Effective resource provisioning for QoS-aware virtual networks in SDN

The emergence of the IoT, 5G and different modes of computing has introduced a new demand to tailor-made networks to support a wide spectrum of applications. Even though virtualizing networks and applying QoS to these networks are crucial, it is always challenging to achieve QoS, high accep­tance ratio, and cost effectiveness on provisioning virtual networks given the constrained resource of the underlying network. This paper introduces Delay Constraint Optimum Bandwidth Tree (DCOBT), which effectively satisfies the QoS requirement of virtual networks in terms of both end-to-end delay and bandwidth. We propose the QoS-aware Resource Provisioning (QRP) algorithm to determine DCOBT with less bandwidth consumption and superior load balancing. Using SDN as a key platform to implement QoS-aware virtual networks, this paper further proposes flow rule reduction using Destination Label Forwarding (DLF) to provision more virtual networks with less Ternary Content-Addressable Memory (TCAM) consumption. The evaluation results proved significant contribution on different aspects of resource provisioning for QoS-aware virtual networks with improved availability, scalability, and cost effectiveness.

[1]  Rob Sherwood,et al.  FlowVisor: A Network Virtualization Layer , 2009 .

[2]  Clarence Filsfils,et al.  The Segment Routing Architecture , 2014, 2015 IEEE Global Communications Conference (GLOBECOM).

[3]  H. Jonathan Chao,et al.  JumpFlow: Reducing flow table usage in software-defined networks , 2015, Comput. Networks.

[4]  Nadjib Aitsaadi,et al.  An enhanced Path Computation for Wide Area Networks based on Software Defined Networking , 2017, 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM).

[5]  Riccardo Trivisonno,et al.  Virtual Links Mapping in Future SDN-Enabled Networks , 2013, 2013 IEEE SDN for Future Networks and Services (SDN4FNS).

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

[7]  Srikanth Kandula,et al.  Achieving high utilization with software-driven WAN , 2013, SIGCOMM.

[8]  Amit Kumar,et al.  Provisioning a virtual private network: a network design problem for multicommodity flow , 2001, STOC '01.

[9]  Maurizio Naldi,et al.  Connectivity of Waxman topology models , 2005, Comput. Commun..

[10]  Lei Zhang,et al.  Provisioning virtual private networks in the hose model with delay requirements , 2005, 2005 International Conference on Parallel Processing (ICPP'05).

[11]  Raouf Boutaba,et al.  Virtual network embedding in software-defined networks , 2016, NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium.

[12]  Tolga Ovatman,et al.  Network-aware embedding of virtual machine clusters onto federated cloud infrastructure , 2016, J. Syst. Softw..

[13]  Min Zhu,et al.  B4: experience with a globally-deployed software defined wan , 2013, SIGCOMM.

[14]  Ali Ridha Mahjoub,et al.  Evolutionary algorithm for provisioning VPN trees based on pipe and hose workload models , 2011, 2011 Seventh International Conference on Natural Computation.

[15]  Riccardo Trivisonno,et al.  Virtual Link Mapping for delay critical services in SDN-enabled 5G networks , 2015, Proceedings of the 2015 1st IEEE Conference on Network Softwarization (NetSoft).

[16]  Amit Kumar,et al.  Algorithms for provisioning virtual private networks in the hose model , 2002, TNET.

[17]  Min Luo,et al.  QoS-aware virtualization-enabled routing in Software-Defined Networks , 2015, 2015 IEEE International Conference on Communications (ICC).

[18]  Cristina Cervello-Pastor,et al.  On the optimal allocation of virtual resources in cloud computing networks , 2013, IEEE Transactions on Computers.

[19]  J. Y. Yen Finding the K Shortest Loopless Paths in a Network , 1971 .

[20]  Albert G. Greenberg,et al.  A flexible model for resource management in virtual private networks , 1999, SIGCOMM '99.