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Mobility-Aware Mult...
Mobility-Aware Multiobjective Task Offloading for Vehicular Edge Computing in Digital Twin Environment
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- Cao, Bin (författare)
- Hebei Univ Technol, State Key Lab Reliabil & Intelligence Elect Equip, Tianjin 300130, Peoples R China.;Hebei Univ Technol, Sch Artificial Intelligence, Tianjin 300401, Peoples R China.
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- Li, Ziming (författare)
- Hebei Univ Technol, State Key Lab Reliabil & Intelligence Elect Equip, Tianjin 300130, Peoples R China.;Hebei Univ Technol, Sch Artificial Intelligence, Tianjin 300401, Peoples R China.
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- Liu, Xin (författare)
- Hebei Univ Technol, Sch Econ & Management, Tianjin 300401, Peoples R China.
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- Lv, Zhihan, Dr. 1984- (författare)
- Uppsala universitet,Institutionen för speldesign
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- He, Hua (författare)
- Hebei Univ Technol, Sch Sci, Tianjin 300401, Peoples R China.
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Hebei Univ Technol, State Key Lab Reliabil & Intelligence Elect Equip, Tianjin 300130, Peoples R China;Hebei Univ Technol, Sch Artificial Intelligence, Tianjin 300401, Peoples R China. Hebei Univ Technol, Sch Econ & Management, Tianjin 300401, Peoples R China. (creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2023
- 2023
- Engelska.
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Ingår i: IEEE Journal on Selected Areas in Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 0733-8716 .- 1558-0008. ; 41:10, s. 3046-3055
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- In vehicular edge computing (VEC), vehicle users (VUs) can offload their computation-intensive tasks to edge server (ES) that provides additional computation resources. Due to the edge server being closer to VUs, the propagation delay between the ESs and the VUs is lower compared to cloud computing. Applying digital twin to VEC allows for low-cost trial in task offloading. In real-word, the mobility of VUs cannot be ignored and the downlink delay in receiving process results from ES is related to the mobility of VUs. Therefore, a five-objective optimization model including downlink delay, computation delay, energy consumption, load balancing, and user satisfaction of the VUs is constructed. To solve the above model, an improved CMA-ES algorithm based on the guiding point (GP-CMA-ES) is proposed. When the number of VUs increases, the dimension of variables also increases. Therefore, a convergence-related variable grouping strategy based on the relationship detection between variables and objectives is proposed. The performance of algorithm GP-CMA-ES is compared with five algorithms in the digital twin environment.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Digital twin
- vehicular networks
- edge computing
- task offloading
- covariance matrix adaptation
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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