Database systems

Silberschatz, Abraham; Ullman, Jeffrey D.

doi:10.1145/122058.122059

Cited by 114 publications

(109 citation statements)

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“…The idea of pipelined execution of the algorithms which process large data sets not fitting into main memory is well known in relational database management systems [33]. The pipelined execution strategy allows to execute a database query with minimum number of external memory accesses, to save memory space to store intermediate results, and to obtain the first result as soon as possible.…”

Section: Related Workmentioning

confidence: 99%

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Stxxl: Standard Template Library for XXL Data Sets

Dementiev¹,

Kettner

Sanders³

2005

Algorithms – ESA 2005

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We present a software library Stxxl, that enables practice-oriented experimentation with huge data sets. Stxxl is an implementation of the C++ standard template library STL for external memory computations. It supports parallel disks, overlapping between I/O and computation and is the first external memory algorithm library that supports the pipelining technique that can save more than half of the I/Os. Stxxl has already been used for the following applications: implementations of external memory algorithms for computing minimum spanning trees, connected components, breadth-first search decompositions, constructing suffix arrays, and computing social network analysis metrics for huge graphs.

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Section: Related Workmentioning

confidence: 99%

“…Many external memory algorithms implemented with the Stxxl streaming layer save a factor at least two in I/Os. The pipelined processing technique is well known in the database world [33]. To the best of our knowledge we are the first who apply this method systematically in the domain of external memory algorithms.…”

Section: Streaming Layermentioning

confidence: 99%

Stxxl: Standard Template Library for XXL Data Sets

Dementiev¹,

Kettner

Sanders³

2005

Algorithms – ESA 2005

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“…Data model is a collection of conceptual tools for describing data, data relationships, data semantics, and consistency constraints [16]. Three levels of data models are defined [19]: conceptual, logical, and physical data model.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the quality of conceptual data model is most of the time subjectively measured, depending upon the "taste" of the people who do the measurement. A work by Husain et al [12] provides a way to objectively measure the quality of an entityrelationship (ER) conceptual data model (for ER model see [16]), but it is only on a property called completeness and it does not provide a whole discussion on the aspects of the quality of conceptual data model.…”

Section: Introductionmentioning

confidence: 99%

“…Data models provide the foundation to organization's activities since they support the organization's systems and data [20]. Therefore, the quality of the data models is foremost.Data model is a collection of conceptual tools for describing data, data relationships, data semantics, and consistency constraints [16]. Three levels of data models are defined [19]: conceptual, logical, and physical data model.…”

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confidence: 99%

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Measurement of the Quality of an FCO-IM Conceptual Data Model

Azizah

Bakema

Sitohang

et al. 2010

ijeei

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Data models provide the foundation to organization's activities since they support the organization's systems and data. Therefore, the quality of the data models is foremost. We describe a methodology to measure the quality of conceptual data models created using a fact oriented data modeling called Fully Communication Oriented Information Modeling (FCO-IM). The measurement method is based on the framework to measure the quality of conceptual model by Lindland et al. Four components are to be considered in the measurement: domain, model, language, and audience interpretation. The quality are measured on three aspects: syntactic quality (measured by syntax correctness), semantic quality (measured by feasible validity and feasible completeness), and pragmatic quality (measured by feasible comprehension). The method is then used to determine the quality of several FCO-IM conceptual data models that were created using a pattern language of conceptual data models, a new method in data modeling that we are currently researching. The method contributes in data modeling area by providing a quantitative and instructive way of measuring the quality of conceptual data models, especially in FCO-IM. Keywords: conceptual model, conceptual data model, data modeling, FCO-IM, measurement, pattern, quality IntroductionInformation is one of the critical assets of a modern organization. Information is extracted from data stored in database systems. An aspect of data management is the definition of the structures of data. The structures of data are designed in an activity called data modeling and the results are data models. Data models provide the foundation to organization's activities since they support the organization's systems and data [20]. Therefore, the quality of the data models is foremost.Data model is a collection of conceptual tools for describing data, data relationships, data semantics, and consistency constraints [16]. Three levels of data models are defined [19]: conceptual, logical, and physical data model. Conceptual data model is a relatively technologyindependent specification of data structures and is close to business requirements [19]. We focus on conceptual data model rather than the logical or physical data model because a conceptual data model can be viewed as the translation of business requirements into technical form of the structures of data (thus, it serves a "link" between human and machine) and providing logical and physical data model is a matter of transforming the conceptual data model using established algorithms. Thus, the challenge is how to provide high quality conceptual data models.

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Communication Protocols

2001

Asynchronous Circuit Design

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Recent advances in communication have made the use of dynamic and reconfigurable network topologies a mandatory requirement in scenarios where the participants must actively collaborate to each other to achieve a common, specific goal. A particular case of those scenarios are the Peer-to-Peer (P2P) systems. The wide applicability of P2P-based applications and its pervasive presence in corporate applications are two important factors that suggest a careful study of the communication protocols underlying these systems. Surprisingly, little effort has been invested in giving formal foundations that support both protocols and its security properties. This paper is intended to be a step towards such a research strand, using a process calculus as main resource to build such foundations. In particular, we focus on the reconfiguration problem in P2P-based applications. We propose two protocols for modeling this problem: while the first one is inspired on an existing protocol (known as the Friends Troubleshooting Network or FTN), the second constitutes an original proposal based on a multi-layered encryption system. We show how SPL (the process calculi in which both models are given) is well-suited to model and to proof certain security properties of the protocols.

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Database systems

Cited by 114 publications

References 0 publications

Stxxl: Standard Template Library for XXL Data Sets

Stxxl: Standard Template Library for XXL Data Sets

Measurement of the Quality of an FCO-IM Conceptual Data Model

Communication Protocols

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