A prediction-based dynamic resource management approach for network virtualization

• Published in: 2017 13th International Conference on Network and Service Management (CNSM) pp. 1 - 5
• Main Authors: Jiacong Li, Ying Wang, Zhanwei Wu, Sixiang Feng, Xuesong Qiu
• Format: Conference Proceeding
• Language: English
• Published: IFIP 01-11-2017
• Subjects: double exponential smoothing; Dynamic scheduling; Heuristic algorithms; network virtualization; Peer-to-peer computing; Prediction algorithms; prediction-based resource management; Resource management; Substrates; Virtualization
• ISSN: 2165-963X
• DOI: 10.23919/CNSM.2017.8255980

In network virtualization environment, multiple virtual networks share the same resource of a physical network. Since the physical resources of a substrate network is limited, it is necessary to improve the utilization of physical resources. Considering the resource requirement of a virtual network may change over its lifetime, we propose a prediction-based resource management mechanism. To increase the utilization of the substrate network, we can adjust the resource allocated to the virtual network based on the result of prediction. Additionally, in order to avoid the result of prediction deviates from the real requirement, we compare our prediction result with the collection of the resource utilization at real time to ensure the correctness of our result. The simulation results show that our approach can increase the utilization of the physical resource and improve the virtual network acceptance ratio while ensuring the requirement of the virtual networks.