NeTS: Small: Demand-Aware Dynamic Virtual Base Station Provisioning and Allocation in Cloud Radio Access Networks (C-RANs)

过去几年，个人移动计算设备的激增以及过多的数据密集型移动应用导致了对无处不在的高数据速率无线通信的需求大幅增加。额外部署和维护大量独立蜂窝基站(BSS)以满足不断增长的容量需求，由于资本和业务支出过高，效率极低。目前，多个无线接入网络(RAN)是静态配置和部署的，每个RAN由地理上邻近的BS组成；然而，这种方法不允许有任何余地来处理由于不断变化的移动应用环境和诸如紧急情况等意外事件而引起的容量需求的波动。云无线网络(Cloud-RAN，C-RAN)是由分布在广域内的远程无线单元(RRU)组成，远程无线单元(RRU)由集中的BS池中的远程虚拟基站(VBS)控制，是一种新的宽带无线接入范例，可以有效地应对容量需求的波动。这种弹性能够提高C-RAN中的用户服务质量(Qos)以及能源和计算资源利用率的效率。但是，虚拟机(VM)资源调配，即确定大小。拥有VBS的VM的数量，以及将VM适当地分配给物理服务器都不是一件容易的事。该项目的任务包括设计和开发(I)需求感知的动态VM配置算法，该算法依赖于对以软件实现的通信功能的计算复杂性和内存占用的离线剖析；(Ii)利用VBS托管模型的服务质量感知的VM分配算法；(Iii)C-RAN测试平台，用于在虚拟企业级服务器上通过仿真活动验证剖析和分配解决方案。这项工作将培养通晓计算机的本科生和研究生研究人员，他们对计算资源的节能设计和管理具有全面的知识。PI将创建关于弹性资源分配的新教学模块，为交换计划提供机会，利用罗格斯大学现有的少数族裔学生外展网络，并纳入学生交换计划。

The proliferation of personal mobile computing devices along with a plethora of data-intensive mobile applications has resulted in a tremendous increase in demand for ubiquitous and high-data-rate wireless communications over the last few years. Additional deployment and maintenance of a large number of stand-alone cellular Base Stations (BSs) to meet the growing capacity demand are highly inefficient due to excessive capital and operating expenditures. Presently, multiple Radio Access Networks (RANs), each composed of geographically proximal BSs, are statically configured and deployed; such an approach, however, does not allow for any margin to handling the fluctuations in capacity demands due to the ever transforming mobile applications landscape and unexpected events such as emergencies. Cloud-RAN (C-RAN), composed of Remote Radio Units (RRUs) distributed over a wide geographic region controlled by remote Virtual Base Stations (VBSs) housed in centralized BS pools, is a new paradigm for broadband wireless access to address the fluctuation in capacity demand efficiently.This research focuses on designing a dynamic reconfigurable cellular communication system that relies on elastic VBSs, which can be dynamically resized to meet the fluctuations in per-user capacity demands. This elasticity enables improvements in user Quality of Service (QoS) and efficiency in energy and computing resource utilization in C-RANs. However, Virtual Machine (VM) provisioning, i.e., determining the ?size? of VMs that hold VBSs, as well as appropriate allocation of VMs to physical servers are non-trivial challenges. The tasks of this project consist in the design and development of (i) a demand-aware dynamic VM provisioning algorithm that relies on an offline profiling of the computational complexity and memory footprint of the communication functionalities implemented in software; (ii) a QoS-aware VM allocation algorithm that exploits VBS co-location models; (iii) a C-RAN testbed on virtualized enterprise-class servers for validation of the profiling and allocation solutions through emulation campaigns.This work will generate computer-literate undergraduate and graduate researchers with a comprehensive knowledge of energy-efficient design and management of computing resources. The PI will create new teaching modules on elastic resource allocation, provide opportunities for exchange programs, leverage existing minority student outreach networks at Rutgers University, and incorporate student exchange programs.