In this paper, we propose general service-oriented end-to-end energy and delay models. They facilitate the evaluation of new schemes, by enabling flexible allocation of processing functions at multilayer radio access network. These models describe the underlaying processing of communication function (PCF)'s complexity and the induced bandwidth. We also introduce the concept of processing interference and link it to the average PCF option of the competing users at the cloud. The proposed framework shows the possibility to compensate the delay or energy degradation, e.g., due to radio environment, by reallocating processing parameters, e.g., allocation of PCF or number of virtual central processing units (VCPUs). Several conclusions are inferred from the system's evaluation. For instance, at low modulation index (MI), the behavior of overall energy consumption is dominated by PCF energy, not the transmission energy, whereas, at high MI, the behavior of overall energy consumption is dominated by transmission energy. Centralization of PCF reduces the impact of processing interference (of competing users) on the targeted service's delay from 11 to 2 ms, and service's energy consumption from 18 to 2 J. We further evaluate the impact of PCF on the decision of offloading the service, to be computed at the cloud.

中文翻译：

---

处理和无线电参数之间的相互作用：面向服务的性能研究

在本文中，我们提出了面向服务的通用端到端能量和延迟模型。通过在多层无线接入网中灵活分配处理功能，它们有助于评估新方案。这些模型描述了通信功能（PCF）的底层处理和引入的带宽。我们还介绍了处理干扰的概念，并将其链接到云中竞争用户的平均PCF选项。所提出的框架示出了通过重新分配处理参数（例如，PCF的分配或虚拟中央处理单元（VCPU）的数量）来补偿例如由于无线电环境引起的延迟或能量劣化的可能性。从系统评估中可以得出一些结论。例如，在低调制指数（MI）下，总能量消耗的行为由PCF能量而不是传输能量控制，而在高MI时，总能量消耗的行为由传输能量控制。PCF的集中化可将（竞争用户的）处理干扰对目标服务的延迟的影响从11毫秒降低到2毫秒，将服务的能耗从18 J降低到2J。我们进一步评估了PCF对卸载服务决策的影响，在云计算。