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Load adaptive and fault tolerant distributed stream processing system for explosive stream data

机译:爆炸性流数据的负荷自适应容错分布式流处理系统

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As smart devices such as sensors, smartphones, and CCTVs are becoming extensively utilized recently, stream data from those smart devices are consistently generated explosively. There are also increasing cases that we notice security attacks after already important assets are damaged by cyber-targeted attacks such as APT attacks due to the lack of real-time security log processing capability. Accordingly, the demand to process and analyse the exploding stream data in real-time and in advance is consistently increasing in many application domains. However, existing distributed stream processing systems like Storm and S4 are not well adaptive when there are drastic increase of input stream data. In this paper, we propose a distributed stream processing system which supports several load adaptation techniques utilizable for various circumstances of explosive data stream, and also supports fault tolerance mechanisms to fail over in several failure situations.
机译:随着近来诸如传感器,智能电话和CCTV之类的智能设备的广泛使用,来自这些智能设备的流数据始终如一地爆炸性地生成。在越来越多的情况下,由于缺乏实时安全日志处理能力,在已经很重要的资产被以网络为目标的攻击(如APT攻击)破坏后,我们注意到安全攻击。因此,在许多应用领域中,实时且提前处理和分析爆炸流数据的需求持续增长。但是,当输入流数据急剧增加时,现有的分布式流处理系统(如Storm和S4)不能很好地适应。在本文中,我们提出了一种分布式流处理系统,该系统支持多种可用于爆炸性数据流各种情况的负载自适应技术,并且还支持在几种故障情况下进行故障转移的容错机制。

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