Recent years have witnessed an increasing diversity of network services and novel applications, which are subject to a wide spectrum of service requirements with respect to bandwidth, throughput, and latency. Energy-efficiency of networks and systems becomes a dramatically growing concern, due to both increasing energy cost and CO2 emission. 5G mobile networks are being recognised as the next-generation Internet to meet the varying needs of diversified services and to reduce the carbon emissions of telecom infrastructure and data centres. In contrast to the network functions built with dedicated equipment in the current network, network elements in 5G mobile networks are provided as Virtual Network Functions (VNF, software implementations of network functions), which are elastically orchestrated in the form of Service Function Chains (SFC) to meet dynamic service demands and energy-efficiency goals.
The SFC orchestration can be performed in two steps: (i) VNF chaining, to define the order in which network functions are connected to form an SFC; (ii) SFC placement, to define how the SFC is embedded into the physical network. The essential features in 5G, such as cross-domain differentiated service and network dynamicity and uncertainty, have made traditional chaining methods and placement models inapplicable for 5G mobile services. Therefore, significant efforts have been devoted to tackling the research challenges of SFC orchestration.
Existing studies have primarily leveraged obvious mutual VNF dependencies to perform VNF chaining. However, such a method cannot determine the global ordering for all involved VNFs of an end-to-end 5G service. Furthermore, it narrows the channel to create SFCs with the aim of optimising the differentiated services and energy-efficiency when being instantiated in a physical network. In addition, SFC placement has been considered as a deterministic scheduling problem with the complete service and network information known as a priori. However, when applied to 5G mobile networks, additional challenges are presented in that network resource and service requirements vary at runtime due to the factors of e.g. time-varying user mobility and dynamic network management. Until now, an energy-efficient SFC orchestration in 5G mobile networks, considering both optimal VNF chaining and dynamic service demands and substrate resource capacities, has not been reported in the existing literature.
This project will investigate VNF chaining and SFC placement in order to achieve energy-efficient and proactive SFC orchestration in the context of 5G mobile networks. To tackle this challenging problem progressively, our work will be focused on three major objectives: 1) propose a uniform VNF chaining framework, that can integrate VNF dependencies, differentiated service policies, and energy-efficiency objectives, to efficiently construct SFCs; 2) develop a proactive model, considering future network and service variations at the initialisation of SFC placement, to perform practical service deployment in 5G mobile networks; 3) propose a real-time deterministic model to perform SFC placement for unforeseen variations with the aim of minimising the negative effects on network performance due to service demand violations. The insights into the energy-efficient VNF chaining framework obtained in Objective 1 will be fed into the SFC placement models in Objective 2 and Objective 3. The research proposed in this project is the first of its kind on the energy-efficient SFC orchestration in 5G mobile networks. In the long-term aim, the implications of this research will contribute to 5G service orchestration in both theoretical and practical sides and pave the way for future green 5G mobile networks.
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