Showing papers by "Nesime Tatbul published in 2008"
01 Aug 2008
TL;DR: This paper presents an optimal but exponential-time dynamic programming algorithm and two polynomial-time heuristic algorithms, as well as their extensions for detecting multiple complex events with common sub-expressions, and describes the behavior and performance of the solutions.
Abstract: Complex Event Detection (CED) is emerging as a key capability for many monitoring applications such as intrusion detection, sensor-based activity & phenomena tracking, and network monitoring. Existing CED solutions commonly assume centralized availability and processing of all relevant events, and thus incur significant overhead in distributed settings. In this paper, we present and evaluate communication efficient techniques that can efficiently perform CED across distributed event sources.Our techniques are plan-based: we generate multi-step event acquisition and processing plans that leverage temporal relationships among events and event occurrence statistics to minimize event transmission costs, while meeting application-specific latency expectations. We present an optimal but exponential-time dynamic programming algorithm and two polynomial-time heuristic algorithms, as well as their extensions for detecting multiple complex events with common sub-expressions. We characterize the behavior and performance of our solutions via extensive experimentation on synthetic and real-world data sets using our prototype implementation.
141 citations
01 Mar 2008
TL;DR: This paper describes algorithms for balanced and resilient load distribution, scalable distributed load shedding, and cooperative and self-configuring high availability in Borealis and presents experimental results from the prototype implementation showing the effectiveness of these algorithms.
Abstract: Borealis is a distributed stream processing engine that has been developed at Brandeis University, Brown University, and MIT. It extends the first generation of data stream processing systems with advanced capabilities such as distributed operation, scalability with time-varying load, high availability against failures, and dynamic data and query modifications. In this paper, we focus on aspects that are related to load management and high availability in Borealis. We describe our algorithms for balanced and resilient load distribution, scalable distributed load shedding, and cooperative and self-configuring high availability. We also present experimental results from our prototype implementation showing the effectiveness of these algorithms.
24 citations