Abstract
A mobile cloud computing (MCC) workflow task dynamic scheduling model is designed to improve the level of adaptation of MCC workflow task dynamic scheduling. The group decision model parameter set of MCC workflow task dynamic scheduling is constructed, the preference information of MCC workflow task flow is assembled and clustered using multi-scale and multi-scalar feature analysis methods, and the dynamic feature evolution clustering analysis model of MCC workflow task is constructed, the dynamic information flow regression parameters of MCC workflow task are obtained by partial least squares method, and the fuzzy clustering processing of MCC workflow task dynamic scheduling is realized according to each attribute The fuzzy clustering process of dynamic scheduling of MCC workflow tasks is realized according to the results of weight vector assignment. Finally, the dynamic adaptive scheduling of MCC workflow tasks is realized according to the information clustering results. The experimental findings indicate that the technique has an excellent dynamic distribution and strong comprehensive assessment capability during MCC workflow task scheduling, aiding in the adaptive assignment of MCC workflow tasks.
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