TY - JOUR
T1 - Reconfiguration in network slicing-optimizing the profit and performance
AU - Wang, Gang
AU - Feng, Gang
AU - Quek, Tony Q.S.
AU - Qin, Shuang
AU - Wen, Ruihan
AU - Tan, Wei
N1 - Funding Information:
Manuscript received July 20, 2018; revised December 12, 2018; accepted February 5, 2019. Date of publication February 15, 2019; date of current version June 10, 2019. This work is supported in part by the National Natural Science Foundation of China under Grant 61631004, 61871099, the SUTD-ZJU Research Collaboration under Grant SUTD-ZJU/RES/01/2016. The associate editor coordinating the review of this paper and approving it for publication was S. Secci. (Corresponding author: Gang Feng.) G. Wang, G. Feng, S. Qin, and R. Wen are with the National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731, China (e-mail: [email protected]; [email protected]; [email protected]; [email protected]).
Publisher Copyright:
© 2019 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - Network slicing enables diversified services to be accommodated by isolated slices in network function virtualization-enabled software-defined networks. To maintain satisfactory user experience and high profit for service providers in a dynamic environment, a slice may need to be reconfigured according to the varying traffic demand and resource availability. However, frequent reconfigurations incur certain cost and might cause service interruption. In this paper, we propose a hybrid slice reconfiguration (HSR) framework, where a fast slice reconfiguration (FSR) scheme reconfigures flows for individual slices at the time scale of flow arrival/departure, while a dimensioning slices with reconfiguration (DSR) scheme is occasionally performed to adjust allocated resources according to the time-varying traffic demand. In order to optimize the slice's profit, i.e., the total utility minus the resource consumption and reconfiguration cost, we formulate the problems for FSR and DSR, which are difficult to solve due to the discontinuity and non-convexity of the reconfiguration cost function. Hence, we approximate the reconfiguration cost function with L1 norm, which preserves the sparsity of the solution, thus facilitating restricting reconfigurations. Besides, we design an algorithm to schedule FSR and DSR, so that DSR is timely triggered according to the traffic dynamics and resource availability to improve the profit of slice. Furthermore, we extend HSR with a resource reservation mechanism, which reserves partial resources for near future traffic to reduce potential reconfigurations. Numerical results validate that our reconfiguration framework is effective in reducing reconfiguration overhead and achieving high profit for slices.
AB - Network slicing enables diversified services to be accommodated by isolated slices in network function virtualization-enabled software-defined networks. To maintain satisfactory user experience and high profit for service providers in a dynamic environment, a slice may need to be reconfigured according to the varying traffic demand and resource availability. However, frequent reconfigurations incur certain cost and might cause service interruption. In this paper, we propose a hybrid slice reconfiguration (HSR) framework, where a fast slice reconfiguration (FSR) scheme reconfigures flows for individual slices at the time scale of flow arrival/departure, while a dimensioning slices with reconfiguration (DSR) scheme is occasionally performed to adjust allocated resources according to the time-varying traffic demand. In order to optimize the slice's profit, i.e., the total utility minus the resource consumption and reconfiguration cost, we formulate the problems for FSR and DSR, which are difficult to solve due to the discontinuity and non-convexity of the reconfiguration cost function. Hence, we approximate the reconfiguration cost function with L1 norm, which preserves the sparsity of the solution, thus facilitating restricting reconfigurations. Besides, we design an algorithm to schedule FSR and DSR, so that DSR is timely triggered according to the traffic dynamics and resource availability to improve the profit of slice. Furthermore, we extend HSR with a resource reservation mechanism, which reserves partial resources for near future traffic to reduce potential reconfigurations. Numerical results validate that our reconfiguration framework is effective in reducing reconfiguration overhead and achieving high profit for slices.
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U2 - 10.1109/TNSM.2019.2899609
DO - 10.1109/TNSM.2019.2899609
M3 - Article
AN - SCOPUS:85071036099
SN - 1932-4537
VL - 16
SP - 591
EP - 605
JO - IEEE Transactions on Network and Service Management
JF - IEEE Transactions on Network and Service Management
IS - 2
M1 - 8642931
ER -