Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Systems Architecture. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Systems Architecture, 94, 2019 DOI: 10.1016/j.sysarc.2019.02.001
Accepted author manuscript, 807 KB, PDF document
Available under license: CC BY-NC-ND
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - An offloading method using decentralized P2P-enabled mobile edge servers in edge computing
AU - Tang, W.
AU - Zhao, Xuan
AU - Rafique, Wajid
AU - Qi, Lianyong
AU - Dou, Wanchun
AU - Ni, Qiang
N1 - This is the author’s version of a work that was accepted for publication in Journal of Systems Architecture. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Systems Architecture, 94, 2019 DOI: 10.1016/j.sysarc.2019.02.001
PY - 2019/3/1
Y1 - 2019/3/1
N2 - Edge computing has emerged as a promising infrastructure for providing elastic resources in the proximity of mobile users. Owing to resource limitations in mobile devices, offloading several computational tasks from mobile devices to mobile edge servers is the main means of improving the quality of experience of mobile users. In fact, because of the high speeds of moving vehicles on expressways, there would be numerous candidate mobile edge servers available for them to offload their computational workload. However, the selection of the mobile edge server to be utilized and how much computation should be offloaded to meet the corresponding task deadlines without large computing bills are topics that have not been discussed much. Furthermore, with the increasing deployment of mobile edge servers, their centralized management would cause certain performance issues. In order to address these challenges, we firstly apply peer-to-peer networks to manage geo-distributed mobile edge servers. Secondly, we propose a new deadline-aware and cost-effective offloading approach, which aims to improve the offloading efficiency for vehicles and allows additional tasks to meet their deadlines. The proposed approach was validated for its feasibility and efficiency by means of extensive experiments, which are presented in this paper.
AB - Edge computing has emerged as a promising infrastructure for providing elastic resources in the proximity of mobile users. Owing to resource limitations in mobile devices, offloading several computational tasks from mobile devices to mobile edge servers is the main means of improving the quality of experience of mobile users. In fact, because of the high speeds of moving vehicles on expressways, there would be numerous candidate mobile edge servers available for them to offload their computational workload. However, the selection of the mobile edge server to be utilized and how much computation should be offloaded to meet the corresponding task deadlines without large computing bills are topics that have not been discussed much. Furthermore, with the increasing deployment of mobile edge servers, their centralized management would cause certain performance issues. In order to address these challenges, we firstly apply peer-to-peer networks to manage geo-distributed mobile edge servers. Secondly, we propose a new deadline-aware and cost-effective offloading approach, which aims to improve the offloading efficiency for vehicles and allows additional tasks to meet their deadlines. The proposed approach was validated for its feasibility and efficiency by means of extensive experiments, which are presented in this paper.
KW - Computation offloading
KW - Cost-effectiveness
KW - Deadline
KW - Decentralization
KW - Edge computing
KW - Cost effectiveness
KW - Efficiency
KW - Mobile telecommunication systems
KW - Quality of service
KW - Centralized management
KW - Computational workload
KW - Performance issues
KW - Quality of experience (QoE)
KW - Resource limitations
KW - Peer to peer networks
U2 - 10.1016/j.sysarc.2019.02.001
DO - 10.1016/j.sysarc.2019.02.001
M3 - Journal article
VL - 94
SP - 1
EP - 13
JO - Journal of Systems Architecture
JF - Journal of Systems Architecture
SN - 1383-7621
ER -