JIPS (한국정보처리학회)
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| 한글제목(Korean Title) |
An Offloading Scheduling Strategy with Minimized Power Overhead for Internet of Vehicles Based on Mobile Edge Computing |
| 영문제목(English Title) |
An Offloading Scheduling Strategy with Minimized Power Overhead for Internet of Vehicles Based on Mobile Edge Computing |
| 저자(Author) |
Bo He
Tianzhang Li
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| 원문수록처(Citation) |
VOL 17 NO. 03 PP. 0489 ~ 0504 (2021. 06) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
By distributing computing tasks among devices at the edge of networks, edge computing uses virtualization, distributed computing and parallel computing technologies to enable users dynamically obtain computing power, storage space and other services as needed. Applying edge computing architectures to Internet of Vehicles can effectively alleviate the contradiction among the large amount of computing, low delayed vehicle applications, and the limited and uneven resource distribution of vehicles. In this paper, a predictive offloading strategy based on the MEC load state is proposed, which not only considers reducing the delay of calculation results by the RSU multi-hop backhaul, but also reduces the queuing time of tasks at MEC servers. Firstly, the delay factor and the energy consumption factor are introduced according to the characteristics of tasks, and the cost of local execution and offloading to MEC servers for execution are defined. Then, from the perspective of vehicles, the delay preference factor and the energy consumption preference factor are introduced to define the cost of executing a computing task for another computing task. Furthermore, a mathematical optimization model for minimizing the power overhead is constructed with the constraints of time delay and power consumption. Additionally, the simulated annealing algorithm is utilized to solve the optimization model. The simulation results show that this strategy can effectively reduce the system power consumption by shortening the task execution delay. Finally, we can choose whether to offload computing tasks to MEC server for execution according to the size of two costs. This strategy not only meets the requirements of time delay and energy consumption, but also ensures the lowest cost. |
| 키워드(Keyword) |
Internet of Vehicles
Minimizing Power Overhead
Mobile Edge Computing
Optimization Model
Simulated Annealing Algorithm
Task Offloading
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| 파일첨부 |
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