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

蜂窝网络已经成为我们所依赖的基础设施的一部分，而不会停下来思考这种网络背后的巨大复杂性。这些网络为各种各样的移动设备提供服务，并在各种各样的无线电环境中运行。这类网络中的故障并不少见，我们从容不迫地将其后果视为生活中的现实，抱怨呼叫掉线和数据断开。同样，我们也会遇到性能下降的问题，无论是通话的语音质量还是连接速度。随着蜂窝网络流量的快速增长和蜂窝频谱的紧缩，预计这些情况在近期到中期内将变得更加严重。此外，在当今的网络中，没有通过协调地理上分散的移动设备的整个网络来向设备提供服务的设施，例如，用于提供来袭龙卷风路径的“视频”。在该项目中，研究人员提出的观点是，与其对故障或性能降级进行被动管理，不如在蜂窝网络中内置对此类事件的主动管理。这样做的主要困难在于，对于终端设备来说，网络基本上被视为一个黑匣子。有关网络的条件，例如蜂窝基础设施的某些元素的拥塞或过载，对于移动终端设备上的应用是不可见的。同样，设备内的大部分应用程序生态系统对网络也不可见。因此，网络不知道某些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颠覆这一黑箱方法，并通过网络和设备之间的合作实现主动的故障和性能管理以及全新的应用类别，这是一种探戈。项目目标将通过两个协同项目推力来实现。在第一个名为“故障管理和协调服务”的项目中，团队将开发用于实时蜂窝数据的计算和统计模型和分析工具，用于预测硬故障和软故障的机器学习算法，以及用于避免预测故障的缓解措施。它还将在蜂窝网络和终端用户之间开发协调的服务，以在“参与式感知”的广泛框架下实现全系统的目标。在被称为“性能驱动设计”的第二个推力中，该团队将开发一种API，该API将允许蜂窝设备和蜂窝网络合作，以实现共同的所需系统级特性，例如，更高的数据带宽。它将通过回填容忍延迟的流量和从移动设备卸载计算来提供先进的流量管理方案，利用团队成员最近在Cirrus Clouds项目中所做的努力。该项目将导致开发一个小型LTE/UMTS试验台，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.