Programming Support for Fault-Tolerant Distributed Live Applications

容错分布式实时应用程序的编程支持

基本信息

项目摘要

Decentralized distributed computing platforms, comprising a mixture of interconnected web servers, decentralized Clouds, mobile and IoT devices, have encouraged the emergence of distributed data-driven and/or interactive applications, which continuously observe and correlate sensor data, logging activities, other event flows, user actions, etc., and in response update their state in real time. We call these applications distributed live applications. Such applications are inherently complex due to asynchrony and the inverted control of user interactions and event/data flow, which encourages programming in some form of continuation-passing style – an error-prone style leading to the so-called Callback Hell. The issues are amplified in a context where computations are distributed across interconnected machines/devices that are not under the control of a single unit. Our specific focus is on complexity due to disconnects and crashes that are ubiquitous in a such a setting (mobile devices may have poor connectivity and shut down when batteries run low; cloud servers are rebooted without prior notice, and a failed network switch results in lost connections between servers).Our hypothesis is that a good fraction of this complexity is due to poor abstractions offered by the existing programming languages and frameworks for distributed applications, which force developers to program the systems and to reason about them in terms of callbacks/continuations. Reactive programming (RP) originally proposed for enabling direct style programming of interactive desktop applications has the potential to address such complexity. However, RP languages/frameworks lack proper support for fault tolerance. In comparison, actor languages, which are often the programming model of choice in the context of distributed live applications feature less declarative message passing abstractions, while cloud languages and programming platforms for big-data processing are not designed with liveliness in mind. The goal of this proposal is to develop a programming model and language for fault-tolerant distributed live applications that brings the benefits of the declarative direct-style of the RP model to this complex domain to enable a higher-level of (automated) reasoning about such systems in the presence of faults. In particular, we aim to leverage unique features of the RP paradigm to generalize automated fault handling – that frameworks like Spark and Flink provide in an controlled environment – to arbitrary live applications deployed on decentralized distributed systems. Furthermore, we will extend RP abstractions with support for error propagation to enable application developers to explicitly handle faults, whenever automated handling is not possible or meaningful. We will formally model our language to prove it properties and we will implement it on top of an existing reactive language.
分散式分布式计算平台,包括互连的web服务器、分散式云、移动的和IoT设备的混合,已经鼓励分布式数据驱动和/或交互式应用的出现,其连续地观察和关联传感器数据、记录活动、其他事件流、用户动作等,并且作为响应,真实的更新它们的状态。我们将这些应用程序称为分布式实时应用程序。由于用户交互和事件/数据流的反向控制,这些应用程序本质上是复杂的,这鼓励以某种形式的延续传递风格进行编程-一种容易出错的风格,导致所谓的回调地狱。在计算分布在不受单个单元控制的互连机器/设备上的情况下,这些问题被放大。我们特别关注的是由于在这样的环境中普遍存在的断开和崩溃而导致的复杂性(移动的设备可能连接性差,在电池电量不足时关闭;云服务器在没有事先通知的情况下重新启动,而失败的网络交换机会导致服务器之间的连接丢失)我们的假设是,这种复杂性的很大一部分是由于现有的分布式编程语言和框架提供的糟糕的抽象。应用程序,这迫使开发人员对系统进行编程,并根据回调/延续对它们进行推理。反应式编程(RP)最初提出的交互式桌面应用程序的直接风格的编程有可能解决这种复杂性。然而,RP语言/框架缺乏对容错的适当支持。相比之下,Actor语言通常是分布式实时应用程序中的编程模型,其声明性消息传递抽象较少,而用于大数据处理的云语言和编程平台在设计时并没有考虑到活跃性。该建议的目标是开发一种容错分布式实时应用程序的编程模型和语言,将RP模型的声明式直接风格的好处带到这个复杂的领域,以实现更高级别的(自动化)推理等系统中存在的故障。特别是,我们的目标是利用RP范式的独特功能,将自动化故障处理(Spark和Flink等框架在受控环境中提供)推广到部署在分散式分布式系统上的任意实时应用程序。此外,我们将通过支持错误传播来扩展RP抽象,以使应用程序开发人员能够在自动处理不可能或没有意义时显式处理错误。我们将正式建模我们的语言来证明它的属性,我们将在现有的反应式语言之上实现它。

项目成果

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Professorin Dr.-Ing. Mira Mezini其他文献

Professorin Dr.-Ing. Mira Mezini的其他文献

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