Composite (or Complex) event processing (CEP) systems search sequences of incoming events for occurrences of user-specified event patterns. Recently, they have gained more attention in a variety of areas due to their powerful and expressive query language and performance potential. Sequentiality (temporal ordering) is the primary way in which CEP systems relate events to each other. In this paper, we present a CEP system called ZStream to efficiently process such sequential patterns. Besides simple sequential patterns, ZStream is also able to detect other patterns, including conjunction, disjunction, negation and Kleene closure.

Sensors capable of sensing phenomena at high data rates on the order of tens to hundreds of thousands of samples per second are now widely deployed in many industrial, civil engineering, scientific, networking, and medical applications. In aggregate, these sensors easily generate several million samples per second that must be processed within milliseconds or seconds. The computation required includes both signal processing and event stream processing. XStream is a stream processing system for such applications. XStream introduces a new data type, the signal segment, which allows applications to manipulate isochronous (regularly spaced in time) collections of sensor samples more conveniently and efficiently than the asynchronous representation used in previous work. XStream includes a memory manager and scheduler optimizations tuned for processing signal segments at high speeds. In benchmark comparisons, we show that XStream outperforms a leading commercial stream processing system by more than three orders of magnitude. On one application, the commercial system processed 72.7 Ksamples/sec, while XStream processed 97.6 Msamples/sec.

WaveScope is a data management and continuous sensor data system that integrates relational database and signal processing operations into a single system. WaveScope is motivated by a large number of signal-oriented streaming sensor applications, such as: preventive maintenance of industrial equipment; detection of fractures and ruptures in various structures; in situ animal behavior studies using acoustic sensing; network traffic analysis; and medical applications such as anomaly detection in EKGs. These target applications use a variety of embedded sensors, each sampling at fine resolution and producing data at high rates ranging from hundreds to hundreds of thousands of samples per second. Though there has been some work on applications in the sensor network community that do this kind of signal processing (for example, shooter localization [5], industrial equipment monitoring [4], and urban infrastructure monitoring [2]), these applications are typically custombuilt and do not provide reusable high-level programming framework suitable for easily building new signal processing applications with similar functionality. This poster shows how WaveScope supports these types of application in a single, unified framework, providing both high run-time performance and easy application development.