TY - JOUR
T1 - Joint optimization of service function placement and flow distribution for service function chaining
AU - Jang, Insun
AU - Suh, Dongeun
AU - Pack, Sangheon
AU - Dán, György
N1 - Funding Information:
Manuscript received April 1, 2017; revised September 12, 2017; accepted September 25, 2017. Date of publication October 25, 2017; date of current version December 1, 2017. This work was supported in part by the NRF of Korea Grant funded by the Korean Government (MSIT) under Grant NRF-2014R1A2A1A12066986 and in part by IITP Grant funded by the Korea government (MSIT) under Grant 2017-0-00195. This paper was presented at the IEEE Netsoft 2016, Seoul, South Korea, June 2016 [13]. (Corresponding author: Sangheon Pack.) I. Jang, D. Suh, and S. Pack are with the School of Electrical Engineering, Korea University, Seoul, South Korea (e-mail: zerantoss@korea.ac.kr; fever1989@korea.ac.kr; shpack@korea.ac.kr).
Publisher Copyright:
© 1983-2012 IEEE.
PY - 2017/11
Y1 - 2017/11
N2 - In this paper, we consider the problem of optimal dynamic service function (SF) placement and flow routing in a SF chaining (SFC) enabled network. We formulate a multi-objective optimization problem to maximize the acceptable flow rate and to minimize the energy cost for multiple service chains. We transform the multi-objective optimization problem into a single-objective mixed integer linear programming (MILP) problem, and prove that the problem is NP-hard. We propose a polynomial time algorithm based on linear relaxation and rounding to approximate the optimal solution of the MILP. Extensive simulations are conducted to evaluate the effects of the energy budget, the network topology, and the amount of server resources on the acceptable flow rate. The results demonstrate that the proposed algorithm can achieve near-optimal performance and can significantly increase the acceptable flow rate and the service capacity compared to other algorithms under an energy cost budget.
AB - In this paper, we consider the problem of optimal dynamic service function (SF) placement and flow routing in a SF chaining (SFC) enabled network. We formulate a multi-objective optimization problem to maximize the acceptable flow rate and to minimize the energy cost for multiple service chains. We transform the multi-objective optimization problem into a single-objective mixed integer linear programming (MILP) problem, and prove that the problem is NP-hard. We propose a polynomial time algorithm based on linear relaxation and rounding to approximate the optimal solution of the MILP. Extensive simulations are conducted to evaluate the effects of the energy budget, the network topology, and the amount of server resources on the acceptable flow rate. The results demonstrate that the proposed algorithm can achieve near-optimal performance and can significantly increase the acceptable flow rate and the service capacity compared to other algorithms under an energy cost budget.
KW - Acceptable flow rate
KW - Energy cost
KW - Flow-compensatory rounding based placement
KW - Service function chaining
UR - http://www.scopus.com/inward/record.url?scp=85032446560&partnerID=8YFLogxK
U2 - 10.1109/JSAC.2017.2760162
DO - 10.1109/JSAC.2017.2760162
M3 - Article
AN - SCOPUS:85032446560
SN - 0733-8716
VL - 35
SP - 2532
EP - 2541
JO - IEEE Journal on Selected Areas in Communications
JF - IEEE Journal on Selected Areas in Communications
IS - 11
M1 - 8082507
ER -