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Network Function Virtualization (NFV) enables mobile operators to virtualizetheir network entities as Virtualized Network Functions (VNFs), offeringfine-grained on-demand network capabilities. VNFs can be dynamicallyscale-in/out to meet the performance requirements for future 5G networks.However, designing an auto-scaling algorithm with low operation cost and lowlatency while considering the capacity of legacy network equipment is achallenge. In this paper, we propose a VNF Dynamic Auto Scaling Algorithm(DASA) considering the tradeoff between performance and operation cost. We alsodevelop an analytical model to quantify the tradeoff and validate the analysisthrough extensive simulations. The system is modeled as a queueing model whilelegacy network equipment is considered as a reserved block of servers. The VNFinstances are powered on and off according to the number of job requests. Theresults show that the proposed DASA can significantly reduce operation costgiven the latency upper-bound. Moreover, the models provide a quick way toevaluate the cost-performance tradeoff without wide deployment, which can savecost and time.

Design and Analysis of Dynamic Auto Scaling Algorithm (DASA) for 5G Mobile Networks