Data Mining - Concepts and Techniques.

National Institute of Standards and Technology における超伝導研究及び生活

We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acquiring data, we are able to significantly reduce power consumption over traditional passive systems that assume the a priori existence of data. We discuss simple extensions to SQL for controlling data acquisition, and show how acquisitional issues influence query optimization, dissemination, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices.

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TinyDB: an acquisitional query processing system for sensor networks

Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem. On the contrary, modern data models exacerbate the problem: In order to manipulate large sets of complex objects as efficiently as today's database systems manipulate simple records, query-processing algorithms and software will become more complex, and a solid understanding of algorithm and architectural issues is essential for the designer of database management software. This survey provides a foundation for the design and implementation of query execution facilities in new database management systems. It describes a wide array of practical query evaluation techniques for both relational and postrelational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.

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Query evaluation techniques for large databases

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The design of an acquisitional query processor for sensor networks

Making a database system active entails developing an expressive event specification language with well-defined semantics, algorithms for the detection of composite events, and an architecture for an event detector along with its implementation. Thii paper presents the semantics of composite events using the notion of a global event history (or a global event-log). Parameter contexts are introduced and precisely defined to facilitate efficient management and detection of composite events. Finally, an architecture and the implementation of a composite event, detector is analyzed in the context of an object-oriented active DBMS.

Composite Events for Active Databases: Semantics, Contexts and Detection

Making a database system active to meet the requirements of a wide range of applications entails developing an expressive event specification language and its implementation. Extant systems support mostly database events and in some cases a few predefined events.

This paper discusses an event specification language (termed Snoop) for active databases. We define an event, distinguish between events and conditions, classify events into a class hierarchy, identify primitive events, and introduce a small number of event operators for constructing composite (or complex) events. Snoop supports temporal, explicit, and composite events in addition to the traditional database events. The novel aspect of our work lies not only in supporting a rich set of events and event expressions, but also in the notion of parameter contexts. Essentially, parameter contexts augment the semantics of composite events for computing their parameters. For concreteness, we present parameter computation for the relational model. Finally, we show how a contingency plan that includes time constraints can be supported without stepping outside of the framework proposed in this paper.

Snoop: an expressive event specification language for active databases

Detection-based semantics does not differentiate between event detection and event occurrence and has been used for detecting events in most of the active systems that support Event-Condition-Action rules. However, this is a limitation for many applications that require interval-based semantics. In this article, we formalize the detection of Snoop (an event specification language) event operators using interval-based semantics (termed SnoopIB) in various event consumption modes. We show how events are detected using event detection graphs, and present a few representative algorithms to detect SnoopIB operators and comment on their implementation in the context of Sentinel-an active object-oriented DBMS.

SnoopIB: Interval-based event specification and detection for active databases

SnoopIB: interval-based event specification and detection for active databases

This paper proposes a new approach for supporting reactive capability in an object-oriented database. We introduce an event interface, which extends the conventional object semantics to include the role of an event generator. This interface provides a basis for the specification of events spanning sets of objects, possibly from different classes, and detection of primitive and complex events. This approach clearly separated event detection from rules. New rules can be added and use existing objects, enabling objects to react to their own changes as well as to the changes of other objects.We use a runtime subscription mechanism, between rules and objects to selectively monitor particular objects dynamically. This elegantly supports class level as well as instance level rules. Both events and rules are treated as first class objects.

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Sharma Chakravarthy

Papers

Composite Events for Active Databases: Semantics, Contexts and Detection

Snoop: an expressive event specification language for active databases

SnoopIB: Interval-based event specification and detection for active databases

SnoopIB: interval-based event specification and detection for active databases

A new perspective on rule support for object-oriented databases