期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2020
卷号：98
期号：13
页码：2595-2605
出版社：Journal of Theoretical and Applied
摘要：Network technologies are dealing with a massive urge to break through the fundamental endorsements of networks. Software-Defined Networking (SDN) has been leading cloud Data Centres (DC's) which states with different policy adaptation for ensuring resource management, concerning about Network Virtualization (NV) performance that is capable of finding the related hardware components to map a Virtual Machine (VM) or a virtual link which represents Virtual Network Embedding (VNE) problem. To overcome the VNE problems our work as proposed a Finite Horizon Markov Decision Process Based Fuzzy Optimization. Fuzzy inference provides an linguistic variables and set of rules to obtain best policy from the available cloud resource and predicts the execution cost for every network function virtualization. This stage also deals with uncertainities and imprecision.Based on the priority and schedulable ability the Finite Horizon Markov Decision Process dynamically allocates the resource for NFV components. Thus, our work obtains a substantial amount of energy utilization by optimizing the use of local host services and will therefore provide greater policy control for physical DCs.
