Joint VNF Load Balancing and Service Auto-Scaling in NFV with Multimedia Case Study

The evolution of 5G key enabler technologies, such as SDN and NFV, has brought Network Operators attention to procure an efficient service delivery mechanism on each possible computing infrastructure PoP. Therefore, it is trivial to leverage service management and orchestration functionalities that operate in harmony since they may have significant impact on each others performance. In this paper, we investigate joint Load balancing and auto-scaling of service instances being provisioned on computing infrastructure in edge or cloud. We address the necessity and challenges of designing the Load balancing algorithm and scale decision making policy, aware of one another, through several practical scenarios. It is demonstrated that not only change in VNF load balancing method may deteriorate scaling Quality of Decision-making, but also scaling policy must be selected according to how load balancing unit distributes traffic among VNFs. We use Multimedia signalling service delivery in NFV environment as a case study, and aforementioned solution is implemented using management and orchestration of XeniumNFV open-source tool.