Abstract
In Network Function Virtualization, the resource demand of the network service evolves with the change of network traffic. VNF dynamic migration has become an effective method to improve network performance. However, for the time-varying resource demand, how to minimize the long-term energy consumption of the network while guaranteeing the Service Level Agreement (SLA) is the key issue that lacks previous research. To tackle this dilemma, this paper proposes an energy-efficient reconfiguration algorithm for VNF based on short-term resource requirement prediction (RP-EDM). Our algorithm uses LSTM to predict VNF resource requirements in advance to eliminate the lag of dynamic migration and determines the timing of migration. RP-EDM eliminates SLA violations by performing VNF separation on potentially overloaded servers and consolidates low-load servers timely to save energy. Meanwhile, we consider the power consumption of servers when booting up, which is existing objectively, to avoid switching on/off the server frequently. The simulation results suggest that RP-EDM has a good performance and stability under machine learning models with different accuracy. Moreover, our algorithm increases the total service traffic by about 15% while ensuring a low SLA interruption rate. The total energy cost is reduced by more than 20% compared with the existing algorithms.
Highlights
In recent years, with the emergence of new network technologies and the growing customer demands, the business model of operators is undergoing a revolutionary change.Network Function Virtualization (NFV), which is a promising network technology in this revolution [1], decouples network functions from hardware so that they can run as software on Virtual Machines (VMs) of commodity servers
As the network slices run, traffic arrivals of each specific service fluctuate over time, which may result in the mismatch between Service Function Chain (SFC) resource requirements and resource availability of servers, which has an adverse effect on Quality of Service (QoS) and resource utilization [4]
Different types of Network Functions (NFs) making up the SFCs are deployed on the corresponding types of Virtual Network Function (VNF)
Summary
With the emergence of new network technologies and the growing customer demands, the business model of operators is undergoing a revolutionary change. When one certain VNF placement and resource allocation policy failed to meet the current network requirements, NFV Orchestrator (NFVO) provides reconfiguration for SFCs including vertical scaling, horizontal scaling, and dynamic migration. The major issue to be solved is to find a VNF reconfiguration strategy for time-varying traffic rate which minimizes energy consumption with less migration cost and ensuring SLA simultaneously. We consider the boot-up energy cost of infrastructures to establish a more accurate energy consumption model; In consideration of the real SFC request scenarios, we use a time-varying traffic dataset. We adopt LSTM models to predict the resource demand of VNFs in short term and make use of the prediction result, making it possible to migrate VNF in advance proactively in certain timing; We propose the RP-EDM algorithm to minimize the energy consumption of the network while considering SLA. We simulate our algorithm using different prediction models to verify the superiority of our proposed strategy
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
