Resource Allocation for Network Slices in 5G with Network Resource Pricing
Resource Allocation for Network Slices in 5G with Network Resource Pricing
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DOI：
10.1109/glocom.2017.8254074
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发表时间：
2017-12
期刊：
影响因子：
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通讯作者：
G. Wang;G. Feng;W. Tan;Shuang Qin;Ruihan Wen;Sanshan Sun
中科院分区：
文献类型：
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作者：
G. Wang;G. Feng;W. Tan;Shuang Qin;Ruihan Wen;Sanshan Sun
端到端网络切片已被视为下一代移动的网络（5G）的关键使能器，其中切片提供商（SP）为切片客户（SC）创建各种网络切片以适应不同的服务。由于资源隔离，对于共存的多个网络切片，\textit {即}网络切片尺寸确定对于最大化网络资源效率是必要的。从运营商的角度来看，SP和SC都追求盈利的商业模式。然而，资源效率和利润最大化之间的关系至今还不清楚。在本文中，我们研究了网络切片尺寸与资源定价政策，通过探索这种关系。我们首先开发了一个优化框架，网络切片尺寸，其中切片客户的问题（SCP）最大限度地提高SC的利润和切片供应商的问题（SPP）最大限度地提高净社会福利（资源效率）。我们发现，当资源稀缺时，社会净福利最大化和SP的利润是两个一致的目标，否则，有一个权衡。基于这一发现，我们提出了一个低复杂度的分布式算法，以实现接近最优的净社会福利与利润保证SP/SC。仿真和数值结果验证了我们提出的切片尺寸策略的有效性，这将有助于充分发挥网络切片的能力。
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.