Computation Offloading with Wardrop Routing Game in Multi-UAV-aided MEC Environment
The combination of Unmanned aerial vehicles(UAVs)and multi-access edge computing(MEC)technology breaks the limitations of traditional terrestrial communications,which has become a significant approach to solve the tasks offloading pro-blem in MEC.Due to the limited computing resources and energy that a single UAV can provide,the tasks offloading problem in a multi-UAV-assisted MEC environment is considered to cope with the growing network scale.Based on the problem definition,to obtain the offloading strategies in the equilibrium and optimal states and analyze the gap between them quantitatively,the tasks offloading process can be viewed as a Wardrop routing game on parallel links with player-specific latency functions.Since the equilibrium solution is difficult to compute,a new potential function is introduced to convert the equilibrium problem into a mini-mization problem of potential function.Simultaneously,the Frank-Wolfe algorithm is used to obtain the equilibrium and the opti-mal offloading strategies finally.At each iteration of this algorithm,the objective function is linearized,and the feasible direction is thus obtained by solving the linear programming,along which a one-dimensional search is performed in the feasible domain.Simu-lation experiments verify that the equilibrium offloading strategy based on the Wardrop routing game on parallel links can effec-tively reduce the model's total cost compared with other benchmark methods,and the ratio between the total costs caused by the equilibrium and optimal offloading strategies is about 1.
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