Customizing service path based on polymorphic routing model in future networks

The current Internet has evolved during the last decade to a global provider of diverse applications. However, the underlying structure of routing and addressing has not evolved in the same pace and is somewhat inflexible. How to provide diverse routing services, support emerging communication paradigms based on limited and definite network resources has become an urgent challenge. This paper investigates the adaptive matching between routing and application through network function decomposition and composition, and proposes a polymorphic routing model to support diverse applications and emerging communication paradigms. The model splits complex routing functions into its constituents, and derives customized routing mechanisms supporting various applications by composing the routing constituents. The derivation process is modeled as a Markov Decision Process (MDP), and a polymorphic derivation algorithm is also proposed to derive customized routing instances for diverse applications. The model enables the network to self-adjust routing services dynamically to adapt to the different requirements of applications, supports coexistence of multiple routing modes and communication paradigms, and provides a feasible solution for the network compatibility and evolvement. We describe the key design and demonstrate the feasibility of polymorphic derivation by simulations. We also present case studies that demonstrate key functionalities the polymorphic routing model enables.

[1]  Franco Davoli,et al.  The dark side of network functions virtualization: A perspective on the technological sustainability , 2017, 2017 IEEE International Conference on Communications (ICC).

[2]  Byrav Ramamurthy,et al.  The Case for Using Content-Centric Networking for Distributing High-Energy Physics Software , 2017, 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS).

[3]  Nick McKeown,et al.  OpenFlow: enabling innovation in campus networks , 2008, CCRV.

[4]  Scott Shenker,et al.  A data-oriented (and beyond) network architecture , 2007, SIGCOMM '07.

[5]  Schahram Dustdar,et al.  Quality-aware service-oriented data integration: requirements, state of the art and open challenges , 2012, SGMD.

[6]  Hongke Zhang,et al.  RACSMI: RL-based access control for identifier locator separation mapping based mobile internet , 2015, 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC).

[7]  Julong Lan,et al.  可重构信息通信基础网络端到端模型的研究与探索 (Research on End-to-End Model of Reconfigurable Information Communication Basal Network) , 2017, 计算机科学.

[8]  Hongke Zhang,et al.  Decoupling the design of identifier-to-locator mapping services from identifiers , 2011, Comput. Networks.

[9]  Ben J. A. Kröse,et al.  Learning from delayed rewards , 1995, Robotics Auton. Syst..

[10]  Seungmin Rho,et al.  Traffic engineering in software-defined networking: Measurement and management , 2016, IEEE Access.

[11]  Paolo Giaccone,et al.  Efficient caching through stateful SDN in named data networking , 2018, Trans. Emerg. Telecommun. Technol..

[12]  Julong Lan,et al.  Providing personalized converged services based on flexible network reconfiguration , 2010, Science China Information Sciences.