Container cloud resource prediction based on APMSSGA-LSTM

Abstract

With the development and application of container cloud,the demand for high concurrency,high availability,high flexibility,and high flexibility of resources is becoming more and more intense.After investigating the current research status of container cloud resource prediction,a container cloud resource prediction model which using an adaptive probability multiselection strategy genetic algorithm (APMSSGA) to optimize the long short term memory network (LSTM) was proposed.The experimental results show that compared with the simple genetic algorithm (SGA),APMSSGA is more efficient in LSTM parameter optimal solution combination search,and the APMSSGA-LSTM model has higher prediction accuracy.

Keywords

• container cloud;resource prediction;long short term memory network;genetic algorithm