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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >On Composing Stream Applications in Peer-to-Peer Environments
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On Composing Stream Applications in Peer-to-Peer Environments

机译:对等环境中的组合流应用程序

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摘要

Stream processing has become increasingly important as many emerging applications call for continuous real-time processing over data streams, such as voice-over-IP telephony, security surveillance, and sensor data analysis. In this paper, we propose a composable stream processing system for cooperative peer-to-peer environments. The system can dynamically select and compose stream processing elements located on different peers into user desired applications. We investigate multiple alternative approaches to composing stream applications: 1) global-state-based centralized versus local-state-based distributed algorithms for initially composing stream applications at setup phase. The centralized algorithm performs periodical global state maintenance while the distributed algorithm performs on-demand state collection. 2) Reactive versus proactive failure recovery schemes for maintaining composed stream applications during runtime. The reactive failure recovery algorithm dynamically recomposes a new stream application upon failures while the proactive approach maintains a number of backup compositions for failure recovery. We conduct both theoretical analysis and experimental evaluations to study the properties of different approaches. Our study illustrates the performance and overhead trade-offs among different design alternatives, which can provide important guidance for selecting proper algorithms to compose stream applications in cooperative peer-to-peer environments.
机译:由于许多新兴应用程序要求对数据流进行连续的实时处理,例如IP语音电话,安全监控和传感器数据分析,因此流处理变得越来越重要。在本文中,我们提出了一种用于协作对等环境的可组合流处理系统。该系统可以动态地选择位于不同对等端上的流处理元素并将它们组成用户所需的应用程序。我们研究了组成流应用程序的多种替代方法:1)基于全局状态的集中式算法与基于局部状态的分布式算法,用于在设置阶段初始组成流应用程序。集中式算法执行定期全局状态维护,而分布式算法执行按需状态收集。 2)反应式与主动式故障恢复方案,用于在运行时维护组合流应用程序。反应性故障恢复算法可在发生故障时动态重组新的流应用程序,而前摄性方法可维护许多备份组合以进行故障恢复。我们进行理论分析和实验评估,以研究不同方法的特性。我们的研究说明了不同设计替代方案之间的性能和开销折衷,这可以为选择合适的算法以构成协作对等环境中的流应用程序提供重要指导。

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