JOURNAL ARTICLE

MEC computing resource-constrained Stackelberg game computing offloading method

Abstract

Mobile Edge Computing (MEC) effectively improves user service quality by sinking the computing center to the edge of the neighboring terminal users. However, insufficient MEC cloud computing resources have created many obstacles to the promotion and application of edge cloud technology. Aiming at the problem of MEC computing offloading and resource allocation under the condition of limited computing resources, this paper builds a Stackelberg master-slave game model to conduct "cloud-side" interactive analysis on MEC revenue and user service quality, and uses differentiated pricing strategies to strengthen the constraints on offloading strategies. Obtain the largest MEC revenue unloading ratio. Finally, the optimal simulated annealing algorithm is used to iterate the optimal allocation strategy of MEC computing resources. Simulations show that the solution in this paper can effectively improve the MEC rate of return on the basis of optimizing the quality of user experience. This method has guiding significance for the study of unloading problems under resource-constrained conditions.

Keywords:
Stackelberg competition Cloud computing Computer science Mobile edge computing Resource allocation Edge computing Distributed computing Utility computing Quality of service Computation offloading Mobile cloud computing Resource management (computing) Revenue Mathematical optimization Computer network Cloud computing security Operating system

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Topics

IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications

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