Prioritized Deployment of Dynamic Service Function Chains

被引:13
|
作者
Farkiani, Behrooz [1 ]
Bakhshi, Bahador [1 ]
MirHassani, S. Ali [2 ]
Wauters, Tim [3 ]
Volckaert, Bruno [3 ]
De Turck, Filip [3 ]
机构
[1] Amirkabir Univ Technol, Dept Comp Engn, Tehran 1591634311, Iran
[2] Amirkabir Univ Technol, Dept Math & Comp Sci, Tehran 1591634311, Iran
[3] Univ Ghent, Dept Informat Technol, B-9000 Ghent, Belgium
关键词
Heuristic algorithms; Servers; Bandwidth; Service function chaining; Virtualization; Process control; Linear programming; network function virtualization; priority; exact solution; FUNCTION PLACEMENT; NETWORK FUNCTIONS; ENERGY-EFFICIENT; ORCHESTRATION; MIGRATION; COST;
D O I
10.1109/TNET.2021.3055074
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Service Function Chaining and Network Function Virtualization are enabling technologies that provide dynamic network services with diverse QoS requirements. Regarding the limited infrastructure resources, service providers need to prioritize service requests and even reject some of low-priority requests to satisfy the requirements of high-priority services. In this paper, we study the problem of deployment and reconfiguration of a set of chains with different priorities with the objective of maximizing the service provider's profit; wherein, we also consider management concerns including the ability to control the migration of virtual functions. We show the problem is more practical and comprehensive than the previous studies, and propose an MILP formulation of it along with two solving algorithms. The first algorithm is a fast polynomial-time heuristic that calculates an initial feasible solution to the problem. The second algorithm is an exact method that utilizes the initial feasible solution to achieve the optimal solution quickly. Using extensive simulations, we evaluate the algorithms and show the proposed heuristic can find a feasible solution in at least 83% of the simulation runs in less than 7 seconds, and the exact algorithm can achieve 25% more profit 8 times faster than the state-of-the-art MILP solving methods.
引用
收藏
页码:979 / 993
页数:15
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