
| title_full_unstemmed | Multi-user fine-grained task offloading scheduling strategy under cloud-edge-end collaboration |
| title_short | Multi-user fine-grained task offloading scheduling strategy under cloud-edge-end collaboration |
| title_sort | multi user fine grained task offloading scheduling strategy under cloud edge end collaboration |
| topic | edge computing task offloading cloud-edge-end collaboration multi-user fine-grained scheduling |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2024086/ |
| work_keys_str_mv | AT xiemande multiuserfinegrainedtaskoffloadingschedulingstrategyundercloudedgeendcollaboration AT huangzhufang multiuserfinegrainedtaskoffloadingschedulingstrategyundercloudedgeendcollaboration AT sunhao multiuserfinegrainedtaskoffloadingschedulingstrategyundercloudedgeendcollaboration |