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Joint optimization of computation cost and delay for task offloading in vehicular fog networks
Author(s) -
Li Haotian,
Li Xujie,
Wang Weiguo
Publication year - 2020
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.3818
Subject(s) - computer science , computation offloading , latency (audio) , mathematical optimization , computation , resource allocation , construct (python library) , convergence (economics) , task (project management) , optimization problem , distributed computing , lagrange multiplier , edge computing , computer network , algorithm , embedded system , internet of things , engineering , telecommunications , mathematics , systems engineering , economics , economic growth
The vehicles equipped with computing devices can provide computing services in vehicular fog networks, thereby reducing latency and improving system efficiency. Hence, we face with the problem of how to select vehicles for the computation offloading of the task. In this paper, we jointly consider the delay and cost, and study the resource allocation problem of multivehicles users. First of all, we construct a hierarchical offloading model, use mathematical method to construct consumption function of the system, and generate a convex optimization problem with inequality constraints. Then, we use Lagrange method to solve the problem and develop a low‐complexity algorithm to select vehicles, optimize the offloading ratio, and reduce the consumption of the system. Numerical results show that the algorithm has a fast convergence rate and good performance.