TY - GEN
T1 - Dynamic auto scaling algorithm (DASA) for 5G mobile networks
AU - Ren, Yi
AU - Phung-Duc, Tuan
AU - Chen, Jyh-Cheng
AU - Yu, Zheng Wei
PY - 2016/1/1
Y1 - 2016/1/1
N2 - Network Function Virtualization (NFV) enables mobile operators to virtualize their network entities as Virtualized Network Functions (VNFs), offering fine-grained on-demand network capabilities. VNFs can be dynamically scale-in/out to meet the performance desire and other dynamic behaviors. However, designing the auto-scaling algorithm for desired characteristics with low operation cost and low latency, while considering the existing capacity of legacy network equipment, is not a trivial task. In this paper, we propose a VNF Dynamic Auto Scaling Algorithm (DASA) considering the tradeoff between performance and operation cost. We develop an analytical model to quantify the tradeoff and validate the analysis through extensive simulations. The results show that the DASA can significantly reduce operation cost given the latency upper-bound. Moreover, the models provide a quick way to evaluate the cost- performance tradeoff and system design without wide deployment, which can save cost and time.
AB - Network Function Virtualization (NFV) enables mobile operators to virtualize their network entities as Virtualized Network Functions (VNFs), offering fine-grained on-demand network capabilities. VNFs can be dynamically scale-in/out to meet the performance desire and other dynamic behaviors. However, designing the auto-scaling algorithm for desired characteristics with low operation cost and low latency, while considering the existing capacity of legacy network equipment, is not a trivial task. In this paper, we propose a VNF Dynamic Auto Scaling Algorithm (DASA) considering the tradeoff between performance and operation cost. We develop an analytical model to quantify the tradeoff and validate the analysis through extensive simulations. The results show that the DASA can significantly reduce operation cost given the latency upper-bound. Moreover, the models provide a quick way to evaluate the cost- performance tradeoff and system design without wide deployment, which can save cost and time.
KW - 5G
KW - Auto Scaling Algorithm
KW - Cloud Networks
KW - Modeling and Analysis
KW - Network Function Virtualization
KW - Virtualized EPC
UR - http://www.scopus.com/inward/record.url?scp=85015387179&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2016.7841759
DO - 10.1109/GLOCOM.2016.7841759
M3 - Conference contribution
AN - SCOPUS:85015387179
T3 - 2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings
BT - 2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 59th IEEE Global Communications Conference, GLOBECOM 2016
Y2 - 4 December 2016 through 8 December 2016
ER -