SCM: A method to improve network service layout efficiency with network evolution
December
SCM: A method to improve network service layout efficiency with network evolution
Qi Zhao 0 1
Chuanhao Zhang 1
Zheng Zhao 1
0 Computer Science and Technology College, Jilin University , Changchun, Jilin , China , 2 Department of Public Security Technology, Railway Police College , Zhengzhou, Henan , China , 3 National Digital Switching System Engineering & Technological R&D Center , Zhengzhou, Henan , China , 4 Department of Network Engineering, Zhengzhou Science and Technology Institute , Zhengzhou, Henan , China
1 Editor: Xiangxiang Zeng, Xiamen University , CHINA
Network services are an important component of the Internet, which are used to expand network functions for third-party developers. Network function virtualization (NFV) can improve the speed and flexibility of network service deployment. However, with the evolution of the network, network service layout may become inefficient. Regarding this problem, this paper proposes a service chain migration (SCM) method with the framework of ªsoftware defined network + network function virtualizationº (SDN+NFV), which migrates service chains to adapt to network evolution and improves the efficiency of the network service layout. SCM is modeled as an integer linear programming problem and resolved via particle swarm optimization. An SCM prototype system is designed based on an SDN controller. Experiments demonstrate that SCM could reduce the network traffic cost and energy consumption efficiently.
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Data Availability Statement: All data are available
within the paper.
Funding: This work is supported by the Ministry of
Public Security Technical Research Plan under
Grant No.2016JSYJB38 (to CZ) and the Scientific
and Technological Research Program under Grant
No.172102210441 (to CZ). The funders had no
role in study design, data collection and analysis,
decision to publish, or preparation of the
manuscript.
Competing interests: The authors have declared
that no competing interests exist.
Introduction
Middleboxes [1], hardware-based network services, are widely deployed in the Internet and
being recognized as important components of networks, such as their uses as firewalls,
intrusion detection systems/intrusion prevention systems (IDS/IPS), load balancers, agencies,
network address translators (NAT), and wide area network (WAN) optimizers etc. Service chains
[2] are created by combining these service instances according to network policies and user
requirements. Service chains satisfy various needs of users and provide value-added services to
networks.
The flexibility and expansibility of the service deployment can be improved by network
function virtualization (NFV) [3±5]. In NFV, special hardware middleboxes are replaced by
virtual services, thus service chain customization and dynamical creation can be achieved. In
addition, software defined networks (SDN) [6±8] are widely used to orchestrate network
services according to policies and control traffic to pass special service chains [9±12]. The "SDN
+NFV" network paradigm [13] provides a flexible, scalable, and adaptable architecture for
deploying virtual services and creates new opportunities for service chain management.
Based on the "SDN+NFV" architecture, there has been extensive researches about service
chain deployment [12, 14±17]. In these studies, service chains are deployed with consideration
of the quality of service, resource allocation, and network security. However, these service
chain placement approaches only consider the current network static status, and the changes
of the network state are neglected. With network evolution, some old flows may disappear and
new flows may arise. Therefore, the status of network changes and the service chain
deployment may lose optimality with network evolution, resulting in a waste of network resources
and energy. Moreover, the quality of services will decrease due to the degraded service chain
layout.
This problem is difficult to resolve in service chain deployment due to the limited ability to
anticipate the evolution of network states. However, if the deployment of service chains is
dynamic throughout their life cycles, the network resource allocation can be adjusted
dynamically to adapt to the changing network status. In this paper, a service chain migration (SCM)
framework is proposed to address this problem, in which service chains are migrated
dynamically to adapt to network evolution. SCM satisfies policy demands and improves the
effectiveness of the network service instance layout. We model SCM as an integer linear programming
(ILP) problem, and particle swarm optimization (PSO) [18] is used to solve the SCM problem.
The contributions of this work are as follows.
1. Two scenarios are shown to illustrate that the efficiency of the network resource layout
decreases with network evolution and that service chain migration is utilized to improve
the situation.
2. An SCM framework is proposed to optimize the network resource layout. We (...truncated)