Task unloading method for selection and energy consumption optimization of trusted edge server

The invention requests to protect a task unloading method for selection and energy consumption optimization of a trusted edge server. The task unloading method comprises the following main steps: S1, constructing a system model according to related information data of the server and equipment; s2, performing standardization processing on the task information and the MEC cache task classes, performing FCM clustering, and performing coding matching to obtain MEC servers which are preferentially selected to be unloaded by each task class; s3, performing measurement analysis on the credibility relationship in the S2 by adopting a set pair analysis theory; and S4, according to a result of S2, dividing the task into sub-tasks, performing task unloading in the multi-access-point network, and calculating energy consumption. Through a WOA algorithm, energy consumption is optimized in a tolerant time delay range, and an unloading decision of each subtask is obtained; and S5, unloading the subtasks to the corresponding