Transferência de Aprendizado para Redes Bayesianas com Aplicação em Predição de Falha de Discos Rígidos

Predizer falhas em Discos Rígidos é muito importante para evitar perda de dados e custos adicionais. Logo, um esforço pode ser observado para encontrar métodos adequados de predição de falhas. Apesar dos resultados encorajantes alcançados por vários métodos, um aspecto notado é a falta de dados disponíveis para construir modelos confiáveis. Transferência de Aprendizado oferece uma alternativa válida, uma vez que pode ser usada para transferir conhecimento de modelos de Disco com muitos dados para Discos com menos dados. Neste trabalho, avaliamos estratégias de Transferência de Aprendizado para esta tarefa. Além disso propomos uma estratégia para construir fontes de informação baseadas no agrupamento de modelos de disco parecidos. Resultados mostraram que todos os cenários testados de transferência melhoram a performance dos métodos de predição, principalmente para Discos com muito poucos dados

DORS: Database Query Optimizer with Rule Based Search Engine

The database query optimizer is a very important and complex module in database management systems. It receives a query optimization request with a query tree as a parameter and return an optimized execution plan. The query optimization problem is NP-Hard; therefore, there are many proposals of heuristics and techniques for optimization strategies. There are also several data models (e.g objectoriented, relational, object-relational and semi-structured/XML) suitable to store information for different kinds of applications. Several optimization frameworks were proposed with the aim of making easier to build optimizers and reuse design decisions. However, they are tied to some specific language and hard to integrate with other database modules. We propose a design pattern to help the design and construction of a database optimizer. So far, we do not have knowledge about similar work. Context Different types of applications should use a suitable data model. For instance, commercial systems work well with relational data models, CAD/CAM systems need a more expressive data model as the objectoriented, and the Internet with XML [W3C] applications work well with semi-structured data models. Different data models and different kinds of applications require specific implementation of the quer

The Impact of Privacy Regulations on DB Systems

Personal data usage and collection are activities that used to grow unrestricted. However, several laws in the physical world ensure rights to people regarding their privacy and information usage. In the last years, legislators passed many laws, regulations, and acts to replicate these rights to the digital world. By doing so, new constraints, rights, and duties appear on every component of the data usage and collection workflow. In this paper, we discuss legislations’ implications, identifying impacts that these regulations introduce to current DBMS, and survey recent works that aim to solve the problems raised by these impacts, highlighting research opportunities and identifying how solutions can be achieved for the problems.</jats:p

Applying Rules for Partitioned Parallelism in OODBMS within an Optimizer Generator Framework

This work presents a rule-based approach for declarative query optimizer generation considering parallel execution in object-oriented databases. The main goal of this work is to provide a framework that can capture relevant aspects of parallel query optimization in a declarative way, combining procedural techniques with the advantages of rule processing. One of those techniques was used for determining repartitioning and selecting the algorithms to evaluate operator in a query tree considering the trade-offs between processing costs and repartitioning costs. This technique was proposed as a procedural algorithm and it was adapted to be used as rules in the context of object-oriented database optimizers. Another algorithm, used for query operator reordering in object-oriented databases, was adapted in order to consider repartitioning cost and was added to the framework. Finally, a new module for processing rules for parallelism extraction was added to the framework, providing a better support for inter-operator parallelism optimization techniques.

A distributed concurrency control mechanism for XML data

AbstractXML has become a standard for data exchange in many fields of application. Thus, a huge amount of data in this format is spread around Web and is stored in different ways. In order to manage the access of this data, concurrency control techniques have been adopted. Nevertheless, most of these techniques are developed on centralized environments and, approaches for distributed environments do not take into account the specificity of XML data. This paper presents DTX, a mechanism for distributed concurrency control of XML data, based on specific techniques for this kind of data. Aiming to evaluate DTX, experiments were conducted in order to measure its performance

An Experimental Analysis of the Use of Different Storage Technologies on a Relational DBMS

Traditional Database Management Systems (DBMSs) are built with the premise that magnetic disks such as hard disks drives (HDDs) store the data. Recently, several alternatives to HDDs have emerged, such as the solid-state drives (SSDs) based on non-volatile memory (NVM) technology such as 3D XPoint and the new generations of dynamic random access memories (DRAMs). Different characteristics of these storage technologies may impact the performance of DBMSs. In this work, we analyze the performance of a DBMS using three storage technologies as data locations:HDD, SSD NVM, and DRAM, as well as a hybrid way combining all three. To do this, we use two workloads, analytical and transactional, and we observe throughput as well as latency. After, we discuss the reasons for the results obtained for each type of storage. We also show that the query processing can benefit from the different characteristics of each storage technology to perform faster queries and, finally, we analyze the benefits of using a hybrid storage system.</jats:p