NeTS: Medium: Collaborative Research: Tango: Performance and Fault Management in Cellular Networks through Device-Network Cooperation

蜂窝网络已成为我们所依赖的基础设施的一部分，而无需停下来思考此类网络背后的巨大复杂性。这些网络为各种各样的移动的设备提供服务，并在各种各样的无线电环境中运行。此类网络的故障并不罕见，我们将其后果视为生活中的事实，抱怨电话掉线和数据中断。同样，我们也会遇到性能下降的情况，无论是通话的语音质量还是连接速度。随着蜂窝网络上业务量的快速增长和蜂窝频谱紧缩，预计这些情况在近期到中期的将来会变得更加严重。此外，在当今的网络中，没有设施通过编排地理上分散的移动的设备的整个网络来向设备提供服务，例如，用于提供即将到来的龙卷风的路径的“视频”。在该项目中，研究人员提出了这样的观点，即，与其对故障或性能降级进行反应式管理，还需要构建到蜂窝网络中，积极主动地管理这些事件。主要困难在于，对于终端设备来说，网络基本上被认为是一个黑盒子。关于网络的条件，例如蜂窝基础设施的某些元件的拥塞或过载，对于移动的终端设备上的应用不可见。同样，设备内的大部分应用程序生态系统对网络不可见。因此，网络不知道某个应用的延迟要求是什么，或者它在不久的将来将对网络提出什么要求。建议的解决方案方法将把这个黑盒方法的头，并使主动故障和性能管理和一个全新的应用程序类通过网络和设备之间的合作，探戈的排序。项目目标将通过两个协同项目的推力来实现。第一个项目名为“故障管理和协调服务”，该团队将开发实时蜂窝数据的计算和统计模型以及相应的分析工具、用于预测硬故障和软故障的机器学习算法以及避免故障的缓解措施。预测故障。它还将在蜂窝网络和最终用户之间开发协调服务，以在“参与式传感”的大伞下实现全系统的目标。在第二个推力中，称为“性能驱动设计”，该团队将开发一个API，该API将允许蜂窝设备和蜂窝网络合作，以实现共同的期望系统级属性，例如更高的数据带宽。它将通过延迟容忍流量的回填和移动的设备的计算卸载来提供先进的流量管理方案，利用团队成员最近在Cirrus Clouds项目中的努力。 该项目将开发一个小型LTE/UMTS测试平台，用于开放实验、开放数据访问和评估上述协议。

Cellular networks have become a part of the infrastructure that we rely on without pausing to think of the enormous complexity that underlies such networks. These networks serve an amazing diversity of mobile devices and operate in an amazing diversity of radio environments. Failures in such networks are not uncommon and we take their consequences in our stride as a fact of life, complaining about call drops and data disconnections. Similarly, we also encounter performance degradations, either in voice quality of calls or connection speeds. With the fast increasing amount of traffic on cellular networks and the cellular spectrum crunch, these conditions are expected to become more severe in the near to mid-term future. Further, in today's networks, there is no facility to provide services to a device by orchestrating an entire network of geographically dispersed mobile devices, such as, for providing a "video" of the path of an oncoming tornado.In this project, the researchers put forward the view that rather than reactive management of failures or performance degradations, there is a need to build into cellular networks, proactive management of such events. The primary difficulty for this is that, to the end devices, the network is considered essentially as a black box. Conditions about the network, such as, congestion or overload of some elements of the cellular infrastructure, are not made visible to the applications on the mobile end devices. Likewise, much of the application eco-system within a device is not made visible to the network. Thus, it is not known to the network what is the latency requirement of some application or what demand it is going to place in the near future on the network. The proposed solution approach will turn this black box approach on its head and enable proactive fault and performance management and an entirely new class of applications through cooperation between the network and the devices, a Tango of sorts.The project goals will be accomplished through two synergistic project thrusts. In the first, called "Fault Management and Orchestrated Services", the team will develop computational and statistical models for the real-time cellular data and analytics tools for the same, machine learning algorithms for predicting hard and soft failures, and mitigation actions for avoiding predicted failures. It will also develop orchestrated services between the cellular network and the end users to achieve system-wide goals under the broad umbrella of "participatory sensing". In the second thrust, called "Performance-driven Design", the team will develop an API that will allow the cellular devices and the cellular network to cooperate for achieving common desired system-level properties, such as, higher data bandwidth. It will provide advanced traffic management schemes through back-filling of delay-tolerant traffic and computation offloading from the mobile devices, leveraging a team member's recent efforts in the Cirrus Clouds Project. The project will result in the development of a miniature LTE/UMTS testbed for open experimentation, open data access, and evaluation of the protocols mentioned above.