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TPStream: low-latency and high-throughput temporal pattern matching on event streams

distributed AND PARALLEL DATABASES 2021年第2期39卷 361-412页

作者： Korber, Michael Glombiewski, Nikolaus Morgen, Andreas Seeger, Bernhard Univ Marburg Database Syst Grp Marburg Germany

Sequential pattern matching to detect a user-defined sequence of conditions on event streams is a key feature in modern event processing systems. However, the sequential nature of event based pattern matching has two major deficiencies. First, it is hardly possible to express complex temporal relationships between situations lasting for periods of time. Because events are equipped with a single timestamp only, the expressible temporal relations are limited to before/after/at the same time. Second, a sequential pattern is mapped to a continuous subsequence of the input stream starting with an arbitrary event, making efficient parallelization a hard problem. In this paper we present TPStream, a novel event processing operator for complex temporal pattern matching on event streams. TPStream first summarizes incoming events to situations lasting for periods of time, before it matches temporal patterns. With situations, temporal patterns can easily be defined based on Allen's interval algebra. We also show that situation based temporal pattern matching can be efficiently executed in parallel using multiple threads on a single machine or multiple machines in a cluster. Finally, we present adaptive optimization components continuously tuning the execution strategy of TPStream towards the lowest possible result latency with respect to the overall system load. The results of our experimental evaluation show that TPStream is capable of processing high-volume event streams with both low latency and high throughput while outperforming applicable CEP solutions from academia and industry.

关键词： event processing Pattern matching Query optimization Parallel event processing distributed event processing

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A high-throughput, scalable solution for calculating frequent routes and profitability of New York taxis 15

A high-throughput, scalable solution for calculating frequen...

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Proceedings of the 9th ACM International Conference on distributed event-Based Systems

作者： Amila Suriarachchi Shrideep Pallickara Colorado State University Fort Collins Colorado

ISBN: (纸本)9781450332866

processing complex queries on unbounded event streams in real-time, is a challenge for many data processing systems. These systems are expected to process data with reduced latency to generate real-time events, and at high throughput to minimize the required hardware. In this regard, Grand Challenge 2015 [6] focuses on evaluating two queries (frequent routes and profitable cells) in real-time with low latency and high throughput. These queries involve processing windows of thousands of records. Firstly, such processing demands efficient data structures and algorithms to minimize the processing overhead. Secondly, the system should partition data to evaluate them in parallel to make it *** this paper, we present a set of data structures that we designed to evaluate the aforementioned queries with O(log n) time complexity and a data partitioning technique to evaluate them in parallel. We then evaluate our solution on a single machine as well as in a distributed setting in a commodity cluster of machines over a 1Gbps LAN. We were able to process the frequent routes query with the 173 million trips dataset within 5 minutes with less than 4 millisecond latency and the profitable cells query with same dataset within 11 minutes with less than 5 millisecond latency.

关键词： real-time analytics time complexity event stream processing running median distributed event processing

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distributed QoS-aware scheduling in storm 15

Distributed QoS-aware scheduling in storm

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Proceedings of the 9th ACM International Conference on distributed event-Based Systems

作者： Valeria Cardellini Vincenzo Grassi Francesco Lo Presti Matteo Nardelli University of Rome "Tor Vergata" Italy

Storm is a distributed stream processing system that has recently gained increasing interest. We extend Storm to make it suitable to operate in a geographically distributed and highly variable environment such as that... 详细信息

ISBN: (纸本)9781450332866

关键词： self-adaptive scheduler storm data streaming distributed event processing resource management

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On Detection and Tracking of Variant Phenomena Clouds

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ACM TRANSACTIONS ON SENSOR NETWORKS 2014年第2期10卷 34-34页

作者： Thai, My T. Tiwari, Ravi Bose, Raja Helal, Abdelsalam Univ Florida Gainesville FL 32611 USA

Phenomena clouds are characterized by nondeterministic, dynamic variations of shapes, sizes, direction, and speed of motion along multiple axes. The phenomena detection and tracking should not be limited to some traditional applications such as oil spills and gas clouds but also be utilized to more accurately observe other types of phenomena such as walking motion of people. This wider range of applications requires more reliable, in-situ techniques that can accurately adapt to the dynamics of phenomena. Unfortunately, existing works which only focus on simple and well-defined shapes of phenomena are no longer sufficient. In this article, we present a new class of applications together with several distributed algorithms to detect and track phenomena clouds, regardless of their shapes and movement direction. We first propose a distributed algorithm for in-situ detection and tracking of phenomena clouds in a sensor space. We next provide a mathematical model to optimize the energy consumption, on which we further propose a localized algorithm to minimize the resource utilization. Our proposed approaches not only ensure low processing and networking overhead at the centralized query processor but also minimize the number of sensors which are actively involved in the detection and tracking processes. We validate our approach using both real-life smart home applications and simulation experiments, which confirm the effectiveness of our proposed algorithms. We also show that our algorithms result in significant reduction in resource usage and power consumption as compared to contemporary stream-based approaches.

关键词： Design Algorithms Performance Sensor networks distributed event processing phenomena detection and tracking optimization

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Adaptive Speculative processing of Out-of-Order event Streams

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ACM TRANSACTIONS ON INTERNET TECHNOLOGY 2014年第1期14卷 4-4页

作者： Mutschler, Christopher Philippsen, Michael Univ Erlangen Nurnberg CS Dept Programming Syst Grp D-91058 Erlangen Germany Fraunhofer IIS Erlangen Germany Fraunhofer Inst Integrated Circuits IIS D-91058 Erlangen Germany

distributed event-based systems are used to detect meaningful events with low latency in high data-rate event streams that occur in surveillance, sports, finances, etc. However, both known approaches to dealing with the predominant out-of-order event arrival at the distributed detectors have their shortcomings: buffering approaches introduce latencies for event ordering, and stream revision approaches may result in system overloads due to unbounded retraction cascades. This article presents an adaptive speculative processing technique for out-of-order event streams that enhances typical buffering approaches. In contrast to other stream revision approaches developed so far, our novel technique encapsulates the event detector, uses the buffering technique to delay events but also speculatively processes a portion of it, and adapts the degree of speculation at runtime to fit the available system resources so that detection latency becomes minimal. Our technique outperforms known approaches on both synthetical data and real sensor data from a realtime locating system (RTLS) with several thousands of out-of-order sensor events per second. Speculative buffering exploits system resources and reduces latency by 40% on average.

关键词： Design Algorithms Performance Reliability Measurement distributed event processing out-of-order event processing publish/subscribe message-oriented middleware speculative processing low latency

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Modeling trade-offs in the design of sensor-based event processing infrastructures

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INFORMATION SYSTEMS FRONTIERS 2012年第2期14卷 317-330页

作者： Voisard, Agnes Ziekow, Holger Humboldt Univ Inst Informat Syst D-10178 Berlin Germany Fraunhofer Inst Software & Syst Engn ISST D-10623 Berlin Germany Free Univ Berlin D-10623 Berlin Germany

Systems for distributed event processing have recently gained increasing attention in a broad range of application domains. This raises the demand for methods to adapt the system design to application-specific needs. Our approach considers (1) trade-offs regarding the hardware infrastructure and (2) trade-offs in the software design. For the underlying model we categorize events along the dimensions of temporal complexity and physical distribution. This yields a categorization of events that drives trade-offs in the infrastructure design. The presented model supports design decisions in dependence on application-specific event properties and design goals.

关键词： event-based systems distributed event processing Architecture Design guidelines

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Provenance and Impact of Complex event processing (CEP): A Retrospective View

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IT-INFORMATION TECHNOLOGY 2009年第5期51卷 243-249页

作者： Chakravarthy, Sharma Adaikkalavan, Raman Univ Texas Arlington CSE Dept & IT Lab 416 Yates St300 Nedderman Hall Arlington TX 76019 USA Indiana Univ South Bend Comp & Informat Sci South Bend IN 46634 USA

This paper retrospectively outlines the progress of event-based capability over the last three decades. It further briefly elaborates the impact of this technology and how it has been adapted for a variety of domains and applications. Although research on event-based approaches started in a humble manner with the intention of introducing triggers in database management systems for monitoring application state and to automate applications by reducing/eliminating user intervention, currently it has become a force to reckon with as it finds use in many diverse domains. This is primarily due to the fact that a large number of real-world applications are indeed event-driven for which this paradigm is the most appropriate.

关键词： H.2.4 [Information Systems: Database Management: Systems] H.2.8 [Information Systems: Database Management: Database Applications] H.3.3 [Information Systems: Information Storage and Retrieval: Information Search and Retrieval] D.4.6 [Software: Operating Systems: Security and Protection] complex event processing ECA Rules event-based applications distributed event processing

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Autonomic configuration and recovery in a mobile agent-based distributed event monitoring system

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SOFTWARE-PRACTICE & EXPERIENCE 2007年第5期37卷 493-522页

作者： Tripathi, Anand R. Kulkarni, Devdatta Talkad, Harsha Koka, Muralidhar Karanth, Sandeep Ahmed, Tanvir Osipkov, Ivan Univ Minnesota Dept Comp Sci Minneapolis MN 55455 USA

In this paper we present a framework for building policy-based autonomic distributed agent systems. The autonomic mechanisms of configuration and recovery are supported through a distributed event processing model and a set of policy enforcement mechanisms embedded in an agent framework. Policies are event-driven rules derived from the system's functional and non-functional requirements. Agents in the network monitor the system state for policy violation conditions, generate appropriate events, and communicate them to other agents for cooperative filtering, aggregation, and handling. A set of agents perform policy enforcement actions whenever events signifying any policy violation conditions occur. Policies are defined using a specification framework based on XML. The policy enforcement agents interpret the policies given in XML. We illustrate the utility of this framework in the context of an agent-based distributed network monitoring application. We also present an experimental evaluation of our approach. Copyright (C) 2006 John Wiley & Sons, Ltd.

关键词： agent-based systems distributed event processing autonomic systems policy-based system management

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