4.5 Article

On Efficient Service Function Chaining in Hybrid Software Defined Networks

Journal

IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
Volume 19, Issue 2, Pages 1614-1628

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSM.2021.3123502

Keywords

Network function virtualization; service provisioning; software-defined networking; hybrid SDN

Funding

  1. National Natural Science Foundation, China [61907036, 51905457]
  2. SWPU of Science and Technology Higher Learning Innovation Ability Enhancement, China [2019CXTD06]
  3. Collaboration Project of University and Nanchong, China [19SXHZ0018]

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This paper emphasizes the importance of using network function virtualization (NFV) and software-defined networking (SDN) for service function chain (SFC) provisioning. By jointly optimizing SDN deployment and VNF placement, a tradeoff can be made between capital expenditures (CAPEX) and operating expenses (OPEX), and an appropriate SDN deployment rate can be determined for network operators.
To minimize operating expenses (OPEX) and enhance flexibility for network service provisioning, network function virtualization (NFV) is used to chain an ordered sequence of virtualized network functions (VNFs), also known as service function chain (SFC), which can be placed on commodity servers. As a highly complementary to NFV, software-defined networking (SDN) can offer an agile way of VNF orchestration with the capability of fine-granularity network control over flows. However, one-step migration to SDN is impossible in ISP networks. Thus, in this paper we resort to hybrid SDN to implement SFC provisioning. By jointly optimizing SDN deployment that largely determines capital expenditures (CAPEX) and VNF placement that decides OPEX, we manage to make a tradeoff between CAPEX and OPEX, and to find out an appropriate SDN deployment rate for network operator. We first formulate the problem as an integer linear programming (ILP) model P, then, reformulate it with column generation technique and decomposition theory to develop a distributed approximation algorithm CGPD which obtains a tight upper bound of optimal solution to P. In order to better decrease CAPEX, a dynamic programming-based heuristic EOES giving importance to effective resource sharing is further designed based on a hidden Markov model. The simulation results indicate that, the difference between P and CGPD is marginal. CGPD outperforms EOES in terms of total cost, average delay and bandwidth utilization, and EOES on the other hand demands 20% SDN deployment rate which is half of that of CGPD.

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