WFO: Cloud-Edge Cooperative Data Offloading Strategy Akin to Water Flow
The exponential growth of video data in networks has led to video flow occupying a significant proportion of network traffic, causing congestion and poor service quality. To address this issue, it is crucial to quickly offload data and ensure high-quality service for users, especially in the context...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-05-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/10/5867 |
| _version_ | 1827742250099015680 |
|---|---|
| author | Shaonan Li Yongqiang Xie Zhongbo Li Jin Qi Junjie Xie Zexin Yan |
| author_facet | Shaonan Li Yongqiang Xie Zhongbo Li Jin Qi Junjie Xie Zexin Yan |
| author_sort | Shaonan Li |
| collection | DOAJ |
| description | The exponential growth of video data in networks has led to video flow occupying a significant proportion of network traffic, causing congestion and poor service quality. To address this issue, it is crucial to quickly offload data and ensure high-quality service for users, especially in the context of cloud-edge collaboration. We propose a strategy for collaborative data offloading between cloud and edge computing, analogous to water flow (WFO). When users simultaneously access the same data from the same data source, WFO can serve more users within the limited bandwidth of the cloud while maintaining the quality of service. WFO creates a water flow-like data link between nodes to enable data offloading, using multiple nodes in collaboration to offload data for a single node. Experimental results show that compared with typical methods, such as fair-queue and first-come-first-served, WFO can significantly reduce the data offloading delay, guarantee service quality, and effectively reduce network congestion. Moreover, the number of service nodes can be as numerous as possible. |
| first_indexed | 2024-03-11T03:59:19Z |
| format | Article |
| id | doaj.art-185ade5406c54053b7cad02aec95b623 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T03:59:19Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-185ade5406c54053b7cad02aec95b6232023-11-18T00:16:56ZengMDPI AGApplied Sciences2076-34172023-05-011310586710.3390/app13105867WFO: Cloud-Edge Cooperative Data Offloading Strategy Akin to Water FlowShaonan Li0Yongqiang Xie1Zhongbo Li2Jin Qi3Junjie Xie4Zexin Yan5Institute of System Engineering, Academy of Military Sciences, Beijing 100010, ChinaInstitute of System Engineering, Academy of Military Sciences, Beijing 100010, ChinaInstitute of System Engineering, Academy of Military Sciences, Beijing 100010, ChinaInstitute of System Engineering, Academy of Military Sciences, Beijing 100010, ChinaInstitute of System Engineering, Academy of Military Sciences, Beijing 100010, ChinaInstitute of System Engineering, Academy of Military Sciences, Beijing 100010, ChinaThe exponential growth of video data in networks has led to video flow occupying a significant proportion of network traffic, causing congestion and poor service quality. To address this issue, it is crucial to quickly offload data and ensure high-quality service for users, especially in the context of cloud-edge collaboration. We propose a strategy for collaborative data offloading between cloud and edge computing, analogous to water flow (WFO). When users simultaneously access the same data from the same data source, WFO can serve more users within the limited bandwidth of the cloud while maintaining the quality of service. WFO creates a water flow-like data link between nodes to enable data offloading, using multiple nodes in collaboration to offload data for a single node. Experimental results show that compared with typical methods, such as fair-queue and first-come-first-served, WFO can significantly reduce the data offloading delay, guarantee service quality, and effectively reduce network congestion. Moreover, the number of service nodes can be as numerous as possible.https://www.mdpi.com/2076-3417/13/10/5867cloud computingcloud-edge cooperativedata offloadingFQFCFS |
| spellingShingle | Shaonan Li Yongqiang Xie Zhongbo Li Jin Qi Junjie Xie Zexin Yan WFO: Cloud-Edge Cooperative Data Offloading Strategy Akin to Water Flow Applied Sciences cloud computing cloud-edge cooperative data offloading FQ FCFS |
| title | WFO: Cloud-Edge Cooperative Data Offloading Strategy Akin to Water Flow |
| title_full | WFO: Cloud-Edge Cooperative Data Offloading Strategy Akin to Water Flow |
| title_fullStr | WFO: Cloud-Edge Cooperative Data Offloading Strategy Akin to Water Flow |
| title_full_unstemmed | WFO: Cloud-Edge Cooperative Data Offloading Strategy Akin to Water Flow |
| title_short | WFO: Cloud-Edge Cooperative Data Offloading Strategy Akin to Water Flow |
| title_sort | wfo cloud edge cooperative data offloading strategy akin to water flow |
| topic | cloud computing cloud-edge cooperative data offloading FQ FCFS |
| url | https://www.mdpi.com/2076-3417/13/10/5867 |
| work_keys_str_mv | AT shaonanli wfocloudedgecooperativedataoffloadingstrategyakintowaterflow AT yongqiangxie wfocloudedgecooperativedataoffloadingstrategyakintowaterflow AT zhongboli wfocloudedgecooperativedataoffloadingstrategyakintowaterflow AT jinqi wfocloudedgecooperativedataoffloadingstrategyakintowaterflow AT junjiexie wfocloudedgecooperativedataoffloadingstrategyakintowaterflow AT zexinyan wfocloudedgecooperativedataoffloadingstrategyakintowaterflow |