A multiservice differentiation traffic management strategy in SDN cloud data center Abstract   The cloud computing technology makes services more diverse, and users have different needs for multiservice experience. The operator cloud data centers support more services and users, resulting in a rapid growth in traffic. Consequently, the traditional network architectures and technologies can no longer meet these traffic management requirements. To address this problem, this paper proposes a multiservice differentiated (MSD) traffic management strategy for the operator SDN cloud data center. The MSD traffic management rules and model are designed according to the operational requirements in cloud data centers. Fibonacci tree optimization algorithm (FTO) is improved for matching the MSD model to optimize the differentiated traffic management solutions. An operator SDN cloud data center test platform is established to verify the effectiveness of the strategy. The results show that the MSDFTO strategy can obtain multiple differentiated traffic management schemes through one single optimization and it outperforms ECMP. In addition, it can properly manage the multiservice traffic and greatly improve the network performance and service experience in cloud data centers.

CostAware and DelayConstrained Service Function Orchestration in MultiDataCenter Networks A virtualized network service is generally implemented via a service function chain(SFC) composed of a set of VNFs in an ordered sequence. The SFC orchestration aims to deploy SFCs on limited and distributed cloud infrastructures with various optimization targets while guaranteeing QoS requirement of the network service. In this paper, we address the problem of SFC orchestration in the multiple data centers aiming at minimizing deploying cost with delay constraint. Especially, we take into account the impact of VNFs on the link cost and multiple ingressesegresses of SFCs. We formulate the problem as a Mixed Integer Linear Programming (MILP) model and propose a heuristic algorithm called CostAware and DelayConstrained SFC Orchestration (CADCSO) to the problem. Extensive simulation results show that CADCSO can achieve nearoptimal results with much less time in smallscale network environments. Compared with the existing solution CASO, CADCSO can reduce the average cost by at least 30% and increase the acceptance ratio by around 23% in largescale network environments. Furthermore, CADSCO outperforms CASO significantly in the case of multiple ingressesegresses.