V2X offloading and resource allocation under SDN and MEC architecture
To address the serious problem of delay and energy consumption increase and service quality degradation caused by complex network status and huge amounts of computing data in the scenario of vehicle-to-everything (V2X),a vehicular network architecture combining mobile edge computing (MEC) and softwa...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2020-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020023/ |
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| author | Haibo ZHANG Zixin WANG Xiaofan HE |
| author_facet | Haibo ZHANG Zixin WANG Xiaofan HE |
| author_sort | Haibo ZHANG |
| collection | DOAJ |
| description | To address the serious problem of delay and energy consumption increase and service quality degradation caused by complex network status and huge amounts of computing data in the scenario of vehicle-to-everything (V2X),a vehicular network architecture combining mobile edge computing (MEC) and software defined network (SDN) was constructed.MEC sinks cloud serviced to the edge of the wireless network to compensate for the delay fluctuation caused by remote cloud computing.The SDN controller could sense network information from a global perspective,flexibly schedule resources,and control offload traffic.To further reduce the system overhead,a joint task offloading and resource allocation scheme was proposed.By modeling the MEC-based V2X offloading and resource allocation,the optimal offloading decision,communication and computing resource allocation scheme were derived.Considering the NP-hard attribute of the problem,Agglomerative Clustering was used to select the initial offloading node,and Q-learning was used for resource allocation.The offloading decision was modeled as an exact potential game,and the existence of Nash equilibrium was proved by the potential function structure.The simulation results show that,as compared to other mechanisms,the proposed mechanism can effectively reduce the system overhead. |
| format | Article |
| id | doaj-art-a26499ea057440aaacd5380814ac9fc2 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2020-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-a26499ea057440aaacd5380814ac9fc22025-01-14T07:18:25ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2020-01-014111412459732648V2X offloading and resource allocation under SDN and MEC architectureHaibo ZHANGZixin WANGXiaofan HETo address the serious problem of delay and energy consumption increase and service quality degradation caused by complex network status and huge amounts of computing data in the scenario of vehicle-to-everything (V2X),a vehicular network architecture combining mobile edge computing (MEC) and software defined network (SDN) was constructed.MEC sinks cloud serviced to the edge of the wireless network to compensate for the delay fluctuation caused by remote cloud computing.The SDN controller could sense network information from a global perspective,flexibly schedule resources,and control offload traffic.To further reduce the system overhead,a joint task offloading and resource allocation scheme was proposed.By modeling the MEC-based V2X offloading and resource allocation,the optimal offloading decision,communication and computing resource allocation scheme were derived.Considering the NP-hard attribute of the problem,Agglomerative Clustering was used to select the initial offloading node,and Q-learning was used for resource allocation.The offloading decision was modeled as an exact potential game,and the existence of Nash equilibrium was proved by the potential function structure.The simulation results show that,as compared to other mechanisms,the proposed mechanism can effectively reduce the system overhead.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020023/vehicular networkmobile edge computingsoftware defined networkresource allocation |
| spellingShingle | Haibo ZHANG Zixin WANG Xiaofan HE V2X offloading and resource allocation under SDN and MEC architecture Tongxin xuebao vehicular network mobile edge computing software defined network resource allocation |
| title | V2X offloading and resource allocation under SDN and MEC architecture |
| title_full | V2X offloading and resource allocation under SDN and MEC architecture |
| title_fullStr | V2X offloading and resource allocation under SDN and MEC architecture |
| title_full_unstemmed | V2X offloading and resource allocation under SDN and MEC architecture |
| title_short | V2X offloading and resource allocation under SDN and MEC architecture |
| title_sort | v2x offloading and resource allocation under sdn and mec architecture |
| topic | vehicular network mobile edge computing software defined network resource allocation |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020023/ |
| work_keys_str_mv | AT haibozhang v2xoffloadingandresourceallocationundersdnandmecarchitecture AT zixinwang v2xoffloadingandresourceallocationundersdnandmecarchitecture AT xiaofanhe v2xoffloadingandresourceallocationundersdnandmecarchitecture |