Efficient Orchestration Mechanisms for Congestion Mitigation in NFV: Models and Algorithms

Network Functions Virtualization (NFV) has recently gained momentum among network operators as a means to share their physical infrastructure among virtual operators, which can independently compose and configure their communication services. However, the spatio-temporal correlation of traffic demands and computational loads can result in high congestion and low network performance for virtual operators, thus leading to service level agreement breaches. In this paper, we analyze the congestion resulting from the sharing of the physical infrastructure and propose innovative orchestration mechanisms based on both centralized and distributed approaches, aimed at unleashing the potential of the NFV technology. In particular, we first formulate the network functions composition problem as a non-linear optimization model to accurately capture the congestion of physical resources. To further simplify the network management, we also propose a dynamic pricing strategy of network resources, proving that the resulting system achieves a stable equilibrium in a completely distributed fashion, even when all virtual operators independently select their best network configuration. Numerical results show that the proposed approaches consistently reduce resource congestion. Furthermore, the distributed solution well approaches the performance that can be achieved using a centralized network orchestration system.

[1]  Athanasios V. Vasilakos,et al.  A Survey on Service-Oriented Network Virtualization Toward Convergence of Networking and Cloud Computing , 2012, IEEE Transactions on Network and Service Management.

[2]  J. Goodman Note on Existence and Uniqueness of Equilibrium Points for Concave N-Person Games , 1965 .

[3]  Wolfgang Kellerer,et al.  Network virtualization: a hypervisor for the Internet? , 2012, IEEE Communications Magazine.

[4]  Raj Jain,et al.  Network virtualization and software defined networking for cloud computing: a survey , 2013, IEEE Communications Magazine.

[5]  Raouf Boutaba,et al.  Virtual Network Embedding with Coordinated Node and Link Mapping , 2009, IEEE INFOCOM 2009.

[6]  Barbara Panicucci,et al.  Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems , 2013, IEEE Transactions on Services Computing.

[7]  Jan Broeckhove,et al.  Network Aware Scheduling for Virtual Machine Workloads with Interference Models , 2015, IEEE Transactions on Services Computing.

[8]  Eitan Altman,et al.  A game theoretic framework for joint routing and pricing in networks with elastic demands , 2009, VALUETOOLS.

[9]  Martin Stiemerling,et al.  Resilient deployment of virtual network functions , 2013, 2013 5th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT).

[10]  Christos H. Papadimitriou,et al.  Worst-case equilibria , 1999 .

[11]  Raouf Boutaba,et al.  ViNEYard: Virtual Network Embedding Algorithms With Coordinated Node and Link Mapping , 2012, IEEE/ACM Transactions on Networking.

[12]  Jianping Wang,et al.  Optimization Models for Congestion Mitigation in Virtual Networks , 2014, 2014 IEEE 22nd International Conference on Network Protocols.

[13]  Navin Mani Upadhyay,et al.  Creation of virtual node, virtual link and managing them in network virtualization , 2011, 2011 World Congress on Information and Communication Technologies.

[14]  Ariel Orda,et al.  Competitive routing in multiuser communication networks , 1993, TNET.

[15]  Symeon Papavassiliou,et al.  Efficient Resource Mapping Framework over Networked Clouds via Iterated Local Search-Based Request Partitioning , 2013, IEEE Transactions on Parallel and Distributed Systems.

[16]  Xavier Hesselbach,et al.  Virtual Network Embedding: A Survey , 2013, IEEE Communications Surveys & Tutorials.

[17]  Sampath Rangarajan,et al.  Radio access network virtualization for future mobile carrier networks , 2013, IEEE Communications Magazine.

[18]  Ahmed Karmouch,et al.  VCG auction-based approach for efficient Virtual Network embedding , 2013, 2013 IFIP/IEEE International Symposium on Integrated Network Management (IM 2013).

[19]  Ilenia Tinnirello,et al.  Wireless MAC processors: Programming MAC protocols on commodity Hardware , 2012, 2012 Proceedings IEEE INFOCOM.

[20]  Xiang Cheng,et al.  Virtual network embedding through topology-aware node ranking , 2011, CCRV.

[21]  C. Buyukkoc,et al.  Software-Defined Networks for Future Networks and Services , 2014 .

[22]  Minlan Yu,et al.  Rethinking virtual network embedding: substrate support for path splitting and migration , 2008, CCRV.

[23]  Dimitri P. Bertsekas,et al.  Data Networks , 1986 .

[24]  Yong Zhu,et al.  Algorithms for Assigning Substrate Network Resources to Virtual Network Components , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[25]  Eitan Altman,et al.  Competitive routing in networks with polynomial costs , 2002, IEEE Trans. Autom. Control..

[26]  Giuseppe Bianchi,et al.  OpenState: programming platform-independent stateful openflow applications inside the switch , 2014, CCRV.

[27]  Ahmed Karmouch,et al.  Decomposition Approaches for Virtual Network Embedding With One-Shot Node and Link Mapping , 2015, IEEE/ACM Transactions on Networking.

[28]  Mikkel Thorup,et al.  Internet traffic engineering by optimizing OSPF weights , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[29]  Xavier Hesselbach,et al.  Energy Efficient Virtual Network Embedding , 2012, IEEE Communications Letters.

[30]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[31]  Aditya Akella,et al.  OpenNF: enabling innovation in network function control , 2015, SIGCOMM 2015.