Wenbin Bi1, Fang Yu2, Ning Cao3,*, Russell Higgs4
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 165-180, 2022, DOI:10.32604/cmc.2022.027776
Abstract Load-time series data in mobile cloud computing of Internet of Vehicles (IoV) usually have linear and nonlinear composite characteristics. In order to accurately describe the dynamic change trend of such loads, this study designs a load prediction method by using the resource scheduling model for mobile cloud computing of IoV. Firstly, a chaotic analysis algorithm is implemented to process the load-time series, while some learning samples of load prediction are constructed. Secondly, a support vector machine (SVM) is used to establish a load prediction model, and an improved artificial bee colony (IABC) function is designed to enhance the learning ability… More >
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