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

个人移动的计算设备的激增沿着过多的数据密集型移动的应用在过去几年中已经导致对无处不在的高数据速率无线通信的需求的巨大增长。为了满足不断增长的容量需求而对大量独立蜂窝基站（BS）进行额外部署和维护，由于过多的资本和运营支出而效率非常低。目前，静态地配置和部署多个无线电接入网络（RAN），每个RAN由地理上接近的BS组成;然而，这种方法不允许任何余量来处理由于不断变化的移动的应用环境和诸如紧急情况的意外事件而引起的容量需求的波动。Cloud-RAN（C-RAN）是一种新的宽带无线接入模式，它由分布在广阔地理区域内的远程无线单元（RRU）组成，远程无线单元（RRU）由位于集中式BS池中的远程虚拟基站（VBSs）控制。其可以被动态地调整大小以满足每用户容量需求的波动。这种弹性使得能够改进C-RAN中的用户服务质量（QoS）以及能量和计算资源利用的效率。然而，虚拟机（VM）供应，即，决定了？尺寸？保持VBS的VM的数量以及将VM适当地分配给物理服务器是不平凡的挑战。该项目的任务包括设计和开发（i）需求感知的动态虚拟机配置算法，该算法依赖于软件中实现的通信功能的计算复杂性和内存占用的离线分析;（ii）利用VBS协同定位模型的QoS感知的虚拟机分配算法;（iii）在虚拟化企业级服务器上建立C-RAN试验平台，通过模拟活动验证分析和分配解决方案。计算资源的有效设计和管理。PI将创建关于弹性资源分配的新教学模块，提供交流计划的机会，利用罗格斯大学现有的少数民族学生外联网络，并纳入学生交流计划。

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.