Partially Symmetric Service Function Chains With the variety of proposed networking services and the growing requirements of subscribers, networking infrastructures strive to offer the best quality of service. Complex services, such as security services require a composition of intermediate Service Functions (SFs). Service Function Chaining (SFC) is a new trending networking concept that enables composing and forcing the order in which service functions are invoked. With the emergence of Software Defined Networks (SDN) and Network Function Virtualization (NFV), the complexity of deploying service chains is reduced. However, configuring traffic symmetry remains a complex operation, especially with composed SFs. Ensuring traffic symmetry for chains is still challenging, particularly with chains of different symmetry requirements. In this paper, we discuss the problem of traffic symmetry for SFC and showcase the issue of partial symmetry chains. Finally, we present a new approach that calculates the reverse path of service chains composed of symmetrical and asymmetrical SFxe2x80x99s requirements. Our results show that our proposed solution reduces the forwarding state and potentially reduces the traffic delay.

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.