On the energy cost of robustness for green virtual network function placement in 5G virtualized infrastructures

Abstract Next generation 5G networks will rely on virtualized Data Centers (vDC) to host virtualized network functions on commodity servers. Such Network Function Virtualization (NFV) will lead to significant savings in terms of infrastructure cost and reduced management complexity. However, green strategies for networking and computing inside data centers, such as server consolidation or energy aware routing, should not negatively impact the quality and service level agreements expected from network operators. In this paper, we study how robust strategies that place virtual network functions (VNF) inside vDC impact the energy savings and the protection level against resource demand uncertainty. We propose novel optimization models that allow the minimization of the energy of the computing and network infrastructure which is hosting a set of service chains that implement the VNFs. The model explicitly provides for robustness to unknown or imprecisely formulated resource demand variations, powers down unused routers, switch ports and servers, and calculates the energy optimal VNF placement and network embedding also considering latency constraints on the service chains. We propose both exact and heuristic methods. Our experiments were carried out using the virtualized Evolved Packet Core (vEPC), which allows us to quantitatively assess the trade-off between energy cost, robustness and the protection level of the solutions against demand uncertainty. Our heuristic is able to converge to a good solution in a very short time, in comparison to the exact solver, which is not able to output better results in a longer run as demonstrated by our numerical evaluation. We also study the degree of robustness of a solution for a given protection level and the cost of additional energy needed because of the usage of more computing and network elements.

[1]  Fabio D'Andreagiovanni,et al.  A fast hybrid primal heuristic for multiband robust capacitated network design with multiple time periods , 2014, Appl. Soft Comput..

[2]  Melvyn Sim,et al.  The Price of Robustness , 2004, Oper. Res..

[3]  Ravindra K. Ahuja,et al.  Network Flows: Theory, Algorithms, and Applications , 1993 .

[4]  Constantine Caramanis,et al.  Theory and Applications of Robust Optimization , 2010, SIAM Rev..

[6]  Thomas Bauschert,et al.  Combined Virtual Mobile Core Network Function Placement and Topology Optimization with Latency Bounds , 2015, 2015 Fourth European Workshop on Software Defined Networks.

[7]  Stefano Coniglio,et al.  Virtual network embedding under uncertainty: Exact and heuristic approaches , 2015, 2015 11th International Conference on the Design of Reliable Communication Networks (DRCN).

[8]  Tarik Taleb,et al.  Cost analysis of initial deployment strategies for virtualized mobile core network functions , 2015, IEEE Communications Magazine.

[9]  Chadi Assi,et al.  Energy-Aware Placement and Scheduling of Network Traffic Flows with Deadlines on Virtual Network Functions , 2016, 2016 5th IEEE International Conference on Cloud Networking (Cloudnet).

[10]  Stephen J. Merrill,et al.  Random Perturbations of Dynamical Systems (M. I. Freidlin and A. D. Wentzell) , 1985 .

[11]  Arie M. C. A. Koster,et al.  Network planning under demand uncertainty with robust optimization , 2014, IEEE Communications Magazine.

[12]  Brunilde Sansò,et al.  Green Cloud Broker: On-line Dynamic Virtual Machine Placement Across Multiple Cloud Providers , 2016, 2016 5th IEEE International Conference on Cloud Networking (Cloudnet).

[13]  Andreas Kassler,et al.  A Power Efficient and Robust Virtual Network Functions Placement Problem , 2016, 2016 28th International Teletraffic Congress (ITC 28).

[14]  Xiuqi Li,et al.  Virtual machine consolidated placement based on multi-objective biogeography-based optimization , 2016, Future Gener. Comput. Syst..

[15]  Raouf Boutaba,et al.  On Orchestrating Virtual Network Functions in NFV , 2015, ArXiv.

[16]  Fabio D'Andreagiovanni,et al.  New Results about Multi-band Uncertainty in Robust Optimization , 2012, SEA.

[17]  Stefano Secci,et al.  Virtual network functions placement and routing optimization , 2015, 2015 IEEE 4th International Conference on Cloud Networking (CloudNet).

[18]  Andreas Kassler,et al.  Optimising for energy or robustness? Trade-offs for VM consolidation in virtualized datacenters under uncertainty , 2017, Optim. Lett..

[19]  Yun Chi,et al.  Packing light: Portable workload performance prediction for the cloud , 2013, 2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW).

[20]  Sujata Banerjee,et al.  ElasticTree: Saving Energy in Data Center Networks , 2010, NSDI.

[21]  Jean-Philippe Vial,et al.  Robust Optimization , 2021, ICORES.

[22]  Dimitri Papadimitriou.  New challenges in network optimization , 2016, 2016 IEEE 17th International Conference on High Performance Switching and Routing (HPSR).