Optimal pricing and capacity partitioning for tiered access service in virtual networks

Many Internet service providers offer some forms of tiered access service to meet diverse demands of users and to improve the efficiency of network resources. A number of studies have attempted to develop a practical economic model for tiered service, but failed to effectively capture the complex interaction between pricing, resource allocation, and user utility in tiered service. In the current single-layered Internet architecture, since different types of services share the same network resources, it is fundamentally difficult to guarantee service quality differentiation. Therefore, in this paper, to remedy the deficiency of the existing tiered service models and to overcome the inherent limitation of the Internet architecture, we propose a network architectural solution that utilizes network virtualization technology as a means of providing tiered service. We first develop an economic model for the tiered service based on virtual networks, which accounts for the user subscription dynamics taking into account the impacts of access rate regulation. Then, we find the optimal pricing and capacity partitioning by addressing the revenue maximization problem in the tiered service. Numerical results show that the tiered service based on virtual networks can be more profitable than the non-tiered service under proper pricing and capacity partitioning.

[1]  Qian Wang,et al.  On the Viability of Paris Metro Pricing for Communication and Service Networks , 2010, 2010 Proceedings IEEE INFOCOM.

[2]  Djamal Zeghlache,et al.  Virtual network provisioning across multiple substrate networks , 2011, Comput. Networks.

[3]  Michael Devetsikiotis,et al.  An overview of pricing concepts for broadband IP networks , 2000, IEEE Communications Surveys & Tutorials.

[4]  Jonathan S. Turner,et al.  Diversifying the Internet , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

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

[6]  Robin Mason,et al.  Internet service classes under competition , 2000, IEEE Journal on Selected Areas in Communications.

[7]  Raghuram Iyengar,et al.  Nonlinear pricing , 2022 .

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

[9]  Bruno Tuffin,et al.  A mathematical model of the Paris Metro Pricing scheme for charging packet networks , 2004, Comput. Networks.

[10]  George N. Rouskas,et al.  On Bandwidth Tiered Service , 2009, IEEE/ACM Transactions on Networking.

[11]  Shaolei Ren,et al.  User subscription dynamics and revenue maximization in communications markets , 2011, 2011 Proceedings IEEE INFOCOM.

[12]  David Besanko,et al.  Logit Demand Estimation Under Competitive Pricing Behavior: An Equilibrium Framework , 1998 .

[13]  Mostafa H. Ammar,et al.  Dynamic Topology Configuration in Service Overlay Networks: A Study of Reconfiguration Policies , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[14]  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.

[15]  Chip Elliott,et al.  GENI - global environment for network innovations , 2008, LCN.

[16]  Yiwei Thomas Hou,et al.  Service overlay networks: SLAs, QoS, and bandwidth provisioning , 2003, TNET.

[17]  Scott Shenker,et al.  Overcoming the Internet impasse through virtualization , 2005, Computer.

[18]  Raouf Boutaba,et al.  Network virtualization: state of the art and research challenges , 2009, IEEE Communications Magazine.

[19]  George N. Rouskas,et al.  An Economic Model for Pricing Tiered Network Services , 2009, ICC.

[20]  Andrew M. Odlyzko,et al.  Paris metro pricing for the internet , 1999, EC '99.

[21]  Jean C. Walrand,et al.  Pricing differentiated Internet services , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[22]  W. Lieberman.  The Theory and Practice of Revenue Management , 2005 .

[23]  Anja Feldmann,et al.  The Price of Specificity in the Age of Network Virtualization , 2012, 2012 IEEE Fifth International Conference on Utility and Cloud Computing.

[24]  John C.-I. Chuang,et al.  Innovations and upgrades in virtualized network architectures , 2010, NetEcon.

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

[26]  Zhi-Li Zhang,et al.  Dynamics of competition between incumbent and emerging network technologies , 2008, NetEcon '08.

[27]  David E. Culler,et al.  PlanetLab: an overlay testbed for broad-coverage services , 2003, CCRV.

[28]  Ravi Jain,et al.  Analysis of Paris Metro Pricing Strategy for QoS with a Single Service Provider , 2001, IWQoS.

[29]  Lixin Gao,et al.  How to lease the internet in your spare time , 2007, CCRV.

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

[31]  Anja Feldmann,et al.  Optimizing Long-Lived CloudNets with Migrations , 2012, 2012 IEEE Fifth International Conference on Utility and Cloud Computing.

[32]  Gustavo de Veciana,et al.  On flat-rate and usage-based pricing for tiered commodity internet services , 2008, 2008 42nd Annual Conference on Information Sciences and Systems.