Resource Allocation for Network Slices in 5G with Network Resource Pricing

End-to-end network slicing has been viewed as a key enabler for the next generation mobile network (5G), where a Slice Provider (SP) creates various network slices for Slice Customers (SCs) to accommodate diverse services. Due to resource isolation, effective resource allocation for coexisted multiple network slices, \textit{i.e.} network slice dimensioning, is essential to maximize network resource efficiency. From the perspective of operators, both SP and SC pursue a profit-earning business model. However, the relationship between resource efficiency and profit maximization is not clear so far. In this paper, we study network slice dimensioning with resource pricing policy, by exploring this relationship. We first develop an optimization framework for network slice dimensioning, in which the Slice Customer's Problem (SCP) maximizes the SC's profit and the Slice Provider's Problem (SPP) maximizes net social welfare (resource efficiency). We find that maximization of net social welfare and SP's profit are two consistent objectives when resources are scarce; otherwise, there is a tradeoff. Based on this finding, we propose a low-complexity distributed algorithm to achieve near-optimal net social welfare with profit guarantee for SP/SCs. Simulations and numerical results verify the effectiveness of our proposed slice dimensioning strategy, which can help fully exploiting the capability of network slicing.

[1]  Mikio Iwamura NGMN View on 5G Architecture , 2015, 2015 IEEE 81st Vehicular Technology Conference (VTC Spring).

[2]  Frank Kelly,et al.  Charging and rate control for elastic traffic , 1997, Eur. Trans. Telecommun..

[3]  Minlan Yu,et al.  Rethinking virtual network embedding: substrate support for path splitting and migration , 2008, CCRV.

[4]  Juanjo Unzilla,et al.  Service description in the NFV revolution: Trends, challenges and a way forward , 2016, IEEE Communications Magazine.

[5]  Gang Wang,et al.  Protocol Function Block Mapping of Software Defined Protocol for 5G Mobile Networks , 2018, IEEE Transactions on Mobile Computing.

[6]  Tarik Taleb,et al.  Fine-grained resource-aware virtual network function management for 5G carrier cloud , 2016, IEEE Network.

[7]  Biswanath Mukherjee,et al.  Optimal Network Function Virtualization Realizing End-to-End Requests , 2014, GLOBECOM 2014.

[8]  Hang Zhang,et al.  5G wireless network: MyNET and SONAC , 2015, IEEE Network.

[9]  Steven H. Low,et al.  Optimization flow control—I: basic algorithm and convergence , 1999, TNET.

[10]  Xavier Hesselbach,et al.  Virtual Network Embedding: A Survey , 2013, IEEE Communications Surveys & Tutorials.

[11]  Tony Q. S. Quek,et al.  Cross-Layer Resource Allocation With Elastic Service Scaling in Cloud Radio Access Network , 2015, IEEE Transactions on Wireless Communications.

[12]  Joseph Naor,et al.  Near optimal placement of virtual network functions , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).