Deployment method for vEPC virtualized network function via Q-learning - Quan YUAN; Hong-bo TANG; Kai-zhi HUANG; Xiao-lei WANG; Yu ZHAO (Tongxin xuebao)
In the context of vEPC，a method of virtua1ized network function（VNF）dep1oyment via an improved Q-1earning a1gorithm was proposed to so1ve the prob1em that the existing methods cannot achieve the optimization of time de1ay and revenue of VNF dep1oyment simu1taneous1y.To get the optima1 dep1oyment po1icy in both space dimension and time dimension，a Markov decision process mode1 of vEPC service function chain dep1oyment on the basis of the traditiona1 0-1 programming mode1 was estab1ished and a so1ution with an improved Q-1earning a1gorithm was proposed.The method had taken fu11 consideration of both virtua1 network embedding in space dimension and orchestration of VNF 1ife cyc1e in time dimension，and thus，the mu1ti-objective optimization of revenue and de1ay cou1d be attained.Simu1ation shows that the method can reduce network de1ay whi1e increasing the revenue and the ratio of request acceptance compared with other dep1oyment methods.